Social Design Practices for Human-Scale Online Games
Posted by Lost Garden [HTML][XML][PERM][FULL] on 28 December 2018, 9:02 pm
For this year's Project Horseshoe, an annual game designer think tank, our workgroup investigated small-scale MMOs. You can read the other reports here:

Our group consisted of:
  • Alexander Youngblood, Game Designer at ArenaNet
  • Amy Jo Kim, Chief Executive Officer at Shufflebrain
  • Crystin Cox, Principal Program Manager at Microsoft
  • Daniel Cook, Chief Creative Officer at Spry Fox
  • Erin Hoffman-John, Lead Prototyper at Google
  • Isaiah Cartwright, Game Director at ArenaNet
  • Kyle Brink, Director of Production at ArenaNet
  • Link Hughes, Game Designer at ArenaNet


Many of the problems associated with making an MMO, a Massively Multiplayer Online game, come in large part from the very first term: “Massively”. An MMO is notably tricky to build due to technical issues involving server scaling, as well as design issues involving scaling economics, politics, level design, pacing, persistence, and progression. A rule of thumb is that development costs grow exponentially as the number of players increases, but for many years, there’s been an unquestioned assumption that bigger player numbers are inherently better and therefore worth pursuing.

Yet we see clear counterexamples. Many early MUDs (Multi-User Dungeons) involved populations of dozens-to-thousands of people and still have vibrant communities to this day [1]. Multiplayer Minecraft is wildly successful, despite its reliance on relatively small, instanced servers. And many modern hit games, like Fortnite, are online games that successfully limit their focus to matches of 100 or less.

What are the critical design lessons from these smaller online games—and how can current research and understanding of social psychology help make sense of those lessons? We combined our decades of experience designing social systems for online games and a deep dive into current academic research to arrive at a set of best practices and common pitfalls.
What we’ll cover in this paper:
  • What we can borrow from social psychology
  • An overview of friendship formation
  • Dunbar’s Layers and the constraints they place on social systems design
  • Social group and the constraints they also introduce
  • Big design insights
  • Opportunities for fulfilling the social motivations of players
  • Conclusion

Borrowing from social psychology

When researching what it meant to make human-scale systems, we found several key concepts from social psychology. Each provides a set of constraints for social design. Social game design operates within the physical and mental constraints of the human animal, so it pays to understand these constraints and build them into our designs.


A friendship is a single social bond between two people. Friendship formation is a distinct process involving proximity, similarity, reciprocity, and disclosure.

Dunbar’s Layers

An individual has a highly structured distribution of relationship bonds. People tend to have a maximum of 150 total friendships [2], including 50 good friendships, which include 15 best friendships, which, in turn, include 5 intimate friendships. This web of relationships can be modeled as an egocentric network with the individual at the center. This paper focuses primarily on the implications of Dunbar’s Layers for human-scale social design in online games.

Social groups

A social group of is a collection of people brought together for a shared task or interest. Groups contain multiple overlapping individual networks. The performance of the group, as a whole, is dependent on how the friendship bonds across the entire group are leveraged to accomplish the shared activity.


At the most basic level, human-scale game design is about creating strong relationship bonds between individuals. Most game populations will start out with weakly-bonded individuals. You’ll need to create activities, incentives, spaces, and social structures that actively build friendship in order to enable even the most basic of trust-based activities.

This section is a brief overview. For more detailed discussion on this topic see the 2016 Project Horseshoe paper on game design for building friendships.

The basics of growing friendships

Friendship formation requires 4 key ingredients:
  • Proximity. Being close together to one another encourages frequent serendipitous interactions.
  • Similarity. Players will generally be more likely to become friends if they perceive one another to be similar.
  • Reciprocity. Players must engage in escalating back-and-forth interactions in order to negotiate shared social norms.
  • Disclosure. At higher levels of friendship, there needs to be an opportunity for safe, consensual, intimate sharing of weaknesses.
You can take any two players, put them together in matches for hundreds of hours, and if the above criteria are not met, they are unlikely to become friends. Naively tossing bodies at one another is not efficient social design.

The micro-design of social systems is all about reciprocation loops

As a designer, you specifically have to build opportunities for consensual reciprocity into your game loops. These look like the following:
  • Opening. A person performs an opening action that a second person observes. This action has a cost in terms of time, investment, skill, and other resources. For example, Player 1 asks a question in open chat, which costs time and social capital.
  • Opportunity. An opportunity is created for the second person to respond. For example, Player 2 sees the question and can answer in the same chat.
  • Response. The second person performs a responding action that acknowledges the first person. This also has a cost. For example, Player 2 offers an answer to the question in chat, which also costs time and social capital.
  • Acknowledgement. The first person acknowledges the second’s response and the loop is now complete. For example, Player 1 thanks Player 2 for answering their question in open chat.

Common Variations

  • Escalation. Either during the Response or the Acknowledgement stages of the loop, a person can escalate by opening up a new loop or prompting additional response. This is an opt-in act. For example, Player 1 asks for additional details.
  • Rejection. Either during the Response or the Acknowledgement stage, a person can either not respond or respond inappropriately, which also collapses the loop. For example, Player 2 mocks Player 1 instead of answering their questions.

Link loops together in an escalating structure

Friendship is a long-term process. Each reciprocation loop may take seconds initially, but you need thousands of linked loops to build a robust friendship.
  • Create low-cost loops with low rejection costs for early relations.
  • Create higher-cost loops for later term relationships.
  • Build space inside the later loops for expression and definition of the personal relationship between two players.
For example, friendships in an MMO tend to start out with parallel play, where two people simply see one another’s name while fighting monsters in the same area. This then escalates to helping one another; a heal spell, an emote of celebration, a dropped item. The two players may start chatting in order to take down harder monsters; they may also friend one another and start talking more about who they are and what they are interested in.

At each stage, interactions take increasing time and effort. And involve richer communication. Each micro-loop is not very expensive, but over long-term repetition of many such loops, the relationship accumulates meaningful amounts of trust.

Design these systems with the same rigor, care, and eye for economic balance that you’d put towards a combat or progression system.

Design for consent

Almost every stage of these reciprocation loops involves consent. Each party must consent to both starting, continuing, and escalating the relationship. At any point, it is totally fine for one or both parties to pull away, either to slow down or move onto some other relationship opportunity.

In the context of Dunbar’s Layers, there’s a limit on the number of people an individual can have in their lives. The process of building friendship is also the active process of curating relationships that are healthy and mutually satisfying. When players actively and enthusiastically consent to engage in your reciprocation loops, you’ll find that the relationships you build in your game are more authentic, last longer, and ultimately provide more value to your players.

Dunbar’s Layers

An individual organizes their friendships by strength of their one-to-one bonds. They have close friends they turn to in times of crisis and more casual friends, with whom they interact with less frequently. Social psychology has been studying these friendship networks for decades. One of the more reproducible findings is the existence of strong limits on the number and strength of bonds an individual can have with other humans.

Dunbar’s Number

Robin Dunbar is an anthropologist who, in the 1980s, posited that a human can have up to 150 meaningful relationships, based off his investigations into primate social brain structures [3]. When others attempted to verify this prediction, they found that “Dunbar’s Number” kept coming up in long-lasting groups in the real world. It’s been replicated across a huge number of domains including businesses, religious organizations, military groups, and, of course, MMO guilds.

Multiple layers, not a single number

However, as researchers dug further into the data, they noticed additional stable clustering at lower numbers of connections. These smaller clusters were part of a person’s total of 150 relationships, but involved much stronger bonds.

Visualization of Dunbar’s Layers. Each block represents time to build one relationship in that layer.

Friend layers

Dunbar’s Layers, as these smaller clusters are known, are generally organized as follows:
  • 1.5 people: The intimate couple or the individual.
  • 5 people: Intimate friends or family. People you can call in a crisis.
  • 15 people: Best friends. People who you can ask for sympathy.
  • 50 people: Good friends. The majority of regular social contacts and, by extension, all of one’s emotional and economic support [4].
  • 150 people: Casual friends or acquaintances.
Note that each layer is cumulative and contains the previous layers, so your best friend layer contains your intimate friends layer as well. A common confusion is to think you have 5 intimate friends AND an additional 15 best friends, etc., but those 5 intimate friends are part of your 15 best friends budget.

These numbers are averages and, in reality, describe tight ranges. In practice, different people have different degrees of social needs and relationship-building capacity. For example, many men average 3-4 relationships that they would consider intimate friends or family, while many women average 7-9 such relationships. Some people, known as “super-connectors,” have upward of 200–250 meaningful friendships.

Non-friend layers

With larger data sets, we’ve discovered these relationships layers also extend past actual friends.
  • 500 people: Nodding acquaintances.
  • 1500 people: You recognize their face, but that’s it. 2000 faces seems to be the absolute maximum that a human can recognize and when you learn a new face, you drop one of the other faces you’ve memorized.

Implications of Dunbar’s Layers

On first glance, Dunbar’s Layers are a mere curiosity. However, they fundamentally shape how people socialize. The following are aspects of Dunbar’s Layers worth knowing about before you attempt to use them in a design.

Dunbar’s Layers are egocentric networks

Visualizing the innermost Dunbar’s Layers as an egocentric network. Note all connections are from the perspective of a single individual.

An ideal way to visualize Dunbar’s Layers is as a network of connections, not as separate layers, per se. In research, this is known as an “egocentric network.”
  • Put a given individual at the center of a nodal network.
  • Then map out bonds going directly to that individual. You’ll end up with an average of 150 meaningful relationships connected to the individual.
  • Some bonds between the individual and their friends will be stronger than others. These bonds map onto Dunbar’s Layers. For example, a person will have an average of five strong bonds.
There are several different ways egocentric networks can be used in analysis of individual relationships:

  • Dyads: The relationship between any two individuals involves two connections, not one. Each person has their own perception of the connection’s strength. It is possible—and, in fact, common [5]—for these perceptions to be unequal.
  • Triads: Friendship networks can be analyzed by looking for triads—groupings of three people with at least two relationships between them. The strongest network structure is a “Triadic Closure,” wherein all three three individuals share mutual friendship bonds of equal strength.
  • Strong Ties: When a person has a direct relationship with another person, it is known as a strong bond. Strong bonds are key to meaningful relationships, support networks and overall happiness.
  • Weak Ties: When a person’s friend has a relationship with another person, but the original person does not, it is known as a weak bond. Weak ties are critical to connecting independent social groups and are particularly important for the functioning of large scale economic and informational systems. Weak ties also populate the 500 and 1500 person layers. When we start discussing social groups, weak ties become a very important concept.
  • Super-connectors: Some individuals have substantially more than the the typical number of connections. Known as “super-connectors,” they end up acting as hubs that connect disparate friend networks together.

Close friendships have a strong influence on quality of life

Overall, having a deep friend network has an immensely positive impact on your health and happiness.
  • Lack of friendship reduces lifespan [6].
  • High quality, high intensity relationships are positively correlated with increased life satisfaction [7].
  • Depression is lower overall in individuals with rich friend networks [8].
On the flip side, toxic relationships have an outsized negative impact on mental and physical health. Something to think about when we deal with trolls in our games [9].

High trust relationships take time and the right context

Building friendships takes many hours of interaction.
The time required to build a single friendship bond [10]:
  • Casual Friend: 40-60 hours
  • Good Friend : 90-110 hours
  • Best Friend: >200 hours
If you meet with someone for 1 hour each week, it will take roughly a year before you consider one another even casual friends. Friendship formation is not a cheap activity.

Maintaining relationships takes less effort. Three key variables here are kinship, gender and frequency of interaction. Kin bonds (bonds with family members) require less maintenance than non-family friendship bonds and do not seem affected by distance. Men tend to affirm bonds by participating in activities together, while women tend to talk with another. Higher strength bonds needs more frequent renewal than lower strength bonds.
  • Casual friends meet up at least once a year.
  • Good friends meetup up once every 6 months.
  • Best friends meet up once a month.
  • Intimate friends meet up at least once a week.

You can’t beat the system

One way of thinking about the constraints suggested by Dunbar’s Layers is to imagine you have a budget of cognitive resources that can be spent on relationships. The physical limits of your human brain mean that you only have enough mental budget for a total of roughly 150 relationships.

Humans have developed a few tools that have expanded our ability to organize into groups well past our primate cousins—most notably language—but also large-scale systems of government and economics. In the early 2000s, people assumed that new technologies like online social networks could help break past Dunbar’s Number; by offloading the cost of remembering our friendships to a computer, we could live richer, more social lives, with strong relationships to even more people.

We now have copious data that this is not the case. Studies suggest that there’s still a limited budget of cognitive resources at play and even in online platforms we see the exact same distribution of relationships [11].

If anything, social networks damage our relationships. By making it possible for us to cheaply form superficial relationships (and invest our limited energy in maintaining them), such systems divert cognitive resources from smaller, intimate groups out towards larger, less-intimate groups. The result is that key relationships with best friends and loved ones suffer. And, unfortunately, it is the strength of these high-trust relationships that are most predictive of mental health and overall happiness [12].

Social Groups

What is a social group?

A social group is a set of individuals labeled as being in a group. This is inherently a fuzzy concept, since the true structure thereof is an overlapping network of egocentric networks, partially-negotiated social norms, and ever-shifting relationship bonds.
There are three dominant perspectives on what makes a group.

Social Identity perspective: “I feel like I’m part of a group.” An individual can self-identify if they are part of a group. By doing so, they start practicing the social norms of the identified group. This is the perspective that gives birth to either imposter syndrome or a feeling of belonging.

Self-categorization perspective: “I feel like you are part of a group.” Someone looking at the behavior of other people can identify if others are behaving as part of a group. By doing so, they treat those people as if they operate using shared social norms. This is the perspective that gives birth to stereotypes.

Social cohesion perspective: “We act according to shared social norms.” A set of people that act in similar manner across a variety of social variables is a group. Those variables include:
  • Shared goals. Are we working towards the same purpose?
  • Roles. Who does what?
  • Status relationships. Who has power?
  • Norms. How do we work together?
  • Sanctions. What happens when norms are violated?
Additional factors that can be used to determine group cohesion include:
  • Group size. How many people are in the group?
  • Group trust. How strong are the bonds between individuals in the group?
  • Group stability. Does the group come together for a short period of time or is it a stable, persistent entity?
The social cohesion perspective proves the most design insight, so we’ll be referencing it for the rest of this discussion.

Group size

Common groups sizes roughly align with Dunbar’s Layers. However, these are not identical concepts. Social groups can contain friends of varying trust levels. You could have a small group composed entirely of strangers. whereas a 5-person intimate friends layer is, by definition, an individual’s closest set of friends.

Small friend groups

These are some of the most common task-oriented groups to form. Non-kin, task-focused groups of these sizes often dissipate when the task is complete. Small groups are, however, able to attain the highest strength of social bonds, usually focused on key family relationships.
  • Pair. 2 people
  • Small Group. 5 ± 2 people
  • Medium group. 15 ± 6 people

Large social groups

These are the largest-possible friend groups. Example groups at these sizes include a guild, shard, or map in an MMO, a mid-sized company, or a social organization in a university.
  • Band. 50 ± 18 people
  • Clans. 150 ± 50 people

Huge impersonal groups

These larger groups are composed of smaller friend-based sub-groups. However, due to their size being larger than Dunbar’s Number, it is impossible for them to engage in very high-trust activities without additional systems like hierarchy, reliance on weak ties, or codified rules.
  • Mega-bands. 500 ± 150 people
  • Tribes. 1500 ± 500 people

Group trust

Group trust, much like friendship, forms according to a process that imposes constraints on any social design. When we matchmake a set of random players together, we first get a low-intimacy, low-trust group of strangers. We then need to take that group through a period of social norm formation and relationship building. This process creates a rich, highly predictive social contract between individuals, which enables people to depend on one another in dynamic group activities.

The process driving group trust

Tuckman’s classic stages of group formation are:
  • Forming: The group is brought together.
  • Storming: The group attempts to make use of disparate norms for interacting with one another. This dissonance causes conflict. This process is very similar to the reciprocation loops that occur in friendship formation
  • Norming: The group negotiates common norms that this group will operate by
  • Performing: The group is able to perform higher-dependency tasks by leveraging their newly developers rules for interacting.
This relates to Dunbar’s Layers in a few key ways:
  • Existing strong bonds can facilitate group norming. If there are existing friends, they’ve already negotiated a set of common norms between them. This is a foundation to build upon when deciding the group’s shared goal and social contract.
  • Small groups need to build fewer bonds in order to perform at high levels. You can think of the norming process as one where people negotiate some minimum level of triadic bonds between all members of the group. With smaller groups, there are fewer connections, so the process goes more quickly.
  • Larger groups naturally have fewer intimate bonds. When dealing with people in the outer layers of our network, we rely more strongly on official rules, rigid social norms, and other forms of bureaucracy. People stop trusting the individual and instead lean upon a system of governance. This is less efficient, in general, due to the cost of maintaining the system, but lets more people participate.

Tips for building group trust

  • Mentoring. People often obtain high levels of competence through interaction with a coach or mentor. Finding ways to incentivize groups to adopt lower-skill members in order to train them up will benefit both group cohesion and general communal friendliness.
  • Slower integration. If facilities are not provided for subdividing groups at this layer in to smaller groupings, then every new member must be inducted by introducing them into a central communication channel. This greatly reduces the chances for the new member’s retention in the group, as they must form relationships with everyone at once, rather than being adopted by a segment of the organization and then extending their relationship network outward from that solid foundation. The best groups at this size and above have clear 15-ish person clusters, which are an ideal size for integrating a new member.

Group stability

Groups vary substantially in how long they last. There are two distinct types of groups worth looking for when designing your group systems:
  • Primary groups. Long-lasting groups of family and friends. They tend to have strong bonds and a shared sense of purpose. People usually only belong to a few primary groups corresponding with their inner Dunbar’s Layers.
  • Secondary groups. Temporary, task-focused groups. These can be large or small. People often belong to many secondary groups corresponding to their outer Dunbar’s layers. It is important to allow people to join (and leave) multiple secondary groups, as they need.

Large group stability

Even through group size and Dunbar’s Layers are very different concepts, they do seem to be related. Small groups are stable at around 5 people, primarily due to their heavily reliance on long-lasting family relationships. Large group sizes tend to stabilize around the 50, 150, 500, and 1500 values found in Dunbar’s Layers.

This works in two directions:
  • Growth: Groups below 150 tend to grow to that size.
  • Fission: Groups above 150 tend to fragment into sub-groups of 150 or less.

Stable friend groups

Groups at 50 and 150 find long term stability, often measured in years, by benefiting from peer pressure (norm reward and censure), without the need for complex rules and hierarchy. The stronger the sense of shared purpose, the more robust the group. There’s more research to be done here, but this seems to be the maximum group size where, due to the limits of Dunbar’s Layers, you can rely on unaugmented human nature to self-organize into stable groups.

Stable non-friend groups

Stable groups at 500 and 1500 are far rarer because they require the addition of some from of hierarchy in order to be sustainable. Usually this involves appointing a small group of 4-5 decision makers who represent other 50 to 150 member sub-groups. These decision makers represent ‘weak ties’ between groups.

Weak ties are key to the stability of 500 and 1500 player groups. They let a group of 50-150 reach out to other groups and quickly gain access to resources, opportunities, and information. Studies show having a diverse set of weak ties -- particularly in a large community of uncaring strangers -- increases life satisfaction.

Weak ties are not universally good for game developers.
  • Scope creep. The economic and political systems necessary to make very large groups function are often some of the most complex features in a game. To support weak ties in your game is to accept a certain level of scope creep.
  • Over emphasis on weak ties can hurt strong ties. Weak ties are also not a replacement for strong ties. Social groups involving mostly weak ties are poor at providing emotional support as well as transferring and enforcing group norms. Many critiques of strongly capitalist, technocratic or libertarian dystopias center on how a overreliance on weak ties (via large-scale trade, algorithmic replacement of reciprocation loops, and other scaleable-yet-dehumanized systems) leads to an accidental erosion of strong ties.
If anything, modern MMOs suffer from too many weak ties and not enough emphasis on building and supporting strong ties. Perhaps because MUDs and early online games were historically rich with strong bonds, MMO designers simply assumed they’d get those for free. They didn’t realize their desire to build a big game—which historically has been conflated with popularity—was antithetical to the magical social connections that made early online games attractive in the first place.

Shared goals for different group sizes

Shared goals are the single strongest predictor of group cohesion. Groups with more group pride and stronger task commitment have strong shared goals. They are most likely to perform well at high-trust tasks, and have high retention, longevity, and increased sense of member well-being.

Group pride and identity

Members with strong group pride feel strong allegiance to the group, are happy with what the group accomplishes, and promote the group identity to others. Group pride is expressed in the same fashion across different group sizes, but identity becomes more formalized as group size increases.
  • Weak identity. Small friend groups may not have an official identity, and many of their positive feelings come from mutual support.
  • Official identity. Large social groups have official identities and a strong sense of membership. When people are part of a high-performance group, they feel like they are part of something bigger than themselves, which can lead to a sense of awe.
  • Stereotype-based identities. At the huge impersonal scale, we see strong tribal identities and stereotypes. People build simple cartoon models of how other people should respond to interactions. Splitting people into in-group members and out-group members occurs relatively quickly, using only superficial information.

Task commitment

Task commitment is about shared activities that contribute to a common goal. Group pride answers, “Who are we and do I belong?” Task commitment, by contrast, answers, “What are we accomplishing by working together?”
  • Tactical tasks. Small secondary groups understand their purpose in terms of short term tactical tasks. This could be completing a small project or finishing an ad-hoc raid together. Small primary groups are usually focused on supporting one another.
  • Trying to sustain the group. Large social groups are focused on bigger topics like long-term survival or sustaining a community that upholds shared beliefs. Group vs group superiority is an interesting task at this scale, especially for groups composed largely of young men.
  • Part of an ecosystem. Huge impersonal groups are brought together by convenience. They share a common set of codified practices involving trade, language, and practices that help their smaller friend groups accomplish desired goals. The task commitment present at this level usually involves maintenance of support systems such as political or economic structures.

Tips for increasing shared goals

  • Share goals, not just shared rewards. Many game designers assume that if there is a shared reward, people will naturally align their activities. This might work if humans were hyper-rational, profit-maximizing automatons, but they are not. Instead, players benefit from clearly-stated goals and examples of how they might work together.
  • Public and private spaces. Large social groups are composed of sub-groups that require private space to reinforce vision and social norms as well as create opportunities for group bonding. They also need public space to display and reinforce the group’s overall identity.
  • Group vs. group content. Conflict with other groups is a common method of providing a shared purpose. Meaningful rivalries can play out over the course of months or years. Games with PvP content can create very rich social histories if they can operate at this scale.
  • Positive goals involving growth and support. Though it is easy to rely on competition in order to give your group a purpose, history is rich with high-longevity groups, usually in the form of religious communities, that exist to preserve a positive way of life. Consider how your game can be a positive refuge from the broader world. Many players will find this to be a worthy goal to dedicated their time toward.

Roles for different group sizes

Every group needs to agree on roles within society. These are composed of appropriate division of labor and division of resources.

Division of labor

Specialization increases with group size.
  • Overlapping roles. In small friend groups, there’s substantial overlap in roles, with a single individual performing many different activities on an as-needed basis. Cross-training and a lack of specialization is quite common. On high-trust tasks, there’s heavy interdependency and the loss of any individual is sorely felt by everyone.
  • Specialization. In large social groups, we start to see specialization where individuals take on specific roles. Secondary groups focused on specialized tasks are common and people belong to multiple of them. An individual may train in several roles and perform one role for each secondary group.
  • Jobs become identities. Huge impersonal groups see the emergence of jobs and classes. A person has one dominant job they do in a hyper-specialized economy, which becomes their formal identity within a broader, rule-based society. They are a crafter, or a teacher, or a doctor, and nothing else.

Division of resources

Economic complexity increases with group size.
  • Communal sharing. With small friend groups, resources are often communal in nature with substantial gifting and untracked sharing. Social currency and interpersonal trust are more important to transactions than currency.
  • Value-based barter. In large social groups more formalized 1-to-1 trade in the form of barter appears. There may be a local currency and individuals keep close track that each trade is of equitable value.
  • Complex economic networks. In huge impersonal groups, both labor and resources are traded within an economic network with markets and auctions. Trade is strongly depersonalized, with every interaction based off a standardized currency. This network is heavily dependent on weak ties and super-connectors—people who can maintain more than 150 meaningful connections—play an outsized role in keeping various sub-groups together.

Status relationships for different group sizes

Status and hierarchy start out relatively undefined in smaller groups and grow in complexity with group size.


Leaders become more important and less personal in larger groups.
  • Context-specific leader. Small friend groups often end up electing a de facto leader, consciously or subconsciously, who is best-suited for the task at hand. Groups this size should be encouraged to designate a leader/organizer who can help keep the members focused on their shared purpose.
  • Cult of personality. Large social groups require leaders. Synchronization of activity becomes immensely difficult without a central authority wrangling the various sub-groups to move in an aligned direction. At this size, leadership is largely a “cult of personality,” driven by personal relationships instead of institutional power.
  • Symbolic leaders. Huge impersonal groups use ceremonial leadership, where the leader is a concrete, personified symbol of shared purpose, allegiance, and/or cultural values. There are a variety of related techniques including the use of celebrity, figurehead leaders, religious characters, or heroic individuals. These establish a type of group known as a reference group, which individuals look to when determining which social norms to emulate.


Hierarchy becomes increasingly necessary as group size increases.
  • Fluid. Small friend group organization is fluid and often depends on the best person for the task at hand stepping up.
  • Activity related sub-groups. Large social groups show visible hierarchy composed of a few primary groups and a number of task-focused secondary groups. We begin to see multiple 5 and 15 person groups operating inside groups of this larger layer.
  • Complex hierarchies: Huge impersonal groups have complex official hierarchies. Groups need official political and economic relationships in order to function.

Tips for supporting status

  • Tools for status signaling. The ability to signal hierarchy and status help larger organizations function. Titles, karma points, and visual flare are all systems that allow status to be earned and displayed.
  • Official reputation tracking. For huge impersonal groups, we see the emergence of strong anonymity, reputation starts to be more important than actual skill competence and parity. At the 500 person layer, freeloaders and bad actors can more easily slip through the cracks, so official means of keeping tabs on someone’s reputation benefits group cohesion.

Social norm formation at different group sizes

Norm formation in social groups involves how a group determines the rules they operate by and how they communicate those rules.

Rule formation

Rule formation becomes increasingly formalized as group size increases.
  • Personally negotiated norms. Small friend groups negotiate rules on a one-to-one basis, usually through small group discussions. Often behavior is determined on a case-by-case basis depending on the person and the context.
  • Key decision makers. Large social groups follow the behavior of high-status individuals or leaders. One or more smaller, high-status groups make decision through consensus-building and then then share those decisions with lower-status individuals. In more equitable groups, simple voting systems appear.
  • Public rules. Huge impersonal groups use official legislative systems for setting or revising laws. They usually have formalized community feedback mechanisms. At this stage we see strong rule of law. In more organized groups, explicit rules become prevalent. By requiring that people work in a very specific, codified fashion, you remove uncertainty and increase the group’s ability to function. You’ve replaced the slow process of negotiating social norms, through in-person reciprocation loops, with rules that simply tell you how you should act. However, this comes with substantial downsides. These rules are inherently less flexible. They need to be written up, conveyed, and enforced. If the situation for such a group changes slightly, the existing rules may actually reduce efficiency. And there’s no real trust—all parties execute on a pattern and hope it works.


Communication shifts from reciprocation loops to broadcast as group size increases.
  • Personal conversation. Small friend group members will communicate frequently and in depth with all other members of the group. This communication is likely to be equally spread between all members and structured as peer communication.
  • Tiered communication channels. Large social groups have multiple tiered communication channels. There generally needs to be an open, shared channel; a one-way broadcasting channel from leadership; and a number of sub-group channels for specific primary and secondary groups.
  • Broadcast communication. In huge impersonal groups, personal communication simply cannot reach all the people in the many sub-groups, so these groups must use broadcast technologies to send one message to many people cheaply. This, in turn, enables propaganda, where various parties use broadcast media to push unquestioned messages that promote new truths. There’s no consent loop for someone to provide a contradictory response. This is useful for spreading new social norms about how one should behave or for emphasizing group bonds, but cartoon symbols of complex systems end up being easier to spread than deep understanding.

Conflicts and sanctions at different group sizes

What happens when norms are violated?

Small friend group

  • Personal disagreements. Small groups are constantly negotiating norms. Norm violations are typically confronted in small group conversation, one-on-one or with the whole group, and are essentially arguments.
  • Withdrawal from the group. In extreme cases, members of small groups will stop talking to someone with whom they have a personal disagreement, or the group will distance themselves from an individual by lowering the frequency of interaction with them.

Large social group

  • Cliques and bullies. Groups this size can form into abusive groups of bullies. Designing for groups this size means added community management. Groups of this size rely on vision-based leadership, which can allow hate groups and other fear-based organizations to fester.

Huge impersonal group

  • Demonizing outgroups. It is common for very large groups to explicitly label those who are enemies of the tribe. This is less about attacking the outgroup and more about focusing the larger group on a larger shared goal. The downside to this is it usually relies on fear, which short-circuits more thoughtful and constructive group coordination patterns.
  • Law enforcement. Tracking down those who break the laws and determining the best way to change their behavior is a feature of very large groups.
  • Economic scams. Groups emerge that profit from preying on people who want to get an economic edge. Various black market scams start to be common, like account and credit card theft. Outside groups target the community.
  • Organized griefing. Though individual griefers exist in smaller groups, within a larger population, a griefing tribe can satisfy all of an individual's social needs. Griefing becomes the social norm for such people and there’s no leverage at any point in the network to deprogram a griefer. This can lead to all-out wars, where one group attempts to destroy, alienate, or otherwise expel a rival group.
  • Account manipulation. With a large number of strangers, it’s hard to track who is coming or going. In online games, people create extra accounts and use them for botting, muling, multi-boxing, and other techniques that are otherwise easily trackable in more intimate settings.
  • Internal corruption. As with nations, if a game becomes big enough, it is easy for moderators and community management to surreptitiously misuse their powers.

Game Design Insights

Considering the constraints imposed by friendships, Dunbar’s Layers, and social groups, it is worth exploring game design that is centered around natural human social scales. Human-scale design is social design that targets the 5, 15, 50 and 150 person egocentric networks and associated groups. It explicitly avoids player systems involving 500 or more players.

If you can build a human-scale game that enables a player to spend quality time with good friends, you’ll likely improve the quality of their life. While if you break these hard limits, you actively damage your game’s social systems. These social psychology models should do more than just inform our evaluation of game systems—they should be actively shaping the way we approach design.

Such an approach focuses on smaller, more intimate social design as the core of a game. It is less concerned with big numbers and infinitely scalable systems, and more interested in fostering trust and connection between players. This perspective led us to some fundamental insights concerning how we approach online game design.

Don’t build a big world first

A common pattern when designing an MMO is:
  1. First, imagine a big world
  2. Then, figure out what to fill it with
  3. Finally, create all the systems necessary to support all the stuff you’ve dreamed up
As a result, the final systems are often surprisingly complex. You’ve jumped directly into designing systems that need to handle the many issues associated with 500+ groups (i.e., your player population). Immediately, you are faced with the key problem that your world is just a large, empty area where a player sporadically meets strangers they don’t trust. As conflict inevitably arises from these low-trust interactions, the dev team toils to add a vast amount of bureaucracy to manage the poor player experience. It can feel like patching unending leaks in a poorly-placed dam.

In the best cases, like EVE Online, players create their own systems of crude governance to shore up the faulty social design. But for the majority of games, we see outcomes like The Sims Online, where mob-style groups grief new players and chase them from the game.

From a social design perspective, this process sets the team up with the hardest possible design challenges, essentially creating a lot of extra problems that then need to be solved. Focusing on designing for human-scale suggests a different approach:
  1. Define social activities. First, imagine activities/content/context for players to enjoy together. For example, you might prototype cooperative raid mechanics for a PvE MMO.
  2. Map out group sizes and trust level. Then, figure out what group sizes and levels of friendship best fit those activities. High-trust activities should be reserved for small groups of close friends in the 5, 15 and 50 layers. Low-trust activities can work for groups up to 150 in size, but not beyond. In fact, explicitly remove activities that involve more than 150 people. For our MMO example, you take your raid prototype and map out variations of the raid that are suited for high-trust small groups, low-trust small groups, and low-trust large groups.
  3. Build appropriate social support systems. Build systems that support the right activity for the right group size. With the MMO, you realize that your high-trust small group encounter needs high-bandwidth communication channels to execute, so you add voice chat or rich emotes—two possible communication channels that support and enable group performance.
  4. Scale the activity based off quality and quantity of friends available. Finally, organize the activities/content so that player groups can organically scale up and down. In the MMO example, a single player might be present and you’ll want to serve them up low-dependency, small-group content. But if a stranger appears, consider how the game might switch to a low-trust activity with parallel play? If several friends appear, how would the activity allow them to opt-in to a higher-trust (and higher-reward!) challenge?
This approach has the advantage of more closely mapping to how humans have grouped historically: in nested layers of families, tribes, villages, etc. Sticking closer to the natural shape of social grouping will make your group activities feel more familiar and facilitate social bonding. It will also allow you to apply lessons and best practices from psychology and anthropology more directly.

Social design drives retention and engagement

When game designers think of retention, we often first consider User Experience (UX). Using the logic of UX, if a developer builds a complicated core interaction that is difficult for a player to understand, most players will churn out early on. Such games should have poor early retention and struggle with new player acquisition.

However, the game industry has many counterexamples. Dwarf Fortress, Go Pets, and Dofus are three games renowned for their poor user experiences. They have weak tutorials, byzantine gameplay loops, and a general lack of traditional first-time user experience polish. By all traditional UX values, they should be failures, yet they are not.

While these games have poor UX, they also have strong social design. For example, Dofus is a game that is specifically popular in France. Its developers tried to expand its reach to other countries with limited success, for many of the aforementioned reasons.

What made France special for Dofus?
  1. Cultural event. When Dofus first launched, French-language MMOs were rare and early adopters were blown away by the novel experience.
  2. Basic virality failed. Players actively proselytized the game to friends, but their friends weren’t able to play as the game was too difficult to learn.
  3. High-cost transmission to close friends. So players went over to their friends’ houses, helped them install the game, and spent hours teaching them, in person, the nuances of how to play.
This was not intentional, but the result was that Dofus ended up being played predominantly by friends, many of whom were already part of each others’ 50, 15, and 5 person layers. This allowed players to build groups stocked up with high-trust compatriots and overcome the high-trust activities in the game. Succeeding at those challenging activities in groups of trusted friends gave the game incredibly high engagement.

A virtuous cycle occurs where strongly-bonded friends make a game their homebase—a safe, intimate space for acting out their friendship. In turn, those players recruit more of their friend networks into the game.

We’ve observed a similar process in other poor-UX, high-retention game examples. To be clear—poor UX is not the root driver for these games’ avid, high-trust communities. Instead, it is one of many pragmatic reasons for players to bring the inner circles of their friend networks into a game.

The reverse of the same basic process that drove the success of Dofus highlights problems with early Facebook-style virality. Such “social network games” would obsessively incentivize players to send out invites to as many people as possible. Two results occurred:
  • Mismatched reciprocation loop costs. Incentivized by these games, players made a low-cost overture to a friend or associate (an invitation) that required a high-cost response (registering for, and playing, the game). This is a huge no-no when acting out reciprocation loops; it actively damages a relationship by suggesting you are ready to extract value from your friend instead of building toward future shared need. That is to say, it annoys your friends and makes them question the value your relationship.
  • Dilution of community trust. Second, it brings low-trust people into the game. Because Facebook didn’t care about Dunbar’s Layers, especially in the early days of the social gaming boom, many users had social graphs with hundreds of “friends,” many of whom were no better than strangers. The low-cost overture to join was little better than a random spam ad and brought many of those random players into the game, diluting the level of trust for the community already inside the game. In one fell swoop, this greedy practice hurt retention, engagement, and future growth.
All of these examples highlight the basic truth that social design is deeply powerful, but is often not a first-order consideration for designers.

Use proper terminology

A very common confusion that came up many times during our discussions was the difference between friends, Dunbar’s Layers, group size, and concurrency (the number of players simultaneously logged in). These are all four distinctly different concepts, yet it is common for social designers to use them interchangeably.

Much of this is the fault of our existing terminology. When we talk about multiplayer games, a common shorthand is to say, “It’s a 16-player game.” We all know that this means there are 16 concurrent players in a match or room, but we often erroneously assume that this also means they are all friends and/or that they are all part of the same social group.

Both of these errors are a naive misunderstanding.
  • Concurrent players can be spread across multiple types of social groups. Some of them might be members of groups that are antagonistic to other sub-groups in the game. Some are members of multiple groups. Some form small sub-groups while others form large sub-groups.
  • They can have a mix of friendship bonds. Some of them may be friends. Most are likely total strangers.
In general, having 16 people online together says almost nothing about whether or not they are in a group, or what the strength of their relationships might be. It is tempting to fall back on old, inexact language, but your game will suffer. Instead, teach your design teams about friendship formation, constraints on types of friendship, trade-offs involved at different groups sizes, and the logistics of social play.

Use Dunbar’s Layers to determine the level of collaboration your audience will support

The structure of Dunbar’s Layers gives us insight into how many friends of a given trust level you can expect a player to have online at any particular time. There are logistical implications for matchmaking, events, and more.

At the most basic level, the logistics of Dunbar’s Layers help you predict the outcome of the following example:
  • You design a high-trust activity that requires 100 people.
  • But we know from Dunbar’s Layers that any human being will only have a maximum of 15 people in their life that have this particular level of trust.
  • You’ve created a logistics mismatch that will results in inevitable failure. And you didn’t even have to build the game, launch it into the market, and watch it fail. You just saved your team millions of dollars and years of their life!
However, we can gain more detailed insights. Here’s how you calculate the exact portion of a player’s friend graph you can actually address with your game. First, you’ll need a few pieces of information:
  • Share of social time
  • Concurrency ratio
  • Distribution of friends

Share of Social Time

Share of Social Time is the percentage of a player’s total time spent socializing that is spent inside your game. This corresponds roughly to the percentage of a player’s social graph that is active in the game.[13] If a player spends 50% of their social time in a game, we’d expect roughly 50% of their friend network is also in the game.

There are a couple ways of calculating this. Conservatively, we know from time-usage studies that the average American has approximately 5 hours of leisure time per day [14]. From this perspective, Share of Social Time equals Hours per Day Spent In Game / 5 hours.

However, less conservatively, we know that people tend to spend approximately 0.65 hours per day actually socializing. This is likely an underestimate since the time-usage studies don’t measure time spent socializing at work. Nor do they consider time spent in playing games [15] as socializing.

For the following calculations, we’ll use the conservative definition of Share of Social Time. For comparison, the heaviest players of Fortnite, around 8% of the player population, spend 3+ hours playing per day. That’s roughly 60% (or more) of an average American’s total leisure time.

Concurrency Ratio

Concurrency ratio is the ratio of monthly active players (MAU) to those currently online. Since synchronous activities require people to be present, it does us no good if you have friends in a game, but they aren’t actually playing.

A highly-social MMO will have a concurrency ratio of 10:1, so for every 10 MAU you’ll have 1 of those players online. An international phenomenon like Fortnite enjoys a 20:1 ratio, while many web-games are as low as 150:1 or 250:1.

Distribution of friends

Dunbar’s Layers suggests that our relationships map onto a very specific frequency distribution of friends.
Chart 1: Percentage of friend network layers present in the game

This distribution holds true only if we make several assumptions:
  • Long-term engagement. First, our game is a long-term activity which has been going on long enough that inner layers like intimate friends or best friends have grown in the game or have integrated pre-existing, external friendships. If a game is new or people have been playing for less than 200 total hours [10], you’ll see this distribution shift towards casual friends and strangers.
  • Sufficiently large cohort. The total population of monthly active players is at least 1500.
  • Support for all layers. If your game doesn’t have all appropriate social mechanisms for any given layer—such as the need at the 5 person layer for private locations/communication to facilitate safe disclosure—that layer will be less represented.


We can use Share of Social Time, Concurrency, and distribution of friends to calculate some useful information about our game.

Let’s say you have a highly engaging MMO:
  • Share of Social Time: 50%
  • Currency ratio: 10:1
How many friends will be in the player’s friend list? Given the standard distribution of friends, 50% of that player’s social network will be present in your game. With a total of 150 friends that means there will be 75 friends playing the game.

How many friends will be online right now? Of those 75 friends in the game, due to the concurrency ratio, only 10% (7.5 friends) will be on at any point in time, on average.

What type of friends will be online right now? Using the distribution of friends in various layers from the chart above and multiplying them by the total friends online, we can expect the following distribution of friends:
  • Casual friends: 5
  • Good friends: 1.8
  • Best friends: 0.5
  • Intimate friends: 0.3
This sort of calculation puts much harder constraints on the types of activities that we can build into our game. Note that this is a best-case scenario. A highly-social MMO with great concurrency, and a player with a fully-engaged friend network. In this best-case situation you are lucky to get a single good friend playing alongside you. You will however get a few casual friends.

This suggests that the core activity of even highly-social games with long-term, highly-invested players should predominantly be target low-to-moderate trust activities involving 5-7 players.

What does this distribution look like at different cohort sizes? Using the same logic, you can see what friend distributions would look like at various fixed populations of active players.

Chart 2: Max and Average number of friends an individual will have for various cohort sizes in a game with 50% share of social time and 10:1 concurrency.

Due to the logistics of concurrency ratios and Share of Social Time, we max out the number of friends online at around 1500 people in a cohort. Simply having bigger cohorts doesn’t improve friend concurrency.

How can we improve these numbers?

The previous calculations are just an average of the sort of friends you can expect online. By shiftings a few variables around, we can create much higher densities of friends.
  • Events. A timed event or a scheduled boss raid spikes the number of people online and can dramatically reduce the concurrency ratio. If you can drop the concurrency ratio to 2:1 with an event, then you have upwards of 12 friends and 4 good friends playing. This shift is one reason why events like boss raids can be high-trust events.
  • Asynchronous Activities. Activities that people can do when others are offline allow for more people to be involved. Some asynchronous activities can reduce the concurrency ratio to the equivalent of 1. These systems have the downside of dramatically slowing down reciprocation loops by reducing communication bandwidth, so building out a full friendship network may take longer for players.
  • Recruitment. Given the low engagement of the innermost friendship layers due to simple logistics, it is unwise to rely on close friends naively playing the game together. Invest in systems that actively encourage players to play with loved ones. Give them tools for scheduling these activities.

Relationship design as systems design

By translating fuzzy social psychology concepts into more mechanical concepts, we can start treating social design as a form of systems design. (Some may find the term 'social systems design' more palatable than 'social game design' after dealing with the horrors of Facebook.)

In particular, social design benefits from using the internal economy perspective, where relationships are modeled as resources and transformations on those resources.
  • Each relationship between two individuals is a pool. A pool is a container that accumulates resource tokens.
  • Successfully completed reciprocation loops is a source that produces a resource called social capital that accumulates in each relationship pool.
  • Rejected or unequal reciprocation loops are a sink that depletes social capital. As does distance and lack of contact over time.
Dunbar’s Layers act as a cap on the maximum number of each level of relationship you might have. When a relationship pool fills up in one of the outer layers, it may transform into a new pool in one of the inner layers. However if the inner layers are full, one must give. If any of the layers are empty, the player seeks actions that fill them.

This paints the process as rather cold and transactional. In practice, this type of design drives intense emotions. Losses of social capital yield strong negative emotions, while gains generate positive emotions. Rate of lose or gain will dramatically intensify the emotional response. If your goal is to make players laugh, cry, or otherwise experience the peak of what it means to be human, build strong social systems.

Minimize designs that require huge impersonal groups

When we develop a game that involves group sizes of 500 and 1500 people, we’ve created populations beyond the human brain’s ability to understand other people through personal relationships. Our players know nothing about most other individuals, as they are incapable of building a large-enough social network to understand the whole. Instead, they must rely heavily on rules and heuristics to govern their interactions, and we, as game designers, are on on the hook to provide those structures.

By simply upping the size of our community, we’ve introduced an immense design challenge. We now need to build systems to manage crime, corruption, economic complexity, classism, racism, and more. Suddenly, our games exhibit most of the ills of modern society and the burden is fully upon us to solve them. If we don’t conscientiously address these issues, our community collapses into a hellish online dystopia.

If you care about maximizing social impact while minimizing scope:
  • Consider building communities of 50–150 players. This will maximally leverage strong bonds for retention and engagement.
  • Use instancing to ensure that your game can support a massive population even though each community is self-contained. Games like Minecraft; Don’t Starve Together; old, instanced MUDs; and numerous other small community games suggest this strategy can be both financially successful and fulfill social design goals.
  • If you want to create larger communities, try limiting yourself to cohorts of 500–1500. There are no other systems larger than these values that are meaningful on a relationship level, and by creating larger populations, you dilute and harm existing social bonds.
  • When creating groups of 500–1500, leverage your instanced groups of 50 and 150. Create a few low-scope systems that allow weak ties between strongly-bonded friend groups. Trade networks and information exchange will be among the highest-value systems to invest in.

Opportunity: Serving Player Motivations

Games that thrive are almost always ones that satisfy a strong audience motivation. This is no different for social games and social features. Dunbar’s Layers, in particular, give us a structure for understanding the player’s social motivations.

The Belongingness motivation

“The belongingness hypothesis proposes two main features. First, people need constant, positive, personal interactions with other people. Second, people need to know that their bond is stable, there is mutual concern, and that this attachment will continue.”

You can think of the various relationship layers as a slots in a list. Everyone has space for about 5 intimate friends, 10 best friends, 35 goods friends and 100 casual friends. If those slots are filled with healthy, mutually-beneficial relationships, a person is reasonably happy.

However if any of those slots are empty, people have a strong desire to fill them in. When they don’t have those slots filled they tend to be unhappy, and, in response, will seek the company of others using several key strategies:
  • Deepen bonds with existing friends. This is done in order to fill inner layers of the friendship network.
  • Meet new people. This is done in order to fill outer layers.
  • Become a member of a group. Often belongingness will be combined with a desire for affiliation. By becoming part of a social group, it becomes substantially easier to both meet new people and quickly deepen friendships. Think of group membership as a bonding multiplier. It is easy to get caught up in group affiliation as an end, by itself, but remember that, ultimately, people join groups not for the sake of the group, but to fill gaps in their primary friend network.

The desire to form relationships waxes and wanes

Life events are predictive of gaps in a person’s friendship network. As new people show up in a person’s life, there’s less time for activities that require making new friends.
  • Entering a new intimate relationship or marriage. This fills an inner-layer slot. There’s also the inevitable shifting and merging of your two friend groups.
  • Having a child. This also fills an inner-layer slot. All that time spent in parenting groups often shifts friendships from your single friends over to other parents with kids just like you.
  • Getting a new job. This can fill any number of slots in several layers as you form new work relationships.

What loneliness looks like in a thinned-out network

There are also numerous events that thin out a person’s network.
  • Becoming unemployed. You lose work relationships.
  • Retiring. This is similar to becoming unemployed, but often you lose professional associations as well.
  • Breaking-up or divorce. One of the more intense losses of an inner, highly-intimate bond. As well as a weakening of all the shared relationships (closed triadic relationships in your networks).
  • Moving. Shifting many high-intimacy friends into outer layers. Can break existing friendships and free up slots. Research suggests it generally doesn’t destroy intimate family bonds.
  • Kids moving out. When kids go off to college, most parents end up losing key members of their inner circle.
  • Becoming elderly. There’s a slow erosion of existing friend networks as people move or die. Elderly are also are less mobile and thus struggle to meet new people.
In particular, there seem to be three major periods in which loneliness spikes: Late 20s, mid 50s and late 80s. During these times one study reported as many as 75% of people report being lonely. These values hold across genders. Providing these individuals with tools for building healthy relationships would be immensely beneficial to society.

Two social game design opportunities

All of this suggests opportunities for social game design to improve the lives of our players.
  • Games for friends. High-trust games should target those with free time and strong, existing friend networks. The design focus is on bringing those friends into the game.
  • Games that help make friends: Games that deliberately try to convert strangers into better friends should target groups that have gaps in their social network. For example, one demographic might be lonely 50-65 year old men who are seeing an erosion of their social network due to unemployment, kids moving out, and fewer opportunities to find new friends. Make a game that is the modern version of a Masonic Lodge.
Both opportunities could be served by the same game, but be sure to sort incoming players based on their needs and direct them into activities that satisfy those identified needs.


The big idea

Key discoveries in social psychology place hard limits on the types of social games we can build.
  • Friendship research shows meaningful in-game relationships require conditions such as proximity, similarity, reciprocity, and disclosure
  • Dunbar’s Layers research shows that players have hard limits on the number of meaningful relationships in their life. These friendship are organized into layers of increasing size and decreasing intimacy.
  • Social group research shows the need for increasingly complex support structure as group size grows
These are the physics that social designers must understand and build into their designs.

The trap

Many past designs ignored Dunbar’s Layers and naively assumed “more is better.” They ignore friendship formation and assume “it just happens.” They ignore social groups and arbitrarily mash players together.

In reality, these assumptions are actively harmful and cause the following:
  • Fewer in-game friendships. A flood of strangers swamp the reciprocation and proximity mechanisms that generate friends. Poor identity, persistence, reciprocity, and consent systems mean these strangers never convert into friends, so there are fewer meaningful relationships in the game.
  • Increased toxicity. Large groups of strangers naturally breed toxic sub-groups. Players engage in violent rejection of out-groups in order to protect their experience and intergroup conflict becomes the cultural norm. Such communities are hard to reform and poison long-term retention.
  • Scope creep. The additional systems necessary to manage large groups of strangers substantially increase the scope of your game.

What players need

If players have not filled all the slots in their primary friend network, they suffer. And, in response, they are intrinsically motivated to deepen their existing relationships or build relationships with new people. Striving for belongingness is one of the strongest human motivations. They will naturally seek out activities that help them make friends and belong to something bigger than themselves.

The opportunity

If your games help build relationships for the player in any of their inner layers, you’ll accomplish a couple key benefits:
  • Increase retention and engagement. Your game becomes the place where people attain their desires. Since you provide immense value, they make the game a key part of their lives.
  • Improve the lives of your players. They’ll experience less depression, better health, and have more robustness in the face of negative life events.

Best practices

If we take all the insights gleaned from research into group psychology, examples from online game design, examination of Dunbar’s Layers and social motivation—all of it into consideration, we can arrive at several, strong best practices:
  • Build games for smaller cohorts. The base activities should target small, collaborative groups. Large groups of close friends are rare or, in many cases, mathematically impossible.
  • Cluster players into persistent, high-density cohorts. So they have repeat interactions with the same players. The more reciprocation loops that are completed, the stronger the friendships. Big, empty spaces are not a positive feature.
  • Encourage high-concurrency events or asynchronous activities. Logistics favor players being around to interact with their friends. Having friends playing the same game doesn’t matter if you never see them.
  • Aim for long-term engagement. Build a game where players are engaged for hundreds of hours, so they have enough time to build deeper friendships. It takes at least 50 hours of interactions to form a basic friendship.
  • Attract existing friends, if possible. Existing friends from the strongest foundation for your game community, especially when first launching your game. Put people into safe, guild-like structures and encourage them to bring in their friends.
  • Design for climbing the trust spectrum. When introducing strangers into your game, build low-trust activities that scale into high-trust activities. Start with parallel or single-player gameplay and allow players to opt-in to higher-dependency activities. If players start forming strong friendships in game, support them. Bring those relationships into safe places with tools for enabling consent, support, and disclosure.

Final thoughts

As ethical game designers, we should strive towards some higher purpose beyond merely extracting money, time, and energy from our players. Building friendships and providing lonely people with human connections are goals worthy of our highest-quality work.

If you are working on a multiplayer game, ask yourself how your designs help build social capital with and among your players. If you encounter people who believe that “more is better” when it comes to building social systems, we recommend you send them this report. There’s a new wave of social game design inspired by lessons from social psychology and we are immensely excited to be part of it.


[1] Active MUD communities. Examples include, as of the time of this writing (December, 2018): Achaea, Dreams of Divine Lands (1997-present); Aardwolf MUD (1996-present); GemStone IV (1988-present); Realms of Despair (1994-present); and Threshold RPG (1996-present)

[2] Dunbar’s Layers. “Generally speaking, humans each have one to two special friends, five intimate friends, 15 best friends, 50 good friends, 150 “just” friends and 500 acquaintances. Our relationships form a series of expanding circles of increasing size and decreasing intensity and quality of the relationship.”
Woodward A (2017) With a Little Help from My Friends. Scientific American. Retrieved December 27, 2018, from

[3] Dunbar’s Number. “The figure of 150 seems to represent the maximum number of individuals with whom we can have a genuinely social relationship, the kind of relationship that goes with knowing who they are and how they relate to us. Putting it another way, it’s the number of people you would not feel embarrassed about joining uninvited for a drink if you happened to bump into them in a bar.”
Dunbar R (1998) Of Brains and Groups and Evolution. In Grooming, Gossip, and the Evolution of Language (pp. 80-105). Retrieved December 26, 2018, from

[4] The 50 Person Layer. “Thus, 50 individuals may represent a natural social grouping (in the world of personal social networks, it is the set of individuals that provides the bulk of one’s regular social contacts and all of one’s emotional and economic support…)”
Kordsmeyer T, Carron P, Dunbar R (2017) Sizes of Permanent Campsite Communities Reflect Constraints on Natural Human Communities. Current Anthropology, 58(2), 289-294. Retrieved December 26, 2018, from

[5] Unequal dyadic bonds. “When analyzing self-reported relationship surveys from several experiments, we find that the vast majority of friendships are expected to be reciprocal, while in reality, only about half of them are indeed reciprocal.”
Almaatouq A, Radaelli L, Pentland A, Shmueli E (2016) Are You Your Friends’ Friend? Poor Perception of Friendship Ties Limits the Ability to Promote Behavioral Change. PLoS ONE 11(3): e0151588.

[6] Loneliness impacts longevity. “...individuals with adequate social relationships have a 50% greater likelihood of survival compared to those with poor or insufficient social relationships. The magnitude of this effect is comparable with quitting smoking and it exceeds many well-known risk factors for mortality (e.g., obesity, physical inactivity).”
Holt-Lunstad J, Smith T, Layton J (2010) Social Relationships and Mortality Risk: A Meta-analytic Review. PLoS Med 7(7): e1000316.

[7] Friendship impacts life satisfaction. “...the results indicate that both having/meeting friends and good-quality friendship relations are important to an overall life satisfaction.”
Amati V, Meggiolaro S, Rivellini G, Zaccarin S (2018) Social relations and life satisfaction: the role of friends. Genus, 74(1), 7.

[8] Friendship reduces depression. “People who have close friends and confidants, friendly neighbors and supportive co-workers are less likely to experience sadness, loneliness, low self-esteem and problems with eating and sleeping. Indeed, a common finding from research on the correlates of life satisfaction is that subjective well-being is best predicted by the breadth and depth of one’s social connections.”
Helliwell J, Putnam R (2004) The social context of well-being. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 359(1449).

[9] Toxic relationships impact health. “...individuals who experienced negative aspects of close relationships had a higher risk of incident coronary events….”
De Vogli R, Chandola T, Marmot M (2007) Negative Aspects of Close Relationships and Heart Disease. Arch Intern Med, 167(18), 1951–1957.

[10] Friendships cost time to build. For more details, see:
Hellman, R (2018) How to make friends? Study reveals time it takes. KU News Service. Retrieved December 19, 2018, from

[11] Social media doesn’t expand our friendship capacity. “The fact that social networks remain about the same size despite the communication opportunities provided by social media suggests that the constraints that limit face-to-face networks are not fully circumvented by online environments. Instead, it seems that online social networks remain subject to the same cognitive demands of maintaining relationships that limit offline friendships.”
Dunbar R (2016) Do online social media cut through the constraints that limit the size of offline social networks? Royal Society Open Science, 3(1).

[12] Intimate relationships best predict health. “...the presence of an intimate relationship (as opposed to a broader social network) [has] the greatest effect on explaining variance in depressed mood.”
Roberts S, Arrow H, Gowlett J, Lehmann J, Dunbar R (2014) Close Social Relationships: An Evolutionary Perspective. In R Dunbar, C Gamble, J Gowlett (Eds.), Lucy to Language: The Benchmark Papers (pp. 151-180). Oxford: Oxford University Press.

[13] How investment shapes social graph distribution. “the strength of a tie is a (probably linear) combination of the amount of time, the emotional intensity, the intimacy (mutual confiding) and the reciprocal services which characterize the tie”
Granovetter M (1973) The Strength of Weak Ties. American Journal of Sociology, 78(6), 1360-1380. Retrieved December 28, 2018 from

[14] Available leisure time. The average American woman spends roughly five hours per day on leisure activities (35 hours per week), while the average American man spends about 5.5 hours per day (38.5 hours per week).
Bureau of Labor Statistics, U.S. Department of Labor (2018) American Time Use Survey — 2017 Results. Press Release for the Bureau of Labor Statistics. Retrieved December 20, 2018, from

[15] Why are people socializing in games? “On the face of it, this may seem like a sad state of affairs. It could even be read as dystopian: people are escaping real life to be in virtual worlds. People often find community within gaming worlds, and may get a heightened sense of shared experience from competing against or teaming up with people across the world who share their interests. In some cases, these connections might even be more valuable than, say, gossiping with a neighbor.”
Kopf D (2018) Americans are socializing less and playing more games. Quartz. Retrieved December 28, 2018, from

Other References

Bura S (2008) Emotion Engineering in Videogames. Retrieved December 28, 2018, from

Casari M, Tagliapietra C (2018) Group size in social-ecological systems. Proceedings of the National Academy of Sciences, 115(11), 2728-2733.

Cook D, (2018) Game design patterns for building friendship. GDC 2018. Retrieved December 28, 2018, from

Cook D, Bialoskurky Y, Fulton B, Fitch M, Gonzales J (2016) Game design patterns that facilitate strangers becoming “friends”. Project Horseshoe. Retrieved December 19, 2018, from

Dormans J, Adams E (2012) Game Mechanics: Advanced Game Design (Voices That Matter). San Francisco, California: Peachpit

Dunbar R, Sosis R (2018) Optimising human community sizes. Evolution and Human Behavior, 39(1), 106-111.

Dunbar, R (1993). Coevolution of neocortical size, group size and language in humans. Behavioral and Brain Sciences, 16(4), 681-735. Retrieved December 28, 2018, from

Glaeser E, Laibson D, Sacerdote B. (2002) An Economic Approach to Social Capital. The Economic Journal 2002, 112(483), F437-F458. Retrieved December 28, 2018, from

Group Cohesiveness. In Wikipedia. Retrieved December 28, 2018, from

Hall J, Davis D (2016) Proposing the Communicate Bond Belong Theory: Evolutionary Intersections With Episodic Interpersonal Communication. Communication Theory, 27(1), 21-47. Retrieved December 28, 2018, from

Interpersonal Ties. In Wikipedia. Retrieved December 28, 2018, from

Koster R (2003) Small Worlds. Retrieved December 28, 2018, from

Koster R (2018) The Trust Spectrum. Retrieved December 28, 2018, from

Lee E, Depp C, Palmer B, Glorioso D (2018) High prevalence and adverse health effects of loneliness in community-dwelling adults across the lifespan: role of wisdom as a protective factor. Cambridge Core.

Marvin R (2018) Fortnite by the Numbers: How Many Hours Are You Playing Each Week? PC Magazine. Retrieved December 20, 2018, from

Moai (social support groups). In Wikipedia. Retrieved December 28, 2018, from

Putnam R (2000) Bowling Alone: The Collapse and Revival of American Community. New York City, New York: Touchstone Books by Simon & Schuster

Sandstrom G, Dunn E (2014) Social Interactions and Well-Being: The Surprising Power of Weak Ties. Personality and Social Psychology Bulletin, 40(7). Retrieved December 28, 2018, from

Shen C, Chen W (2015) Social capital, coplaying patterns, and health disruptions: A survey of Massively Multiplayer Online Game participants in China. Computers in Human Behavior
Volume 52, November 2015, Pages 243-249 

Social Cohesion Approach. In Wikipedia. Retrieved December 28, 2018, from

Tamarit I, Cuesta J, Dunbar R, Sánchez A (2018) Cognitive resource allocation determines the organization of personal networks. Proceedings of the National Academy of Sciences, 115(33), 8316-8321.

Depp C, Palmer B, Glorioso D, Daly R, Liu J, Tu X, Kim H, Tarr P, Yamada Y (2018) Serious loneliness spans the adult lifespan but there is a silver lining: Feeling alone linked to psychological and physical ills, but wisdom may be a protective factor [Press release]. Eureka Alert. Retrieved December 28, 2018, from

Williams, D. (2007). The impact of time online: Social capital and cyberbalkanization. CyberPsychology & Behavior, 10(3), 398–406.

Shadow Emotions and Primary Emotions
Posted by Lost Garden [HTML][XML][PERM][FULL] on 16 July 2011, 8:54 pm

Not all emotions are created equal.

Consider: It is a distinctly different thing to feel sad while reading about a dying mother than to actually feel sad because your mother is dying. The former is a shadowy reflection that we intuitively understand is not immediately threatening. The later is raw, primary and life changing.

I've yet to see existing terminology for this phenomena, so at the risk of stepping on existing toes, let's use the following labels.
  • Shadow emotions:  The emotions we feel when partaking in narratives, art and other safely evocative stimuli
  • Primary emotions: The emotions we feel when we are in a situation with real perceived consequences.
The closest I've seen to this being described elsewhere is something called the Somatic Marker Theory.  It postulates:

"When we make decisions, we must assess the incentive value of the choices available to us, using cognitive and emotional processes. When we face complex and conflicting choices, we may be unable to decide using only cognitive processes, which may become overloaded and unable to help us decide. In these cases (and others), somatic markers can help us decide. Somatic markers are associations between reinforcing stimuli that induce an associated physiological affective state."

Crucially, the theory identify two distinct classes of emotion.  The first is the 'body loop' which corresponds closely to primary emotions.  The second is the 'as-if body loop' which corresponds to shadow emotions.

No doubt this is a well studied topic, so if someone educated in the neurosciences is able to provide even more accurate labels or links to additional models I'll happily amend this essay.

The distinction between these two classes of emotion may seem academic, but I find myself fascinated by a game's ability to provoke primary emotions in a manner that is difficult if not impossible for more reflective forms of media.  As a game designer, I can and have put the player in situation where they experience real loss.   The best a movie or book can manage is evoking a shadow of loss.

    Brief thoughts on memory and emotion

    A small bit of background is necessary to describe the mechanism of shadow emotions.   It starts with the link between memory and emotion.

    Memories come loaded with judgments.  In some sense, the true function of memory has been polluted by a modern concept of coldly analytic 'data storage'.   Perhaps a better term for 'memory' is 'lesson'.  Each memory has deeply integrated emotional tags that informs us of how we might want to react if we call upon that memory in relation to our current stimuli.   When you see a dog sitting on the sidewalk, you instinctively compare it to your existing mental models and memories of past dogs.  In that basic act of cognition, you nearly instantly become awash with emotions.  Perhaps you feel a sense of comfort and fondness.  Or perhaps a wave of anxiety passes through you as you recall the sharp teeth of past encounters gone awry.  In a split second, you know exactly how you feel about that dog.

    One way of thinking of emotion as an early specialized form of cognition that serves a clear survival function. Quite often you need to make a decision, but you don't have time to think about. Quick! Act now! At this moment, you are flooded with an emotional signal. It is strong, primitive and highly effective at making you either run, attack, bond, threaten or pause.  Emotions tied to memories help us boil vast decades of experience  down into an immediate instinctive reaction.

    Hair trigger emotions exists because more complex cognition takes time and for certain classes of decision, delays yield failure and failure is costly. If you are attacked by wolf, it likely isn't prudent to debate the finer details of how you classify canids. Much later, be it seconds or hours, your conscious understanding of the situation kicks in and moderates the emotional response.  More often than not, what we think of as consciousness is little more than a post processed justification of our ongoing roller coaster of instinctive emotional reactions.

    Emotions are necessary but they are not civilized.  It is easy to imprint rapid fire lessons that trigger at the worst possible moment.  A child who learns to lash out in anger as a way of surviving neighborhood bullies might have difficulty as an adult if he reacts the same way when he perceives a more subtle theme of bullying from his boss.  What makes managing emotions so tricky is that such emotional triggering situations unfold before we are even aware they are occurring.  Emotions are by definition lessons turned into lightning, unconscious action (or inaction as the case may be).

    Narrative as a means of playing emotional scenarios

    You cannot easily or consciously stop emotions in full activation; however you can train them ahead of time.  One method (of many!) is to test and explore our emotions in the safe mediums of narrative, sound and imagery. The mechanism for triggering a safe emotional response seems to be primarily based off a mixture of empathy and the emotional aspects of memory that we've previously covered.
    • Stimuli: When we see or read a particular evocative narrative or scene.
    • Memory: We tap into our own related stored memories
    • Synthesis: We assemble disparate elements into a coherent whole
    • Empathy: We simulate what we might feel in this particular situation
    • Conscious understanding: We process the resulting safe emotions from a safe distance. 
    Now imagine that you read about the dog sitting on the sidewalk.  You can confront your anxiety with crystal clear understanding that he cannot hurt you.  You activate your empathy and simulate how you might feel if the dog were in fact in front of you.  Now you roll the emotion around and savor it, examining it from multiple angles.  You instinctively role-play the scenario.  Perhaps you become comfortable with the idea that you don't need to immediately run away from all dogs.  By storing this revised impression, you slightly moderate your future emotional reactions.

    In a biological sense, this is a surprisingly inexpensive method of practicing how to moderate our emotions.  Instead of placing yourself in potentially mortal danger, you can instead read about what it while sitting in a chair.  The training that occurs is not perfect, but I suspect that it helps.  There is a wide body of experimental research that shows how emotions are differentiated through a process of psychological response and then the application of a cognitive label.  If you can practice labeling a rush of adrenaline as bravery instead of fear, you may be able to successfully alter your emotions in real world situations.

    Though by no means proof of this theory, it is suggestive that many popular fictional and artistic works are highly focused on evoking emotion and chains of strong drama.  Situations that are risky, expensive or socially compromising regularly find their way into the evocative arts and enable us to practice those scenarios in a safe fashion.

    Shadow Emotions

    The relatively safe emotions that result from consuming and simulating evocative stimuli are what I'm calling shadow emotions.

    A shadow emotion is by no means a 'fake' emotion.  Your heart rate increases, your palms sweat.  The patterns of the past carry echos of real emotions and your body responds accordingly.  All the physiological signs of experiencing an emotion are present.  However, you know intellectually it is a carefully controlled experiment.   Despite hysterical claims to the contrary, humans appear to have a surprisingly robust understanding of simulation vs. reality.  We labels our simulations as such and can usually set them aside at our convenience.

    Shadow emotions are by no means completely safe. Anyone that goes through a therapeutic process where they directly recall past trauma can bear witness to the fact that recalling strong emotions is an intense and even frightening experience.  Distance matters when role-playing stored emotions and the more closely you simulate the original event, the stronger the response.

    All this leads to many of the common techniques found in making powerful drama or art.  This list is by no comprehensive, but it is a good sample of the practical tools available to a craftsman interested evoking shadow emotions:
    • Richly describe salient stimuli
    • Exaggerate stimuli (Peak Shift Principle)
    • Layer multiple channels of stimuli
    • Target commonly shared emotional triggers (Love, Death, Triumph, etc) 
    • Create coherent chains of context and causation to facilitate easy simulation
    • Personalize the stimuli to better match the emotional history of an individual.  
    As an artist, a story teller and a game designer, I've used all of these and they are far less mysterious than many would presume. When such techniques are well executed, you'll increase the intensity of the evoked shadow emotion.  The word 'evoke' is key since our concern is more about using a signal to trigger emotions that already exists.  As such I think of these techniques clumped primarily into methods of simplifying processing our evocative signal or methods of increasing strength of that signal.

    Shadow emotions absolutely exist in games.  In fact, the game industry spends ludicrous sums of money attempting to ensure that high end console titles are as good at evoking shadow emotions as media such as movies or books.  During the dark reign of the techno-cultists who preached the ascendancy of visual immersion, realism and games as predominantly narrative medium, a thousand chained craftsmen made heroic attempts to evoke stronger shadow emotions.  See such baroque creations as Mortal Combat, God of War or L.A. Noire.  This expensive pursuit will continue because humans crave shadow emotions as a path to more effective emotional cognition.  Game developers, as paid schmucks making disposable and consumable media, have an economic incentive to fill this need.

    The next time you safely experience the emotion of shooting a minority-skinned terrorist in the head and watching the beautifully rendered blood and brains splatter in slow motion, step back and consider the emotional role-playing that you are simulating.  It obviously isn't real, but you do feel something. Perhaps it is even therapeutic.  These are shadow emotions in action.  I remain unimpressed, but perhaps if we render those skull fragments at a higher resolution, AAA games will one day achieve something deeply meaningful.

    Primary emotions in games

    In this expensive pursuit of shadow emotions, we may have accidentally sidelined deeper exploration of a phenomena more fundamental to the emotional capabilities of games.

    I spend large portions of my day observing game players.  Some of this is observation of others, but there is also a peculiar detached observation of my own reactions to a particular game or prototype. Repeatedly, I see sparkles of emotion that seem to have different roots than shadow emotions.  A player might become frustrated that they don't understand a particular level layout.  Or they may feel anguish when their character suffers permadeath in Realm of the Mad God.  Or they may feel elation at finally getting the long tetrimino necessary to clear four rows in Tetris.

    I would make the bold and perhaps unsupportable claim that these responses are not a reference to a past emotional experience.  Instead they seem to be derived from much more primitive circuitry.   Where do emotions originally come from?  Not all are reflections of memories past.  There are means of creating emotions from scratch.

    Consider the sense of anguish that one feels when the character you've built up over many hours of dedicated play dies for all eternity.  This system, permadeath, is quite uncommon in many modern games, but thousands of players go through the process everyday in the game Realm of the Mad God.  As a designer you can think of this experience in almost purely mechanical terms.  A player invests time and energy into accumulating a resources and capabilities inside a defined value structure.  Then due mostly to a failure of skill, the player gets hit with a barrage of bullets and that investment is irretrievably lost.

    Despite the coldly mechanistic nature of the system, the player feels intense anguish.  It is a raw, primordial thing that courses through your veins and makes breathing difficult.  There is really nothing playful or distant about this emotion. The magnitude and newness of the loss directly correlates to the intensity of the experience. Most players I know have great difficulty setting aside the first major loss and pretending that it did not matter. Some will even quit the game because the emotional intensity is just too much to bear.

    What I find intriguing about this particular emotion reaction is that it pops up in other non-gaming scenarios.  Recently I forgot to save a file and in one horrible instant lost hours of labor.  The self recrimination and sense of loss is quite similar. In a more extreme example, when the stock market collapsed in the 1920's the emotional response to abrupt and permanent loss was so great that people took to jumping from buildings. The systemic creation of emotion is a powerful phenomena.

    There are variations on the theme that result in a spectrum of different yet equally reproducible emotions.  If the player is struck with lag or a control glitch or they feel that some other player helped cause their demise, the emotional reaction is almost always incandescent rage.  Small adjustments to the mechanical systems of cause and effect result in distinct emotional responses.

    Primary emotions appear to be emotions triggered by interactive situations not evocative stimuli.  They tend to involve several telling mechanical factors:
    • Territory
    • Time 
    • Resources
    • Information
    • Investment and Loss
    • Skill and Randomness 
    • Social interaction  
    As I write this list, I can't help but realize that these sound like many of the fundamental elements of games.  Yes, we can still talk about games-as-systems when we start talking about emotions.  There is no need to scurry back to the well worn tropes of evocative media.  As game developers, we really do not need the crutch of shadow emotions to create a meaningful emotional experience for our players.  Instead, we can succeed by making "games as games" not "games as some bizarrely crippled copy of another industry."

    I wish I could say more about the exact biological process behind generating primary emotions, but alas it is not my area of expertise.  Instead, the best I can do for the moment is to describe the pragmatic process that I use to create desired primary emotions in a population of players.  Compare the following process to the one I listed above for shadow emotions.  They are rather different.
    • Define: Create mechanics and models that describe a player-centric system of value.  What should the player care about and how do the systems and resources reinforce their interest?
    • Acclimate the player to value structures by having them interact with it repeatedly via various loops and processes.  Pay careful attention to skill and resource acquisition as well as the formation of social bonds since these must be grown. 
    • Trigger: Put the player directly in situations involve a practical loss or gain that triggers the generation of new primary emotions.  
    • Label: Apply labels or context to the raw emotion so that players interpret it in the desired fashion.  See the two-factor theory of emotion for examples of how contextual labels can transform a base physiological response into a myriad of subtle emotions. 
    You can certainly use evocative stimuli within such a process, but it will always be a supporting tool.  The emotions are engineered from the players interactions and experience with the system and not by bombarding someone with  images, dialog or sound. Player choice matters.  Failure matters.  Learning and skill matters.  The game matters.

    My friend Stephane Bura has done important work in mapping game systems onto emotions, but there is far more to be done. I highly recommend you read through his pioneering essay Emotion Engineering in Games.  It took several years before it started to sink in, but I'm hoping that you'll have a head start.


    I've derived immense practical value from the distinction between primary emotions and shadow emotions.  Once you've internalized the concept, you can look at a game and ask with great clarity "How is this player emotion being generated?"   Once you know the mechanism, you can then take steps to amplify or soften the observed effect. Should you increase the fidelity of visual feedback or merely change a resource variable? If you know neither the type of emotion nor mechanism driving the emotion, you are designing blindly.

    It is also important that we start talking about how games generate primary emotions. The feeling of victory in a game of Chess is real. The feeling of anger at a Counter Strike camper is real and visceral. The feeling of belonging when you are asked to join a popular guild will stay with you for the rest of your life. We are not reflecting or empathizing (though this can occur in parallel). Due to the interactive nature of the game and our ability to adopt the value structure of the game, there are consequences that are real enough for our body to  muster actual new-to-the-world emotions.  This is an amazing and fundamental property of games that is at best weakly represented in more traditional media.  Let's play to our strengths.

    Every second you spend blathering on about the damnable Hero's Journey or the role of traditional evocative narrative is a second you could instead be exploring the vast and uncharted frontier of emotional game design. We make games.  And games are great and powerful entities in their own right.  What happens if you strip out as much of your reliance on shadow emotions as possible and focus your design efforts on creating primary emotions in your players?

    In Realm of the Mad God, the player dies. And he can't come back. It is a harsh penalty with strong sense of failure. Colliding with a 8x8 pixelated bullet with no fidelity, realism or crafted narrative means something emotionally that no movie or novel will ever capture.

    take care,

    (Edited July 11, 2011 to include a reference to Somatic Marker Theory)
    (Edited September 12, 2011 to include a reference to Two-factor Theory of Emotion)


    Triple Town Beta (Now with Bears)
    Posted by Lost Garden [HTML][XML][PERM][FULL] on 3 October 2011, 11:22 am

    Exciting times.  You can now play our puzzle game Triple Town in your web browser.  We are releasing it as a beta and the game should evolve quite substantially over time. Huge kudos to Cristian Soulos for making this project blossom after a long winter. You can play it here.

    Triple Town is a special game. It has the highest user rating of any of the games I've designed (94%). It is also the only one of my designs that I go back to again and again. Why is this?

    On the surface, it is a simple match-3 variant, but after a few games you'll start noticing the strategic depth.  The pacing is...uncommon.  There's a relaxed mellow rhythm to the game where you casually make dozens of micro decisions.  Yet these decisions add up to games that can last upwards of a week for advanced players. After a while you realize you are playing the Civilization of Match-3 games and that you care deeply about what you are building.  That burst of strong emotion always surprises me.

    The big addition for this release? Bears.

    Bears, bears everywhere

    Triple Town helped solidify how I construct the world and setting in my games.  My inclination is to look for ways of supporting the emotions inherent in the game dynamics.  If you've ever played the Kindle version, the design is a rather abstract puzzle game with highly symbolic tokens and mechanical rules. It has only the briefest of settings. Yet as I played the game and watched other play, I realized that it evoked an intense spectrum of emotions.  Here were some of the ones that I noticed:
    • Pride:  When you create a great city, you want to share it.  People take screenshots.  They brag. Pride in what they've built is the primary emotion that drives players of Triple Town. 
    • Curiosity:  You want to know what the next item looks like. Some people are driven to get a castle for the first time. 
    • Hate: You learn to hate the teleporting Ninjas.  They never attack you, but they end up blocking your plans.
    • Sadness: You have slight sadness the first time you kill a bear.  Then you learn to steel yourself against the emotion. 
    • Irritation:  When fate gives you the wrong piece at the wrong time. 
    • Competition:  When you notice that your friends are doing better than you. 
    • Despair: When you feel the board closing in and realize that you can't possible catch up to your friends. 
    • Relief:  When the board is filling up and then you perform a miraculous move that empties a swath of the board and helps you start afresh. 
    Games are great at eliciting primary emotions.  They don't need the Hero's Journey, they don't need story, they don't need hyper realistic visuals with immersive first person cameras.  You can create an emotional, deeply meaningful experience simply by using the fundamentals of system design.

    (You can read a bit more on the theory of how games are unique suited to creating emotional experiences in my previous essay on Shadow Emotions and Primary Emotions.  I include a small section at the end of this essay on the OCC emotion model that fits nicely with my process. Thanks, Aki!)

    Tuning emotions

    When I revisited the Triple Town design, the emotions were already clearly evident.  However, I wanted to explore how I could more directly shape those emotions to fit my vision of the game.

    Emotions are complex to say the least so we need some sort of entry into the topic.  There's a general consensus that you can divide emotions into rough categories.  For example 'negative feelings toward others.'  Then within those rough categories, you see variations that we recognize as distinct emotions.  For example, hate and irritation are actually highly related and are typically related to a sense of loss or constraint caused by others.  As a designer, how do I push the conditions that elicit a general class of emotion so that I can dial in the emotional variant that I desire?

    There are a variety of theories.  In Triple Town, I was influenced by the two factor theory of emotion and the somatic marker theory. Like many aspects of human cognition, multiple inputs are necessary to create the final refined experience. The 'taste' of wine is synthesized out of the actual chemical taste and the perceived quality of the wine.  A five dollar wine labeled as a 100 dollar wine can be perceived to taste better than that same wine in it's original bottle.  Similarly, we posit that our brain synthesizes most common primary emotions out of the following:
    • An ambiguous physical response (your adrenaline jumping and your heart rate elevating)
    • The system-derived context of the situation you are in. 
    • Recalled cognitive labels of related past experiences.  
    Looking at Triple Town, both the physical response and the system-derived context are very much present.  I can experimentally validate that I'm getting strong emotions from the players even using a highly abstract game board.   However the cognitive labels are underdeveloped.  So this analysis led me to try a particular tactic:
    • If you can evoke a general class of emotions with game mechanics, then you can apply evocative stimuli to label and therefore tune that response to elicit a specific emotion. 

    Monsters or children?

    Consider a very basic example of labeling in Triple Town.  The raw materials I was working with was an observation that players felt immense sense of relief when they killed annoying NPCs.  I experimented with applying various labels to see how we could tune the response.
    • Pass 1: During one early prototype, the NPCs were accidentally displayed as small children.  Naturally, players felt bad when trapped them and they turned into grave stones.  Accidental deaths led to guilt and sadness while deliberate deaths evoked a dissonant feeling of cruelty. 
    • Pass 2: So next we switched them to evil looking monsters.  This was a dramatic change.  Now players felt righteous glee when they trapped and killed the monsters. 
    • Pass 3: Finally, during this latest build, I settle on bears that have slightly evil looking eyes.  Most players feel fine killing the bears, but for some there is a slight edge of ambiguity that makes them uncomfortable. 
    • Future passes: Now that I've explored the emotional space a little, I've set up the bears so that with one simple tweak of the eyes, I can make the bears incredibly cute and bring back many of the feelings of guilt and sadness. 
    Evil bear & Good bear cognitive label.  One small part of an overall emotional experience

    In essence, I was balancing and tuning the player's emotional response.  Much like Sid Meier using a binary search ("double it or or cut it by half") to narrow in on the correct setting in his game, I was trying out various extremes to narrow in on the appropriate emotion.

    Using evocative imagery is a common enough practice, but in practice the labeling of NPCs is functionally quite different than merely putting up a picture or cut scene of a dead child.  The bear is not an image for the sake of being an image.  Instead you create a distinct label that is only meaningful due to how it builds upon an emotional foundation derived from play.  Without the mechanics, you just have a picture of a bear.  With the mechanics setting the context and providing the raw emotional reactions, you craft a carefully refined emotional moment.

    Avoiding dissonance

    With the children images in the first pass, I saw an example of dissonance.  It is easy to add a poorly fitted label that confuses the emotions the mechanics are eliciting.

    The heart of Triple Town are the strong feelings of pride and accomplishment. These comes directly from the rather amazing investment in extended tactical play that the player exerts when creating their 6x6 city.  A well crafted city can represent hours of carefully considered labor.

    In the Kindle version of the game, I used the sort of end game tropes that you find in Tetris or Bejeweled.  You play the game, you get a score and then move onto the next game.  Most designers rely on proven fallbacks to get the job done since it is difficult to always be reinventing the wheel.

    Unfortunately, this 'obvious' design choice conflicted rather painfully with the slow and steady building of pride. There comes a point at which the player presses a button and in the act of creating a new game, erases all their hard earned progress.  It is surprisingly how many times I've let the game sit on the last screen, not willing to leave it behind.  The label of 'its just a game session that you finish and move on from' didn't fit the emotional response that the other systems were creating.
    • 1st pass: The first attempt at fixing this involved added coins so there is some persistent resource you take with you after each city.  That helps a little, but not enough.   Coins are merely a resource and players weren't sad because they were losing some simple generic token.
    • 2nd pass: The second attempt involved the ability to flip back and look at your city a last few times before you move on.  This was quite effective since it lets the player say goodbye.  The emotional dissonance was channeled into an activity that let players come to terms with it at their own pace. This still isn't good enough.
    Luckily Triple Town is a service, not a game that gets launched and forgotten.  As I design future features, I'm explicitly creating them to amplify the feeling of pride. Fresh in my mind is the lesson that even something as simple as how to end the game involves labeling the context. What if instead of ending the game, you are finishing cities?

    Deriving the world's metaphor from gameplay

    These individual emotional moments form a unique emotional fingerprint for Triple Town.  Due to dissonance, you can't simple apply any theme to this set of dynamic emotions and still end up with an emotionally coherent game.  Instead, you want a theme that fits the mechanics like a glove where the emotional beats elicited by the system dynamics have a clear connection with the labels you'd applied.

    With Triple Town, as with most of my designs, the theme and metaphor for the world came from watching people play.  I would observe and note the emotions and then ask questions about the fundamental nature of the experience that was evolving.  Is this a game about exploration?  Creation?  Building?  If it is a game about building, what is a related theme that matches the current unique fingerprint?  Are you building real estate?  A tomb?  What are those NPCs doing if that is the case?

    Overly on the nose

    After playing many hundreds of hours of Triple Town, I settled upon a metaphor that fit all the nuances of the mechanics.  Triple Town is a game about colonization.  Consider the following common dynamics and how labels derived from the metaphor tie them together in a coherent setting.
    • You've been ordered by the empire from across the sea to build a new city on virgin territory. 
    • In the process, natives (depicted as less than human) keep showing up on 'your' land.  They never attack you, but they keep preventing you from expanding. 
    • So you push them off to the side.  More experienced players create small reservations and pack the natives in as tightly as possible. 
    • Due to overcrowding the natives die off en mass.
    • You use their bones to build churches and cathedrals.
    • When particularly difficult natives appear that seek to escape your reservations, you bring out your overwhelming the military might and remove the pest so you can continue with your manifest destiny. 
    The match between the theme of colonization and emotions of the mechanics was so strong, I tuned it back slightly so it wasn't quite so on the nose.  Instead of selecting a recognizable group that suffered under colonization, I made the NPCs into morally ambiguous bears.   It would have been very easy to present players with a choices that were obviously black and white where players fall back on pre-learned schema.  However, I'm more interested in the edge cases in which a player does something they feel is appropriate and then as time goes on they begin to understand the larger consequences of their actions. At this point in the development of the world, player should naively explore the system and due to the dynamics of game, then form a strong justification of their role as colonists.

    What started as an abstract game is slowly but surely turning into a rich world. What is beyond the city walls? Long term, the themes of colonization, imperialism and the impact on native cultures will unfold over a series of planned game expansions.  With slight variations in labeling, I should be able to tune in a variety of powerful emotions related to the theme of colonization.

    Differences from traditional theme generation

    I find this bottom ups, mechanics-centric method of theme generation quite different from a traditional process of storytelling.  In a narrative heavy game, I think about characters, plot, or message first and foremost and then attempting to fit supporting gameplay into the mix. Often you pitch the world and characters to a publisher and then are expected to come up with gameplay that fits. Consider the implications of these two popular styles of narrative-first development:
    • Unique mini-games and puzzles used to support narrative:  One extreme example of this is your typical adventure game where instead of a core mechanic, you have a series of plot appropriate puzzles.  The emotional aspects of the puzzle (frustration, delight) are only marginally related to the emotional beats of the plot.  Also, in order to avoid dissonance with the wide variety of emotional beats that the story requires, the style of the puzzles is switched up on a regular basis.  It is hard enough balancing one game, but asking the team to balance dozens of tinier games results in shallow systems throughout.   I think of this as chopping up gameplay to fit the story. 
    • Generic gameplay that supports the narrative: A Japanese RPG like Final Fantasy repeatedly uses turn-based tactical combat to illustrate story beats.  The time-tested tactical combat system usually produce a handful of primary emotions such as loss, victory, relief, feeling powerful and feeling powerless.  No matter what story is being told, the same system is called upon to provide emotional support.  Such a pattern avoids dissonance the majority of the time, but then when the plot veers into non-combat area, the dissonance comes back full force.  I think of this as telling more story than the gameplay can naturally support. 
    Some of the most painful design rat-holes I've have ever dug myself into followed these patterns.  In one project, I created a world based off finding relics from a post-Singularity civilization (circa 100AD) deep in the Mediterranean.  In another, I was overly attached to a set of small bobble-headed creatures. For both, I was afraid to change the world. Instead, I desperately iterated upon new game mechanics, hoping to find one that fit my world better.  And I rarely found one.  As far as I can tell, creating a compelling new game mechanic is hard and success is unpredictable.  Yet creating a functional game world's is surprisingly cheap.  Any idiot can copy a working game, toss some pirates on top and call it good.

    Now I follow a different philosophy that better reflects these costs. Gameplay comes first and the worldbuilding are flow from the dynamics of play. If, as you iterate upon gameplay you make a rule change that breaks the emotional connection with a particular world, you should feel very comfortable tossing that world aside and starting fresh.  Create a world that supports the game, not the other way around.


    The amount of theming and world building in Triple Town is still quite light.  Those of players used to the extravagant productions that burden a game with an overworked story may not even recognize the labels I've choosen as having an impact on your experience.  Yet they do and most players will feel the emotional beats of the game quite clearly.

    Nothing I've outlined here is new. The important insight for me has been creating the labels and world for a game as a bottoms up process. You start with the mechanics and then find the labels that fit the emotional beats. From this game play foundation, you build the world.

    Enough rambling!  Go play Triple Town.  It is still a beta so let me know what you think.

    take care,


    Cheat sheet: Steps for tuning primary emotions

    Here's the process for tuning emotions
    1. Create a playful system.
    2. Observe the emotional reactions of the player within that system.
    3. Adjust the system's emotion eliciting conditions to increase or decrease particular raw emotional reactions.
    4. Once you have a rich set of desired emotional responses, brainstorm natural labels that refine the emotions.
    5. Test the labels and see how they elicit specific emotional variations. 
    6. Bundle the labels into a metaphor for your game that communicates and amplifies its unique emotional fingerprint. 

    Note: OCC Model of emotions

    Aki Järvinen's thesis "Games without Frontiers" (pdf) pointed me towards a fascinating model of emotion by Ortony, Clore and Collins (OCC). It posits that emotional outcomes are tied to systemic variables.  For example the strength of a player's dissapointment would be tied to the variable 'likelihood'
    • Low likelihood: If the player predicts a particular result, but they know from past experience that it is highly unlikely, they typically won't be overly dissapointed.  
    • High likelihood: Yet the likelihood is high and the outcome doesn't occur, dissapointment will also generally be more pronounced. 
    By adjusting variables such as likilihood, degree of effort or value of results, the designer crafts a set of 'eliciting conditions'.  I love this phrase since it gives us game friendly terminology for discussing emotion without reverting to the fuzzy non-functional handwaving of the humanities.  By setting your system variables appropriately, you can create eliciting conditions that spark specific categories of emotion.

    There is far more work to be done applying these ideas to game development, but as it stands the conceptual framework is already really quite powerful.  I've referenced here several useful OCC Charts that Aki assembled that list conditions, variables, main emotional categories and emotional variants. (I do recommend you read the full thesis.  It gives a bit more context and it also one of the more clearly written works and easily consumable works to come out in recent years.)

    Emotions resulting from personal well being.  pg. 211
    (Click to enlarge)

    Emotions resulting from events involving the fortune of others. pg. 211
    (Click to enlarge)

    Emotions resulting from future prospects. pg. 212
    (Click to enlarge)

    Note: Surrealism in video games

    Often the best video games have disjointed, narratively surreal worlds. Mario, Pacman, Katamari, Bejeweled and even a game like Portal take place in distinctly surreal locations that obey the logic of association, but are freed from the logic of the real world.  Even more interesting is that despite immense amounts of effort making our labeling systems externally consistent (They aren't 'save points', they are regen tanks), the vast majority of players happily engage in surrealist worlds with nary a complaint.  If anything, the unnecessary justification introduces more unnecessary dissonance into the game by asking the player to pay attention to details that don't functionally matter.

    I see this surrealist aesthetic as the practical outcome of deriving the world from the emotional beats of the gameplay.   The constantly tuning and tweaking of  various labels needed to bring out the best parts of your game fragments the traditional narrative process.  Why is there a walking turtle?  Because it fits the mechanics like a glove. That is all the justification that is required and layering on more burdens both the experience and the development process.  In the end, light surrealist labels are a positive thing since they gives you substantial wiggle room to avoid dissonance. And due to the solid fit with existing emotional dynamics, they often yields stronger game-centric experiences.

    Steambirds: Survival Mobile
    Posted by Lost Garden [HTML][XML][PERM][FULL] on 12 October 2011, 10:26 pm

    Today, we are launching Steambirds Survival for iOS. The layout has been rejiggered to work nicely on the iPhone. And there's a wonderfully expansive HD version for the iPad that it easily my favorite way to play Steambirds. The Android version will follow shortly.  All of them are free, so give it a go and let me know what you think.

    Though this new mobile version of Steambirds Survival shares the same name as web-based game, by partnering with Halfbrick (of Fruit Ninja fame) we've transformed it into a much bigger (and my opinion, better) game.
    • Improved progression system with new missions:  There are 64 missions, 8 of which are infinite survival modes.  If you liked Steambirds and want to play it forever, this is your game.  (Sometimes you need something a bit meatier than a tiny handful of puzzle levels.)
    • Free-to-play:  This is our first free-to-play game on mobile.  Like most of our games, we take the 'free' part pretty seriously.  I want people to buy because they love the game and can't get enough.  I'm very curious what lessons we'll learn. 
    • Multiple player planes: We added a really fun recruitment system that lets you hire multiple player controlled planes.   Running through a level with three Chickadees feels amazing.  Previously lackluster planes like the Cockroach turn into fascinating exercises in multi-plane tactics. 
    • New Reinforcement powerup: You can call in NPC allies to fight along side.   This leads to rather epic mix ups with dozens of planes pinwheeling about in a deadly dance. 

    Does your game have a clear "Arrow of Play"?

    After launching the web version of Steambirds Survival, I was unhappy with the mission structure.  Originally there was an open list of planes that you could unlock in any order.  It seemed like a good idea at the time since 'openness' and 'choice' are good, right?  But we saw that a lot of players would cherry pick a few planes and then after they found one that they liked, they'd just play that plane to grind the in-game currency, copper. As a result, the progression lacked a clear feeling of momentum that encouraged you to trying out a wide variety of different play styles.

    With the new mission structure, you unlock cities one at a time and each city reveals more cities to play.  Within each city, there are 8 sub-missions that give the player to demonstrate increasing levels of mastery to pass. Now, there's a very clear direction to the unlocking and this should give players short term and long term goals to work towards.

    In physics, Arthur Eddington coined the phrase 'arrow of time' to describe how time appears to flow in a single direction.  As you dabble in general relativity, you realize that time is wonderfully compressible and can be manipulated in a variety of clever ways, especially near the speed of light.  Yet even with all this variation, it consistently advances forward.

    When I look at a design, I always ask "What is the arrow of play?"  This is a directional property of the mechanical systems that always moves the player forward. And like time, there's often a surprisingly amount of variation that occurs along the way.  Some players advance slowly, others take strange side paths, but all advance.

    Tools for creating the arrow of play

    In Steambirds Survival, there are a variety of systems that result in a distinct arrow of play.
    • Inevitable decay: Plane health almost always goes downward.  There are very rare health boosts, but they are at best a temporary reprieve. 
    • Escalation: Enemies slowly increase over time.  Waves get larger.  Difficult enemies spawn with increased frequency.  Even the best players find themselves at a point where they can't fight back the chaos any longer and errors creep in. 
    • Short term goals: Short term, you are trying to live long enough to complete mission goals that are just on the edge of your capabilities. 
    • Repeated patterns: Each mission goal unlocks new mission goals.  Once you learn the pattern you can repeat it again and again building momentum like train wheels accelerating down the track. 
    • Resource flow: Each goal you complete earns you copper, which you spend to either facilitate the completion of goals or to unlock new cities. There is a clear resource flow from sources of currency to sinks of currency. 
    • Limited choices:  Unlocking new cities in turn lets you unlock more cities, eventually getting to the point where you have explored all the content in the game.  At once point in my career I thought linearity was a curse. And it is when taken to extremes.  But it is also a tool.   If you end up overwhelming most players with too many choices, the perceived quality of the choices provides goes down.  In Steambirds Survival, there are always at least 4 choices.  You can unlock up two cities.  Or you can attempt missions in at least two cities.  The hope is that it is clear what to do next. 
    • Linear affordances:  The map of cities is a simple list that scrolls in along one dimension.  Should I have made a map that scrolls in two dimensions?  I could have, but I'm not sure it would have improved the quality of the choices that the player made.  Instead, by restricting the dimensionality of the UI, the player can focus on picking a city instead of wandering around a map, trying to remember which corner the next locked item is located at.   (I learned this lesson from map scrolling in Lemmings.  One of my favorite tools for simplify interfaces)
    Games are about change.  The system moves from one state to another at the poking and prodding of the players. Each tick of the clock or press of a button creates momentum that leads the player on a joyful rush through challenge after mastery challenge. You start slowly.  The player builds speed and eventually they steam forward in a continuous state of flow.  The arrow of play leads inevitably to a sense of pacing.  Yet critically it approaches these not from a traditional narrative perspective, but as a property of the game systems.  The beats of the game rhythm are those clicks and taps turning tight loops over and over.  Steambirds is a turn-based strategy game, a genre typically seen as a slow and plodding.  Yet in the middle of a dog fight, it can feel like an action game.

    A system that lacks a clear arrow of play results in players being mired in odd dead ends.  It isn't enough to make a game that has feedback loops, widgets to master and all the various atomic elements of a game.  It also needs a strong sense of momentum that like time or entropy hurtles the play forward.

    take care,

    Panda Poet: My most social design
    Posted by Lost Garden [HTML][XML][PERM][FULL] on 31 October 2011, 3:04 pm

    Way back in 2010, Spry Fox put out a single player word game for the Kindle called Panda Poet.  I had always had some vague ideas for a multiplayer variation so when an opportunity came up to create an original HTML 5 game, I pitched play-by-mail Panda Poet.  As David says over on his blog, this is our third release this month so things have been a wee bit hectic.  Reminder to self: do not launch multiple new games while attempting to vacation in Japan.

    As with all my projects, we spent the first few months heavily iterating on prototype designs.  I went back to the root of the original concept and ended up deviating substantially from the single player mechanics.  The game still involves growing pandas by spelling words.  But now the game is based around a capture mechanism that lets you take pandas from the other player.  The territory aspects of the game give play a rather unique feel and the end result reminds me of "Scrabble meets Go."  The timer countdowns that were such a large part of the single player game are gone.  Playing against another player who constantly creates words out of any letters you didn't use ends up being more than enough pressure to give the game forward momentum.  The arrow of play is strong in this one.

    Go give Panda Poet a try over at  Or install it on the Chrome Web Store. Invite a friend to play.  It is more fun.

    Putting the social into a game

    Most multiplayer games played over the computer aren't very social.  In console games, you get a lot of teabagging and swearing with very little space or time set aside for meaningful social dialog. In games on social networks, you find people poking one another using cynically automated systems. There's a pushy one-to-many broadcast aspect of the experience that does little to encourage deeper social bonds.

    My wife is a longtime player of Words with Friends and seeing her chatting with complete strangers for months on end reignited my interest in play-by-mail games.  You can think of these games as a bit like a conversation.  You make a statement by playing a turn and then pass the conversation onto the next person so they can respond.  Side by side with the game is a chat window, but the important realization is that both the chat and the moves you make in the game are forms of communication.

    Panda Poet follows a similar model.  It has an inbox, just like an email program and you can have multiple conversations going at once.  Here are some observations:
    • Every interaction is opt-in:  Everytime you choose to make a move, you are signaling that you want to continue the relationship.   There's little penalty for dropping out. 
    • Relationships grow over time:  Many random matches put strangers together.  Initially, people play silently for long stretches of time.  However, very slowly you get the occasional safe comment.  Eventually this blossoms into more detailed conversations.  Trust comes from a long series of safe and reliable interactions.  Each time you submit a turn, you are building trust and respect. 
    • Griefing is difficult: If someone is rude, you just resign from the game and stop playing with them.  Or you don't play the next turn. It is possible to spam someone, but number of people effected is so minimal and the feedback in response to your Killer cleverness so sparse that it is rarely worth it.  The typical incentives driving griefing fizzle without an audience or social status.
    • You can build on existing relationships: When was the last time you did any activity with your brother or close friend from college that now lives a thousand miles away? We live in social world fractured by Schumpeter's creative destruction.  You dwell in distant lands as determined by the latest job opening.  As a result, the deeply meaningful local relationships that dominated life of eras past suffer. Social isolation is a very real consequence of the capitalist eradication of that most charming of labor rigidities, a generational home.  Games like Panda Poet give you a private shared space to reconnect.  Take five minutes out of your day and create a new experience with the ones you once held near. 
    I see immense potential in this style of game and I'll be using similar multiplayer structures in future games.  When you design a game with real social play, ask "What is the intrinsic rhythm of back and forth conversation between participants?"  If this key pattern has no space to exist, then perhaps you aren't creating a social game after all.

    take care,


    Other Notes

    • Easy initial learning curve:  People get that you are supposed to spell words.  There doesn't seem to be much confusion over the basic UI.  
    • The game is reasonably well balanced. I've seen multiple games between two skilled players that are decided based off the final few words.  You almost never find yourself halfway through the game in a position where it is impossible to make a comeback. 
    • Pacing:  I'm adore the short play sessions (a single turn takes 10-30 seconds).  However, since players can have multiple games going, you get a random distribution of games popping up throughout the day much like email or an IM conversation with a friend.  This combined with a daily email archive  prompting people to check back into the site and catch up on waiting games should yield a reasonably high rate of retention. 
    Our big challenges going forward:
    • Complex capture mechanics: The capture mechanics are a dash too complex for casual players to understand the strategic elements of the game immediately.   In particular, it takes multiple games for players to understand how to lock in pandas mid game. 
    • Poor monetization opportunities:  Right now there's just an initial Premium version that removes ads and gives access to a more expansive and strategic board layout.  My suspicion is that we are going to need to do a lot more work to craft a compelling offer. 

    Plagiarism as a moral choice
    Posted by Lost Garden [HTML][XML][PERM][FULL] on 16 November 2011, 9:44 pm

    Plagiarism is defined in dictionaries as the "wrongful appropriation," "close imitation," or "purloining and publication" of another author's "language, thoughts, ideas, or expressions," and the representation of them as one's own original work, but the notion remains problematic with nebulous boundaries.

    The modern concept of plagiarism as immoral and originality as an ideal emerged in Europe only in the 18th century, particularly with the Romantic movement, while in the previous centuries authors and artists were encouraged to "copy the masters as closely as possible" and avoid "unnecessary invention.

    The 18th century new morals have been institutionalized and enforced prominently in the sectors of academia and journalism, where plagiarism is now considered academic dishonesty and a breach of journalistic ethics, subject to sanctions like expulsion and other severe career damage...

    Plagiarism is not a crime per se but is disapproved more on the grounds of moral offence...
    -Wikipedia's entry on Plagiarism

    Thought: Most professional game developers are also professional plagiarists

    Here's a quiz for all the game developers who are reading:
    • Do you follow the rule of thumb "90% familiar, 10% fresh"?
    • When you look at the game you are working on is there a direct comparable?
    • Do your designers say "For that feature let's model how X did it" and consistently refer to the same pre-existing game?
    • Is your primary reference a game considered original or innovative in the last 3-5 years?
    • Is your primary philosophy of design "I could totally make a better version of game X"
    • Do you copy mechanics and assume that adding different content such as levels or graphics makes your game unique?
    If you follow these patterns, you are likely a plagiarist. To rewrite the industry's golden rule in the language of other arts, "90% is plagiarized and 10% is remixed to give the illusion that the player is engaged in an original work."

    This lazy and morally offensive practice has become a social norm within our incestuous industry. We don't even consider that there might be alternative method of developing games. We are the equivalent of the western world before the suffrage movement. Or the South before the civil rights movement. We look at our current derivative behavior, acknowledge that it is harmful and then proceed to dogmatically justify its continued pursuit based off economic, legal, historical and short-term selfish reasons. Yet the fact that 'everyone does it' fails to provide a strong moral foundation for an act that diminishes our industry and damages the minority that strive to create original works.

    Where plagiarism differs from evolving key innovations of the past

    It is a common practice to include individual mechanics inspired by previous games. This is a natural part of the creative process. Plagiarists, however borrows systems en mass. They takes not just the movement mechanic from Zelda, but the flow of the dungeons, the majority of the power ups, and the millisecond by millisecond feel of the game.

    Game designs are very close to a mechanical invention.  The rules, interface and feedback systems all create a reproducible set of player dynamics.  Think of a game as an invented 'fun engine' that when placed in front of a player yields delight and mastery.

    Developers go through a few stages of invention when building games.

    1. Copying a design. Most programmers make a simple copy of an existing functional game as part of their learning process.  You copy everything including interface, levels, scoring and more. You don't understand why the game works so you replicate it in the hopes of blindly capturing the magic. You may change out the art, but otherwise it is the same game. 
    2. Modifying an existing design. Usually this involves just playing with existing parameters or content.  You might add a a triple shotgun and new levels to your Doom-clone.  You still don't understand the game, but you can play with safe variables like narrative, level design or theme that are unlikely to ruin the value of the core mechanic. Warcraft is a classic example of a modification of the original Dune 2 RTS design. 
    3. Adding to a design. Taking the core fun engine and add something to it. Think of this as adding a turbo charger on an existing car.  Sonic took Mario and made the main character much faster.  In the best games this results in a cascade effect throughout the entire design that requires you to rethink content, pacing, scoring and more. 
    4. Synthesizing a new design. Take multiple disparate parts and put together a new game that has unique dynamics. A game like PuzzleJuice is a great example of a synthesized design that takes elements from Tetris and Boggle.  To many players, it feels like a brand new games built out of familiar pieces. 
    5. Inventing a design. Using a variety of sources of inspiration, create a new fun engine that is unique and new to the world. 

    The early stages of copying are an essential process that all students of game design should undertake.  As a learning activity, there isn't a lot of money in creating master studies, but it is a respectable pursuit along the path to self improvement.  As long as students cite their inspiration and refrain from competing directly with the original creator there is little conflict.

    The later stages of invention are risky, difficult work.  There's an immense amount of experimentation and failure.  Even the simplest game inventions (such as Tetris or Lemmings) were the result of years of diligent labor by master designers.  There aren't a lot of these people, yet they bring immense amounts of joy to the world.  They deserve to profit from their inventions and in general players are excited to spend their money on new, delightful games.

    The plagiarist is someone who wants to shortcut the process of invention. They decide that it is cheaper to copy as much a possible so that the dynamics of a previous game are preserved. Then cosmetic tweaks are applied and the copy is sold as a new thing by an original creator. Changing out the graphics or giving the game a new plot are the most common tweaks because they are easily decoupled without damaging the delicate dynamics of play.  When you look at the games released on the market, you can easily see that there is a spectrum of theft.  The most blatant plagiarists are those that steal the most and innovate new mechanics and dynamics the least.

    The economic and human cost of plagiarism

    By cheaply creating games without needing to pay the cost of research and invention, plagiarists are able to quickly release games into markets that the original innovator has not fully addressed. Clones therefore capture value that would have otherwise eventually accrued to the original innovator. For example, clones of Minecraft that reach XBLA earlier tap unmet demand and reduce the audience for Minecraft when it eventually releases there.

    On first blush, consumer advocates might imagine that this is a fine situation. They get a product they like faster and as the population of plagiarists merrily plagiarize one another, you end up with an explosion of quality choices.

    Consider how this effects the original source of the innovation. While the overall market may be larger, the original innovator is left naked with no protection that lets them recoup the cost of the initial invention. There are few legal protections for game inventors. There is only the stark reality that many smaller independent developers, the life blood of innovation in our current markets, are blindsided by a blast of competition that they lack the development resources, distribution agreements or business expertise to successfully compete against. The plagiarists capture the majority of the market, establish well known evergreen brands and the original innovators are at best a footnote.

    As a result of this tragically common feedback loop, those inclined to innovate are discouraged from innovating in the first place. Why innovate when it costs you money and doesn't yield the competitive advantage you might hope due to the nearly instantaneous influx of copy-cat competitors? It may look like a better business option to simply join the plagiarists and avoid the whole expensive innovation thing in the first place. It is no surprise that the game industry tends to have a large number of evolutionary works, but fewer genre-busting founder works.

    The plagiarist's 'make a buck at any cost' attitude directly results in a creatively stagnant industry long term.  You don't need to look far to see concrete examples of these dynamics in action. Note how quickly the cartoonishly mercenary plagiarism-focused culture of social games turned a bright spot of burgeoning innovation into an endless red ocean of clone after clone within a mere handful of years. Such a wasteland fails to grow the market and ultimately leads to less consumer choice.

    Plagiarist pride

    There is of course skill in plagiarizing well, just as there is skill in forging a famous painting. To be a professional plagiarist is laborious work. I acknowledge this. We've developed a whole subculture of designers that specialize in the subtle arts of copying the work of others. A 'good designer' is one that excels at 'researching comparable games'. They steal with great care from only the best. They also excel at 'polish' which has been warped to mean the skill at reverse engineering a comparable game so that the copy feels identical down to the smallest detail.

    The current industry put such skills on a pedestal. We hire for them and we pay top dollar for reliable execution. Yet at best, these are the skills of a journeyman, mechanically copying the master works of past giants.

    If you stick to doing only this, there's a pretty clear career path. You end up as a wage slave. Typically such laborers are hired by businesses that couldn't give a damn about pushing the craft of game design forward. Instead, the goal is another product for another slot on either the retail shelf or the downloadable dashboard. Grind it out, worker bee. If you can copy a past hit by the flickering candle of midnight crunch, your family gets its ball of rice for the day. This is the entirety of your creative worth. If you go to sleep each night thinking "I'm a hack, but at least I pay the bills", you deserve pity. And you need to contemplate the quiet whisper that maybe you don't need to spend your entire career diligently copying others.  Remember when you were a sparklingly original creative person?  Remember when you wanted to change the world? Remember that time before you compromised?

    Plagiarism is a moral choice

    We live in an economic world.  Yes, you need to eat. We also live in a legal world.  There is a rather low minimum bar for our behavior. But as creators and artists, we can each choose where we put our creative energy. What we create has a moral and emotional component that is perhaps more important for both our mental health than any paycheck. To be a plagiarist and to stay a plagiarist is to waste your very limited time on this planet. What amazing things could you be making if you didn't spend so much time slavishly copying others?

    What's the alternative? Why not start up a small prototyping project? Knock a genre down to its most basic element. Give yourself constraints so you intentionally do not replicate games of the past. Rebuild your game from that simple foundation, borrowing elements from the entire breadth of game history. Finish a game that has a half dozen influences from widely disparate games that in the end create a player experience that is uniquely yours. This is how you stop being a plagiarist and start becoming a master game designer.  There is still time to create something amazing and new.

    take care,

    Useful links

    The Real Triple Town available on iOS and Android
    Posted by Lost Garden [HTML][XML][PERM][FULL] on 19 January 2012, 5:56 pm

    The holidays were crazy. Instead of opening presents, we were putting the finishing touches on the mobile version of Triple Town. Some late nights all around. Big kudos to Cliff Owen for doing an immense amount of the heavy lifting.

    Triple Town for iPhone and iPad

    Triple Town for Android

    If you love Triple Town, please download it (it is free) and rate it. We are in a bit of a David and Goliath situation here since a very large and nasty company copied Triple Town on mobile right at the end of December. We're a small team and we work hard, but moving to the phone took a few precious months. I don't quite know how to express the feeling of bleeding our lives out trying to finish the game...all while watching a soulless shark lavishly spend VC cash to ride up the chart. Using my own design. That was like a punch in the gut. Betrayal, violation and powerlessness all wrapped up into one unpleasant emotion. This has easily been one of the most emotionally difficult releases I've ever done.

    To add insult to injury, the night we got ready to upload the Android version we made an awkward discovery: There was already a game called Triple Town being sold by a certain Mr. WangYang.  In fact, it was Triple Town.  The art was ripped from the web version.  The logo was the same.  Check out that screenshot...captured for posterity.  I want to send big thank you to Google.  Even though their offices had closed for the night, they took down the fake immediately.  That was deeply appreciated.

    Ripped off: An example of a counterfeit game.

    The best and most positive thing anyone who loves innovative indie games can do is spread the word about the original. Share the link. Download Triple Town. Write a review. Tell your friends. Heck, I tell strangers in coffee shops.

    No one ever complains since a good indie game is an authentic joy. The next time I see someone after introducing them to Triple Town, all they ever want to talk about is Triple Town. It becomes an essential part of their life. It doesn't matter that it was done by a few guys working out of home offices. All that matters is that it is a good, original game that players love. I figure the Fast Follower bastards may have money and evil on their side, but maybe a passionate community and some word of mouth about a decent game can carve a small space for the little guys.

    Big thanks for all the continued requests asking us to make Triple Town for mobile. It kept me going.

    take care,

    PS: Also a lot of folks told me they just wanted to 'buy the damned thing'. So even though the game is still free if you want, you can now pay once and get unlimited turns.

    PPS: First game in Unity! Very nice!

    Standing up for ourselves
    Posted by Lost Garden [HTML][XML][PERM][FULL] on 29 January 2012, 11:00 am
    Sometimes you need to stand up for yourself, or you're just begging to be taken advantage of.

    We (Spry Fox) have filed a copyright infringement suit in federal court against 6Waves LOLAPPS in response to their release of Yeti Town, their blatant copy of Triple Town. This was a difficult decision for David and I. We are not enthusiastic about the prospect of spending our time in court as opposed to making games. And in general, we believe that only in the most extreme circumstances should a video game developer resort to legal action in order to defend their creative works — the last thing our industry needs is frivolous lawsuits. Unfortunately, it is our opinion that 6waves has behaved in a reprehensible and illegal manner, and we can not, in good conscience, ignore it.

    The full legal complaint can be downloaded here. In particular, I will call attention to these issues:

    First: Yeti Town, as launched by 6waves, was a nearly perfect copy of Triple Town. We’re not just talking about the game’s basic mechanics here. We’re talking about tons of little details, from the language in the tutorial, to many of our UI elements, to the quantities and prices of every single item in the store (how exactly did 6waves “independently” decide to price 200 turns for 950 coins, or 4 wildcards for 1500 coins each? That’s quite a coincidence!) But don’t take our word for it. Here are just a few quotes taken from the numerous press articles that were published shortly after the release of Yeti Town:

    • Gamezebo: "Unfortunately for Yeti Town, the only substantial difference between it and Facebook’s Triple Town is the platform it's on. Otherwise it’s the exact same game, only this time with snow."
    • InsideSocialGames: "Yeti Town is a matching game nearly identical to Spry Fox’s Triple Town"
    • "Replace "saplings" with "bushes", "tents" with "houses" and "yetis" with "bears". What do you get? Something that would look a lot like independent developer Spry Fox's Triple Town"

    Second: what most people don’t know is that 6waves was in confidential (under NDA) negotiations with us to publish Triple Town at the exact same time that they were actively copying Triple Town. We gave 6waves private access to Triple Town when it was still in closed beta, months before the public was exposed to the game. We believed those negotiations were ongoing, and we continued to give private information to 6waves, until 6waves’ Executive Director of Business Development sent us a message via Facebook on the day Yeti Town was published in which he suddenly broke off negotiations and apologized for the nasty situation. His message can be found in its entirety in the body of our legal complaint.

    It’s bad enough to rip off another company. To do so while you are pumping them for private information (first, our game design ideas, and later, after the game was launched on Facebook, our private revenue and retention numbers) is profoundly unethical by any measure.

    Despite all this, David and I still struggled with the idea of initiating a lawsuit. However, 6waves brought the issue to a head when, rather than openly and honestly discuss their actions, they had the chutzpah to tell Gamasutra that they had developed Yeti Town completely independently, and characterized the legitimate public criticism of their company as simply “part of the natural process” of game development.

    We believe that there is nothing “natural” or ethical or legal about 6waves behavior. What they did was wrong. And if they get away with it, it will simply encourage more publishers to prey on independent game developers like us. We refuse to sit back and let that happen.

    -Dave & Danc

    Giving a talk at plague stricken GDC 2012 on sexy-sexy innovation
    Posted by Lost Garden [HTML][XML][PERM][FULL] on 1 March 2012, 11:15 pm
    It is that time of year when I bodysurf the sweating developer crowds in San Francisco and inevitably contract to some horrible nerd-specific viral infection. Current theory: Never touch the glasses.  The past three years have resulted in the entire week of GDC being a blur of  fever and fatigue-induced hallucinations interspersed with violently explosive sneezing fits.  Here's to GDC 2012: Reliving Twelve Monkeys for the fourth year in a row.

    Somewhere in the midst of all this, I'll be giving a talk on game design.  David, who somehow manages to thrive on the additional contact with humanity, is doubling down on two talks.  His immune system must be made of titanium.  Alternatively, I hear if you eat a school teacher at the first sign of illness, you double the effectiveness of Cold-Eeze.  No wonder there is a teacher shortage.  I blame GDC.

    Here's my plan.  I'm just going to stand on some stage, deep in a fog of over-the-counter drugs and say something, anything.  Last year, people looked like rhubarb-colored elephants.  I hope my mouth movements makes sense to the mysterious minds behind those enormous loxodontal ears.  I never watch the videos afterwards so I'm blissfully ignorant of the actual outcome.

    Realm of the Counter-Intuitive God (SOGS Postmortem)
    SPEAKER/S: David Edery (Spry Fox)
    Monday 11:15-12:15 Room 135, North Hall
    Social and Online Games Summit / 60-Minute Lecture
    Description: Realm of the Mad God is a web-based f2p MMO with a penchant for breaking rules. It’s a MMO bullet-hell-shooter… in Flash. It is based on open source art. It features permadeath (the ultimate in retention challenges)! And it just so happens to be surprisingly popular and very profitable. This lecture will review some of the unusual design and business choices we made and explore which worked, which didn’t, and why. Financial and other data will be shared (and not just the stuff that makes us look good).

    Create New Genres (and Stop Wasting Your Life in the Clone Factories)
    SPEAKER/S: Daniel Cook (Spry Fox)
    Tuesday 3:00-4:00 Room 135, North Hall
    Social and Online Games Summit / 60-Minute Lecture
    Description: Re-releasing old designs with pretty new graphics means me-too titles fighting off a crowd of similar products. This is the path to mediocrity. To become a master designer, you need to break past a slavish devotion of past forms and create vibrant, new experiences. This design talk covers practical techniques for reinventing game genres. The goal is the invention of a unique and highly differentiated customer value proposition that makes both strong business sense and is also deeply creatively fulfilling. We cover designing from the root, reducing design risk, and igniting original franchises. We also cover the pitfalls of design innovation including fending off shark-like fast followers and other cloners. The presentation covers personal examples from recent titles such as Steambirds, Realm of the Mad God, Triple Town and other innovative successes.

    How F2P Games Blur the Line Between Design and Business
    SPEAKER/S: Soren Johnson (Game Developer Magazine), Ben Cousins (ngmoco Sweden), Matthias Worch (LucasArts), Tom Chick (Quarter to Three) and David Edery (Spry Fox)
    Friday 4:00-5:00 Room 2003, West Hall, 2nd Fl
    60-Minute Panel
    The free-to-play movement is here to stay and will touch every corner of the games industry. However, the format blurs the line between game design and game business, so that business decisions will become increasingly indistinguishable from design decisions. Free-to-play content must be fun enough to attract and retain players but not so much fun that no one feels the need to spend some money. Managing this tension makes free-to-play design extremely difficult, especially for traditional game designers who are used to simply making the best game possible. Our panelists will discuss this transition and best practices for building free-to-play games with soul.

    See you there.

    Loops and Arcs
    Posted by Lost Garden [HTML][XML][PERM][FULL] on 29 April 2012, 8:15 pm
    Here are two tools I've been using lately to better understand the functionality of my game designs.  The first is the loop, a structure that should be very familiar to those who have looked into skill atoms.  The second is the arc.


    The 'game' aspect of this beast we call a computer game always involves 'loops'.
    • The player starts with a mental model that prompts them to...
    • Apply an action to...
    • The game system and in return...
    • Receives feedback that...
    • Updates their mental model and starts the loop all over again.  Or kicks off a new loop. 
    These loops are fractal and occur at multiple levels and frequencies throughout a game. They are almost always exercised multiple times, either within a game or by playing the game multiple times.

    Nested, dependent loops yields complex feedback loops and unexpected dynamics.  Loops tend to deliver value through the act of being exercised.  Thus they are well suited for mastery tasks that involve trial and error or repeated exposure. The goal of both loops and arcs is to update the player's mental model, however loops tend to rely on a balance of the following:
    • Interrelated actions that trigger multiple loops in order to bring about specific system dynamics.
    • Systems of crisply defined cause and effect that yield self contained systems of meaning.
    • Functional feedback that helps players understand causation. 
    Loops are very good at building 'wisdom', a holistic understanding of a complex system.  The player ends up with a mental model that contains a thousand branches, successes, failures and nuances that lets them approach new situations with confidence.


    'Arcs' have similar elements to a loop, but are not built for repeated usage. The player still starts with a mental model, they apply an action to a system and receive feedback. This arc of interaction could be reading a book or watching a movie. However, the mental model that is updated rarely results in the player returning to the same interaction. The movie is watched. The book consumed. An arc is a broken loop you exit immediately.

    Arcs are well suited for delivering a payload of pre-processed information.  You'll typically find many arcs have the following footprint:
    • Simple independent actions such as turning a page or watching a movie
    • Simple systems that rely heavily on complex mental models to have meaning.  Text on a page is a good example. 
    • Complex evocative feedback that links together existing mental models in some unique, interesting or useful manner.  For arcs, the feedback is 99% of the payload and the actions and systems are simply a means to an end.  Once this payload is fully delivered, the value of repeated exposure to the arc drops substantially. 
    Arcs are highly efficient at communicating 'success stories', a singular path through a system that someone else previously explored. The best teach a lesson, either informative, positive or negative. This is a brilliant learning shortcut but the acquired knowledge is often quite different and less robust in the face of change than 'wisdom'. With a slight shift in context, the learning becomes no longer directly applicable. It is not an accident that we make the distinction between 'book learning' and 'life experience'.

    One of the common issues with arcs is that people burn out on them rapidly, rarely desiring to experience them more than once. It is possible to give arcs a bit more staying power by stringing them together serially in a sequence of arcs. This is a pretty proven technique and is at the base of the majority of commercial attempts to give content arcs longer retention.  Businesses that rely on a constant sequence of arcs to bring in ongoing revenue often find themselves running along the content treadmill.  If you stop producing content, the business fails.

    Any loop can be superficially described as a series of arcs with one arc for each pass you make through the loop. This is an expanded loop. This is useful for recording a particular play-through, however it tells you little about the possibility space described by the loops.  Where loops often describe a statistical spectrum of outcomes, the arc notation describes only a single sample.

    Mixing Loops and Arcs

    Since both loops and arcs can be easily nested and connected to one another, in practice you end up with chemistry-like mixtures of the two that can get a bit messy to tease apart.  The simplest method of analysis is to ask "What repeats and what does not?"

    Narrative games are the most common example of mixing loops and arcs.  A simple combination might involve layering a segment where the player is engaged with loops with a segments of arcs.  This is your typical cutscene-gameplay-cutescene sandwich.

    However, the analysis can get far more detailed.  For example:
    • Parallel Arcs: You can treat the emotional payload of song as an arc that plays in parallel to the looping gameplay.
    • Levels:  The spatial arc of navigating a level provides context for exploring variations on a central gameplay loop. The 'Golden Path' in a single player level is really just another name for an arc. 
    • Micro Parallel Arcs:  A game like Half Life combines both levels and parallel arcs to deliver snippets of evocative stimuli as you progress through the level. 
    These structures also exist in traditional media. For example, if you look at a traditionally arc-based form such as a book, you find an odd outlier in the form of the Bible.  At one level of analysis it can be seen as a story arc that you read through and finish.  However, it is embedded in a much larger set of loops we casually refer to as a religion. The game-like loops include everything from worship rituals to the mining of the Bible in order to synthesize weekly sermons.  The arc is a central rule book for a larger game consisting primarily of loops.

    In the past I've discussed criticism as a game that attempts to revisit an arc repeatedly and embellish it with additional meaning.  The game is to generate essays superficially based on some piece of existing art.  In turn, other players generate additional essays based off the first essays.  This acts as both a referee mechanism and judge.  Score is accumulated via reference counts and by rising through an organization hierarchy.  It is a deliciously political game of wit that is both impenetrable to outsiders and nearly independent of the actual source arcs.  Here creating an arc becomes a move in the larger game. Intriguingly, tabletop roleplaying games use a similar core structure though the high level rewards differ.

    Even in these complex cases, understanding which behavior is a loop and which is an arc helps tease apart the systemic behaviors. Of the two, loops are rarely discussed in any logical fashion.  People note the arcs and comment on them at length while being quite blind to the loops driving the outcomes. Both criticism and religions are lovely examples of how loop analysis can provide a practical description of the game's ruleset and magic circle even when the actual players are only vaguely aware of their constraints.

    The growth of arcs in games

    In the pre-computer era, games dealt almost entirely with loops.  The light arcs that games like Chess or Monopoly contained served the highly functional purpose of triggering a player's mental schema.  Once that setup payload was delivered, the games focused almost entirely on loops. One could easily claim that historically the term 'game' was used to describe an entertainment made predominantly of loops.

    With the advent of computer games, designers started mixing more arcs with their loops. Adventure games, game endings and other narrative elements became more prevalent.  There are strong cultural and economic reason why this occurred at this period of time that are not strictly an inherent function of the computer game medium.

    The primary driver for the proliferation of arc-based games is that they fit nicely into the existing retail business model.  Over the past 40-years, the dominant way you made money off media was to sell the customer an arc, be it a book, an album or a movie.  Once they had consumed that, you sold them another one.  With a large enough portfolio of games (typically managed by a publisher), you'd get a reliable stream of revenue.

    As is the case with evolutionary systems, certain ill-fitting forms of games were punished financially and thus faded from the market. Assume you tried to build a popular evergreen game. You sell it once and that is the only money you get for the rest of the consumer's life. The retailers didn't want that outcome. Nor did the publishers. They preferred to sell players multiple games a year, year after year. The developers that made games that fit the constraints of this specific market reality flourished with profits from mega hits used to fund future moon launches.  Many of the modern game tropes such as beatable games, sequels, game concept conveyable by box covers, etc are a direct result this early retail environment.

    Again, this is a statistical process, not a conspiracy.  Mammals and dinosaurs coexisted for millions of year but the shifting climate ended up being more amendable to one form than the other.  During the retail era, evergreen games still existed, but in diminished quantities.

    Since systems are hard to understand, one popular just-so story that emerged during this period that arc-heavy games are some ideal outcome of new computer technology. This matured into a strange arc-worshipping segment of the population that predicts a technology-driven singularity for games that involves ever richer payloads and an eventual acceptance as an equal of other arc-centric media. Someone like David Cage, maker of Heavy Rain, is a modern example of such ideals.  But the roots go back much further to the dreams of early science fiction writers and researchers that had little practical experience with creating games.  They sold us a delightful dream for the future of games without understanding the first thing about the actual loop-like nature of games.

    On reflection, it seems quite false to claim computers enabled arc-heavy gaming. A choose-your-own adventure was technologically feasible a hundred years ago. This suggests that arc-heavy games are not nearly as inevitable as some might imagine.

    Consider the arcade market with its very different business requirements.  The arcade owners, publishers and developers were less interested in selling consumable boxes and more interested in repeat play.  This business constraint encouraged the creation of evergreen loop-based games that thrived for decades. The market and the culture hugely shapes the form of the games we make. It is certainly not locked in stone.

    The market is shifting once again.  With in-app purchases, there is a large financial benefit to keeping the player engaged both emotionally and financially for long periods of time.  A fit game is one that you play forever all while paying for your hobby.  It is not one you beat and cast aside. This suggests that loop-heavy games may be making a comeback.

    Untangling loops and arcs in existing game forms

    So how do we evolve our designs with the market environment?  One exercise I've been performing on various games is identifying loop and arcs in a popular genre and then removing the arcs to see if what is left stands on its own.  What I've discovered is that arcs are almost never critical game elements. You can remove them and still have a playable game.

    As an exercise, take your favorite genre (such as platform games) and remove the following:
    • Puzzles
    • Missions
    • Narrative sequences that are not specifically functional feedback that powers the completion of a loop.
    To take this one step further, remove any elements of a computer game that you can 'beat' or that render the game boring or meaningless upon repeated play.

    Can you make a wonderful game out of the remaining bones?  The vast majority of the time you can.  Even deeply arc-heavy graphical adventure games yield procedural hidden object games at their root.  Now, you can never get rid of arcs completely, nor would you want to.  Loops and arcs are ingredients and the goal is to create a new recipe with different mix rather than unquestioningly recreated the same meal again and again.

    A brilliant future for loops

    However, this is admittedly a rather reductive exercise.  What I'm far more interested in is what happens when we, as designers and developers, invest our full energy in exploring the potential of loops.  The language here is far less developed and it is an extremely fertile field for a young developer to make their mark.  Consider the following sparely settled frontiers:
    • Both Will Wright and Notch made millions by exploring the loops of player expression.  
    • Eve forges forth into new territory with every update by exploring the loops of economics and politics.  
    • Star Craft thrives because it taps into the mastery loops at the competitive heart of sports.  
    • No one is even talking about the loops inherent in religion, a system that has driven the behavior of humanity for thousands of years. 
    • Games of improv or bluffing or charades are all loop-based activities with nearly zero traction in the markets today.  These are games that can be played for life. 


    Look for loops and arcs in your game.  What is the balance between the two elements in your design?  What does your game need?

    This isn't a black and white situation and I respectfully ask you to avoid couching this in any tired us vs them terminology.  There is not one market.  You may find that the traditional arc-heavy recipes are exactly what you need.  If you are selling to a community whose norms for buying games were set during the retail era, creating a great beatable payload of entertainment may make you a lot of money.   Many of the popular indie sales channels remain conservative recreations of markets past.  It is a well trodden path.
    • Author evocative arcs
    • Build sequels 
    • Reduce portfolio risk in order to survive long droughts between mega hits 
    If you are making a more modern evergreen game, consider how loops may result in delivering long term value to the players.  Question the forms of a traditional game and ask yourself if they are still valid in today's market.
    • Invent dynamic loops
    • Build a hobby
    • Create a fortified island nation with an ongoing stream of revenue
    This is admittedly the harder path.  You need to analyze your design preconceptions. You need to understand the psychological functionality of what you are building something instead of merely mimicking patterns of the last generation.  Break your game down into loops and arcs.  Understand what is filler.  Understand what core elements form a endless engine for generating value (be it 'fun' or your outcome of choice.)

    Above all, evolve.

    take care,

    Prototyping challenge: Make a web-based 3D modeling toy
    Posted by Lost Garden [HTML][XML][PERM][FULL] on 6 May 2012, 8:48 pm
    I'm rather obsessed with user generated content, particularly art tools.  Recently, I had a wonderful experience with Realm of the Mad God.  Alex Carobus added in a simple pixel editor that allowed anyone to create sprites that might be used in the game.  Very rapidly, players created thousands of truly delightful pieces of art.

    Inspired by this, I set a design challenge for myself.
    • 3D in a browsers. What is an easy-to-use 3D modeling tool that lives in the browser?
    • Unique style:  I want the output to be instantly recognizable as being created in this toy.  That means radically constraining the tools.  Instead, I was particularly inspired by the extruded 3D style of Land-a Panda. 

    • Minimalism: Are there any ways of simplifying 3D modeling? What is the pixel editor equivalent of a 3D modeling tool?
    • Professional results:  Can we build something where you look at the results and think "Wow, that is really nice."  Think of it as the Instagram effect. I'm particularly targeting casual games, but I suspect if that is nailed, people will find all sorts of uses for the toy. 
    What I'm avoiding:
    • No copying an existing tool.  Sure there are well established paths for 3D modeling or vector editing, but that is too easy.  Lets go back to the design roots of these complex monstrosities and build up something elegant and different. 
    • No voxels: I don't want to use voxels.  Minecraft already does this so let's push in a wacky new direction. 
    The closest I've found that fits these constraints is the amazing TinkerCad, which is a simplified solid modeling tool.  It is very nice, but only really ticks the first checkbox.

    Here's what I've come up with.  If anyone find the idea curious enough and wants to build a prototype over a few weekends, I'm happy to collaborate.  This wacky, broken and experimental.  But what is the fun in sharing only perfect ideas?

    Model Toy

    Model Toy: An easy to use drawing and modeling tool for making stylized objects

    Model Toy is a 'back to the roots' effort that asks if you can make a modeling tool by only manipulating vertices on simple curves. The tool is made of several basic elements
    • Grid-based drawing plane: All drawing occurs on a plane.  This can feel more like a 2D tools than a 3D tool. 
    • Shapes:  The key primitive is a unique extruded vector shape defined by 4 points on a plane. 99% of the time, the artist is moving around vertices. 
    • Shape Palette:  A list of available primitive shapes. 
    • Shape Properties:  List of the current shape's color, extrusion, etc. 


    The heart of the tool are these odd 2D path-based primitives that Pete Blois and I have been experimenting with.  You can play with an example of it here:
    • The shape is a 2D vector composed of 3 to 4 vertices. 
    • Each vertex is either a rounded corner, half rounded or straight corner. 
    • Vertices only snap point on the grid. 
    • The shape can be extruded and beveled. 
    These actually came out of a lot of different experiments and I realized something really obvious.
    • Engineers tend to make art primitives that have lots of knobs and widgets...they are highly parametric objects with a complex interface.  
    • Yet, many artists don't necessarily think in terms of complex objects.  Instead, they use simple  things that are easily manipulated and then repeat the same tweaking action thousands of times until the composite result is interesting.  There are no explicit 'rotation' or 'scale' operation when painting.  Yet the results are still impressive.  
    • So this design preferences 'tweaking thousands of times' over 'a complex object where you set variables once'.

    Basic move, scale and translate operations

    One interesting aspect of these primitives is that they don't have an explicit scale, rotation or translation matrix for the user to manipulate.  Instead, all those operations are performed by moving vertices around. That's all you really do in this tool...move vertices about.
    • Move shape: Click on a shape to select it. Drag on the body to move it around.  This moves all vertices together.  Note that all vertices always snap to the grid. 
    • Deformation: You can deform a primitive by moving its vertices in a 3D plane. Drag on the square surrounded a vertex to move it to a new grid point. 
    • Rotate: To rotate, move vertices one by one until the new shape looks rotated.  This is not true rotation since the snapping to the grid will not allow true rotation.   However, the result will look rotated and that is all that matters in art.  This works surprisingly well. 

    There are big limits on the shapes

    We could allow thousand of these objects on the screen.  But instead I'm inspired by the elegance of low resolution pixel art where beauty comes from working within limitations. 
    • All vertices are constrained to a 16x16 square grid.  This allows for easy selection of vertices and accurate adjoining of shapes. 
    • There are only 32 shapes in any one model.  This encourages the artist to create elegant compositions. 
    • Each shape is one of 16 colors in a fixed palette. 

    Shape Toolbar

    There are four basic shapes you can create with this method.  Click one of the primitive button on the toolbar and the shape is added to the scene.
    • Circle: 4 rounded vertices
    • Rectangle: 4 straight vertices
    • Half Circle: 3 vertices: 1 curved and 2 half curve / half straight
    • Triangle: 3 straight vertices 
    Example shapes that can be created by moving vertices about on grid

      One system for defining hidden control handles

      The follow is one method of getting the desired curves using bezier handles. Straight corners are a trivia case, but round and half round need to be tweaked to allow for aesthetically pleasing circular geometries.

      • For round corners, handles are defined only by adjacent vertices (vertex 2 and 3 are adjacent to 1)
      • Handles are parallel to the line segment ‘a’
      • Length of handle is proportionate to segment ‘a’  (Note that the .27 in the diagram is a value that results in 4 round corners arranged in a square yields a perfect circle.  There is likely a mathematical means of deriving this as well, but that is beyond me. :-) 

      • For half round, half corner points, calculating the normal based off the points adjacent to vertex 1 (in the picture above) results in a bowed out shape.
      • Instead, mirror point 2 across the line segment A. This creates a new ‘Fake A’ that goes in the correct direction.
      • The new curve handle for point 1 is now parallel and proportionate to ‘Fake A’

      What this toy lacks

      • 2D scale and Rotation: With such simple primitives that are easily rearranged, we don’t need these operations.
      • Full color picker: You can’t define arbitrary colors
      • Layers and grouping: With 32 shapes, a shape list is the layer list
      • Lines: There is only the shape color. Later on, we can have effects that apply to the object as a whole.
      • Empty shapes: Shapes always have a fill color.

      Extending to 3D

      To the left is the side view palette.  This is a bit like a layer palette in photoshop, but it also lets you control Z-depth.  This is a bit geeky and isn't my favorite part of the design, but worth trying.

      • Dragging on the body of the shape moves it left or right.  This is changing the depth of the object. 
      • Dragging on the left side of the shape extrude backwards. This snaps to the grid. 
      • Dragging on the right side extrudes forwards. This snaps to the grid. 
      • The profile of the shape shows its bevel. 

      Other shape Properties

      You can select a shape and edit its properties.
      • Color: Click a shape, click a color and the shape becomes that color.
      • Bevel:  Select the bevel for the object.  No bevel, rounded corners, dome, flat bevel
      • Extrusion:  Select how far you want the object to be extruded. 

      Open questions

      • Is this expressive enough?
      • Is there a better method of expressing the 3D extrusion?
      • How might it be simplified even further?

      Near Future

      The first part of the challenge is to get a basic editor up and running. For these new drawing tools you usually need to build it and then iterate on it 5 to 10 times so that the feel of the program is solid.

      Web-based editing, saving and viewing
      The model is editable in a browser window. You can save to a database and load. You can share the model with another user and they can make a copy of it and edit their own version.

      3D view
      Once you have a 3D view you can rotate the drawing plane to see the object from from various angles.  Some experiments to try:
      • The plane always snaps back to the frontal view when you release. 
      • Alternatively if you rotate the object 90 degrees, it snap to the side view and swap the side view for the front view in the other palette.  

      Export options

      • 3D model: Exports a static 3D model for import into something like Maya, 3DS or Unity. 
      • Bitmap: Export as a series of X (64?) images rotated around a center point. Includes Alpha

      Far future

      Shader sets
      Users can load in different shader sets as alternates to the base 16 colors. For example, there is a wood set that has different types and tones of wood. Or there is a metal set that has pitted bronze, steel and copper.

      Post processing and Lighting Presets
      You can apply a variety of preset post processing filters much like Instagram. Honestly this is where the magic occurs. The idea is that these are incredibly high quality professional filters that give your simple model a distinct style.
      • Outline: Add an outline to the image so that it looks like Land-a-panda. 
      • Pop art: Dot shading.
      • Sepia: Grainy, old timey image
      Define states for each model with each state have a different configuration of the 32 shapes.  For example, you could have a walk state and an attack state for a character.

      Now if you bundle these states into templates, you could provide users with a 'character template' that they can fill out to their heart's content to create a thousand unique characters that all 'work' the same.

      Animations between states
      Allow for tweening animations between states.  Add ease in and ease out for basic timing.


      This odd art toy is not a perfect tool.  Having made art for a few decades now, I'm not sure there is such at thing.  Instead it is series of constraints.  The theory is that these constraints will yield interesting art when placed in the hands of motivated artists.  We've seen this happen before.  Vector art is a style that emerged from the limits and strengths of printing technology.  Pixel art emerged from the constraints of early computer displays.  There is an exuberant creativity within carefully chosen walls. Is it possible to artificially foster that?

      Mostly I wanted to share these ideas.   For the folks that love an oddball project, this might be fun to play around with for a weekend or two.  It is certainly a way to learn about curves, 3D extrusions (and the exquisite pain of iterating on an artist-centric UI.)  I'd be delighted to give feedback and try out prototypes if any emerge.

      Long term if the basics works out, I could see making an entire professionally polished game in this art style with every single character, wall, door and tree built out of these shapes. This is the real test. Once you get artist trying their hardest to build real things with a new art tool, a feedback loop is born.  The artist asks for tiny yet critical features you could have never imagined.  After a few dozen iterations, the simple odd tool begins enabling amazing artists to create a certain kind of masterpiece.

      take care,


      In order to keep all the learning going on in one spot, here are the prototypes that folks have made so far and feedback to each:

      Pete Blois's Model Toy - Iteration 3

      This was the first prototype Pete and I iterated on and got the basic primitives working.

      Jeiel Aranal's Model Toy - Iteration 1

      This one was done in Unity and has manual control handles and some extrusion. Thoughts here:
      • Drag to move shape: The ability to click on a shape and drag it on the plane will make the tool much easier to use. (You can put rotate the view on right press or by dragging on the empty canvas.)
      • Auto-control handles: One of the neat things about the little 4 point vector objects is that the control handles are automated and not actually visible to the user. The intent is that every time you move a vertex, you look at the adjacent vertices and then calculate the length and orientation of the handles. This really simplifies the use of the tool since many users find manual control handles fiddly. (Though you did a good job putting them in!)
      • Hit region on handles: In the current build, the hit region is the circular vertex. If you use the rectangular region behind the vertex, it will be much easier to grab the vertex.
      • Mouse over: Outlining / highlighting the object on mouse over and showing the vertices makes it much clearer what you are about to manipulate.
      • Ctrl or Alt drag to duplicate: This is a classic short cut that makes it much easier to make complex objects.  Works when combined with 'Drag to move shape'. 
      • Slightly tilted drawing plane: A more complex tweak is to make the drawing plane tilted so that you are always drawing in 3D space. Since everything is still on a grid, it should be possible to still treat it as primarily a 2D drawing surface. This does require that the drawing plane be aligned with the face of each selected object.
      Mikko Mononen's Model Toy - Iteration 1

      • A lovely testbed for the 2D shapes.  It is clear that there is something off with the control handle behavior. 
      • Maybe adjust the control handles independently since currently they are completely symmetrical. Perhaps bisecting A in some manner may give a better value for each handle
      • The whole thing starts feeling much better if you can drag directly on the shapes themselves to move them around the 2D drawing plane.
      • Same thought as above on the tilted drawing plane. 

      Looking to hire unicorn programmer for Spry Fox
      Posted by Lost Garden [HTML][XML][PERM][FULL] on 17 May 2012, 6:53 pm

      Hi everyone -- my company Spry Fox is looking to hire a senior-level engineer/developer. If you are not this person but have worked with someone you love and trust, let me know!

      Job title
      We don't really do titles here. Feel free to call yourself something amusing and/or impressive.

      What we're looking for...
      • Senior level engineer (five to ten years of work experience, minimum.)
      • Can program both the front end and back end of an original online game - by themselves or as half a team of two
      • Has worked on multiple shipped games in the past
      • Very comfortable with frequent, rapid iteration (daily to weekly)
      • Excited about original, free to play games
      • Familiarity with Flash and Unity is a major plus but not a requirement. It's actually more important for whomever we hire to be flexible and not wedded to any given language, as we frequently find ourselves adjusting our tech to meet specific circumstances.
      • You must be a self-starter who can work effectively without being closely managed or prodded. This is a company for entrepreneurs, not worker bees.
      • Reliability and honesty are essential.  We love working with nice people. 
      • Location is not an issue; we all work remotely. But if you live in Seattle or the Bay Area, you'll get to have lunch with us pretty regularly. :-)
      About us
      Spry Fox is a successful developer of online games that have collectively reached over 30m people. Our titles include Steambirds, Triple Town, Realm of the Mad God and Panda Poet. We are passionate about two things: making great original games and bringing happiness to the world.  It is kind of a sweet gig.

      Send unicorn intros to

      take care,
      Danc and David

      Goodbye Realm of the Mad God
      Posted by Lost Garden [HTML][XML][PERM][FULL] on 19 June 2012, 12:45 am
      It is hard to let go of something you’ve worked on for such a long time, but such is life.

      After a rather successful launch of Realm of the Mad God on Steam and Kongregate, our partners at Wild Shadow Studios decided that the best course of action was to sell the game to a larger operator, and we agreed to sell our stake alongside them.

      Kabam will be operating the game from here on out and Willem Rosenthal, who has been designing the new dungeons and loot in RotMG for several months now, will stay on board to guide the project going forward.


      RotMG will always be a special game for David and I. Alex Carobus is one of the most talented programmers we’ve ever had the pleasure to work with, and the game itself pushed the boundaries of what an MMO could be. When we started out, RotMG had the bare bones of a multiplayer bullet hell shooter. The foundations of the game were fascinating: coop only, permadeath, procedurally generated worlds, and retro 8-bit art. It had such promise, but it was on track to end up as just another interesting game jam prototype.


      Over the course of 2+ years, we worked with Alex to turn RotMG into a full-fledged MMO with more meaningful cooperation, a trading system, guilds, a compelling advancement system and community full of passionate players. We measured fun, retention and monetization and steadily increased all of them. At this point, millions of people have played a game that at first glance appears to be a niche hobby project.

      I'm particularly proud of how monetization turned out in RotMG. The game is completely free-to-play, but it is not a pay-to-win game. Skill matters (much more so than in many other games) and the items we offer for sale for hard currency never imbalance the game. In fact, some purchases (such as dungeon keys) are highly social purchases that can benefit free players as much as they do the original buyer.

      If you are interested in learning more about how RotMG evolved, David gave a lecture at GDC that you can watch for free at:

      We wish the best of luck to Kabam as it proceeds to make the most of a very special game. And to the RotMG community: we want you to know how grateful we are for the years of support and encouragement you gave us. We appreciate how hard you pushed us to be better at our craft, and how warmly and generously you treated us when we weren’t screwing things up. ;-)

      We wish we could have continued to grow RotMG alongside you, but we know we’re leaving you in good hands. In the meantime, we’re going to keep cranking away on a couple of new online games that we’ve been quietly developing for the past year or so. We can’t wait to share 'em with you!

      -'Chedd' and 'SpryFox' signing off from Realm of the Mad God.

      Building Tight Game Systems of Cause and Effect
      Posted by Lost Garden [HTML][XML][PERM][FULL] on 1 July 2012, 5:33 pm

      To play a game well, a player must master a mental model of cause and effect.  You learn that pressing a specific button moves you forward.  You figure out that a sequence of controller moves lets you dodge a fired rocket.  You observe a slight pause before an enemy attack and theorize that you could fire off a headshot at that exact moment.  At each stage of learning, you create a hypothesis, test it via your actions and refine your mental models of the whirring black box at the heart of the game.

      This escalating refinement and mastery of new mental models and tools is essential to what makes many a game enjoyable. Such mastery obviously depends on the player.  Yet it also is dependent on the designer and the systems they build.  You can accidentally create a broken black box. 

      Not all systems are readily amenable to the intuitive formation of models of cause and effect. As a game designer, it is your job to create systems that are intriguing to master without being completely baffling. If the system is too predictable, it becomes boring. If it is not predictable at all we assume that the system is either random or spiritual in nature. Both of these are failure conditions if you are attempting to encourage mastery.

      Tight and Loose systems

      I am a mechanic who fixes broken black boxes. One importance concept that has served me well is to think of the relationship between systems and the feedback the game uses to describe interactions with the systems as either ‘tight’ or ‘loose’. A tight system has clearly defined cause and effect. A loose system make is more difficult to distinguish cause and effect relationships.

      There is no correct ‘tightness’ of a loop. However there are clear methods of increasing either the tightness or the looseness.

      Techniques for adjusting tightness

      For your reading pleasure, I've put together a list of tools that I use to tweak a system's tightness.  Not all are applicable to any given system but all of them should be part of an expert designer's toolkit.  Some of the tools are worthy of dedicated books so I apologize up front for any obvious shallowness.  For example, probability has so many subtle flavors that some designers devote their lives to studying how it impacts a player's ability to predict outcomes.  At best this is an overview.

      To tighten a system, I'm making the cause and effect more obvious.  To loosen a system, I'm making the connection between cause and effect less obvious.

      Strength of Feedback

      Tighter: Multiple channels of aligned feedback such as color, animation, sound, and touch that reinforce one another.  The classic example is Peggle which uses particles, rainbows, Ode to Joy and time dilation to let you know that yes, the match is over and glorious points are being scored.
      • Am I using all the potential channels I need to make an impact?
      • Is the feedback sequenced correctly so that player can read it clearly?
      • Does the feedback leverage an existing mental schema so that becomes more impactful?
      Looser: One channel of feedback that is weakly evident.  In multiplayer FPS games often the only sense that you have that another player is near comes from the faint patter of their footsteps.   Expert players gain immense satisfaction from being able to predict the location of their opponent by combining knowledge of the levels with tiny hints of where they might be. 
      • Does the feedback have nuance that is not readily understandable upon casual inspection?
      • Can the feedback be combined with other non-obvious information to give a clear picture to an expert user?
      Space Giraffe

      Tighter: A clear signal of effect that is related to the cause.
      • What is the most important piece of information the player needs right now?
      • Have I removed extraneous elements that distract the player's attention?
      • Is my feedback at the center of the player's attention? 
      Looser: A multiplicity of conflicting, attention sapping signals, which are not related to cause. One of the critical skills in Jeff Minter’s Space Giraffe is learning to see through the visual noise of the psychedelic backgrounds.
      • Are there ambient elements I can add that distract, but don't annoy?
      • Can noise create a perceptual puzzle for the player?
      Sensory type
      Assassin's Creed 3:  Nice use of contrast and perspective

      Tighter: Visually or tactile feedback is often more clearly perceived.  Consider the many billions of dollars spent on improving visual feedback each year so that we can demonstrate the visceral impact of a players bullet on simulated flesh with ever greater fidelity.  Tight visual feedback is highly functional; it communicates the effect to the player in an elegant efficient fashion.  It is not just about making pretty pictures. In a recent update of Triple Town, we changed the color scheme so that the background was the same general value as the foreground objects.  The result was attractive, but players were pissed because the icons weren't nearly as visible as before.
      • Am I using good visual design such as color, motion, contrast, line, white space, shadow, volume, perspective so that my visuals read clearly?
      • Did I make something pretty when I needed something functional?
      • What feedback is functional and what is evocative or aesthetic?
      • Am I over investing in visual feedback?
      Looser: Auditory and smell are less clearly perceived.  Not as much has been done here, but due to the looseness that come such systems it would seem that there are potential systems of mastery.  It is perhaps ironic that most music games, a topic typically associated with auditory mastery, can be played with the sound turned off. 

      Tapping Existing Mental Models
      Plants vs Zombies

      Tighter: Closely map the theme, feedback and system to existing mental models.  Due to decades of exposure to pop culture, players know how zombies move and that they should be avoided.  One means of quickly communicating the dozens of variables in a particular slow moving group of monsters is to label them 'zombies'.

      • What is the cartoon model that players have in their heads (vs the 'realistic model of how the real world works)?
      • Does my theme support my mechanics?
      • Does my theme inspire useful variations on my core mechanics?
      • Am I engaging in the cardinal sin of watering down my mechanics to fit the theme?

      Looser: Step away from existing models and introduce the player to new systems that they've never experienced.  Consider the metaphors involved in Tetris.  Falling elements are something our brain can process as reasonably familiar.  Tetriminos that you fit into lines that disappear to earn points while Russian music plays?  That doesn't fit any known metaphor that I know, yet it results in a great game.

      • At what point do I no longer need a gateway schema and the game can stand on its own internal consistency?
      • Are there opportunities for surrealism or intentional disorientation?
      • Can we step away from cliches to synthesis fresh experiences?

      Advance Wars:  Limited units and small numbers. 

      Tighter: Discrete states or low value numbers. Binary is the tightest. For example, recently we were playing with units moving a various speeds.  By making them move a 1, 2, and 4 tiles/sec, it suddenly became very obvious to the player how each unit type was distinct.  This is one of my favorite techniques for getting unruly systems under control. 
      • What is the minimum number of values that I need to create meaningful choices?
      • Can player clearly distinguish between the effect of each increment in value?
      • What would happen if I had to reduce this variable to 3 discrete values?
      Looser: Analogue values or very high value numbers. For example, in Angry Birds, you can give your bird a wide range of angles and velocities.  This makes the results surprisingly uncertain.  Think of how predictable (and boring) the game would be if you could only pick 2 distinct angles and velocities. 
      • Do I have enough range that players can play creatively?
      • Do my values add interesting uncertainty to choices?
      Diablo Loot Pacing

      Tighter: Short time lapses between cause and effect.  When creating mouse over boxes like you find in Diablo, a common mistake is to add a delay between when the mouse is over the inventory item and when the hover dialog appears. If the delay is too short, the hover dialog pops up when the player doesn't expect it.  If the delay is too long, the dialog feels laggy and non-responsive. (In my experience, 200ms seems ideal.  That's right inside the perception gap where you've decided to do something, but your conscious mind hasn't quite caught up) 
      • Where does the game play lag?
      • What happens if I speed timing up? 
      • What happens if slow timing down?
      • What systems allow me to vary timing in an indirect fashion?
      • Am I adjusting pacing using manual content arcs when I could instead use with algorithmic loops?
      Looser: Long time lapses between cause and effect. Too long and the player misses that there is an effect at all. Imagine an RPG where you have a switch and a timer.  If you hit the switch, a door opens 60 seconds later.  Surprisingly few people will figure out that the door is linked to the switch.  On the other hand, early investment in industry in Alpha Centauri resulted in alien attacks deep in the end game.  This created a richer system of interesting trade off for players to manipulate over a long time span. 
      • What are the longer loops in the game?
      • Are there long burning effects that cause players to reconsider their models for long term play loops? 
      Castlevania Medusa movement (via Kotaku) 

      Tighter: Linearly increasing variables are more predictable. Consider the general friendliness of throwing a sword in a straight line in Zelda versus catching an enemy with an arcing boomerang while moving.
      • What happen if I simplify the model and make the reaction linear?
      • How can I remove non-linear systems from early gameplay?
      Looser: Non-linearly increasing variables, less so. The Medusa heads in Castlevania pose a surprisingly difficult challenge to many players because tracking them breaks the typical expectation linear movement.  Even something as commonplace as gravity throws most people off their game.  After all, it took thousands of years before we figured out how to accurately land an artillery shell. 
      • What systems are exponential in nature?
      • How do I constrain my non-linear systems so they are predictable?
      • How do I create interestingly chaotic behavior via feedback loops?

      Tighter: Primary effects where the cause is directly related to the effect. In Zelda again, the primary attack is highly direct. You press a button, the sword swings out and a nearby enemy is hit. 
      • What systems can I remove to make the results of an action more obvious?
      • Is my cognitive load high enough?
      Looser: Secondary effects where the cause triggers a secondary (or tertiary) system that in turn triggers an effect. Simulations and AI's are notorious for rapidly become indecipherable due to numerous levels of indirection.   In a game of SimEarth, it was often possible to noodle with variables and have little idea what was actually happening.  However, the immense indirection yields systems that people can play with for decades. 
      • How can simple system interact to create useful indirect effects? 
      • How can I layer useful indirect effects to create wide expressive opportunities for the player?
      Hidden information 


      Tighter: Visible sequences that are readily apparent.  For example, in Triple Town we signal that a current position is a match.  The game isn't about matching patterns so instead the design goal is to make the available movement opportunities as obvious as possible. 
      • Is there something hidden that shouldn't be?
      • Is there something visible that doesn't matter?
      Looser: Hidden information or off screen information. A game like Mastermind is entirely about a hidden code that must be carefully deciphered via indirect clues.   Board games that are converted into computer games often accidentally hide information.  In a board game, the systems are impossible to hide because they are manually executed by the players.  However, in computers the rules are often simulated in the background, turning a previously comprehensible system into mysterious gibberish. 
      • Would hiding information fully or partially make mastery more challenging?

      Tighter: Deterministic where the same effect always follows a specific cause. In a game like chess, the result of a move is always the same; a knight moves in an L and will capture the piece in lands upon. You can imagine a variant where instead you role a die to determine the winner. You can make that tighter again by constraining the probability so that certain characters roll larger dice than others. The 1d20 Pawn of Doom is a grand horror.
      • How do I make the outcome highly deterministic?
      • Is this direct action still interesting if repeated hundreds of times?
      Looser: Probabilistic so that sometimes one outcome occurs but occasionally a different one happens. In one prototype I worked on there was both a long time scale between the action and the results as well as a heavily weighted but still semi-random outcome. Players were convinced that the game was completely random and had zero logic. If you pacing is fast enough and your feedback strong enough, you might be able to treat this as a slot machine.
      • Do I need a simple method of simulating a complex system?
      • Do I need a means of adding interesting pacing to the game?
      • Does the player perceive that they have the situation under controls despite the randomness?
      Processing Complexity

      Tighter: System requires simulating few steps to predict an outcome.  In a vertically scrolling shooter, you see the bullet coming towards you.  It doesn't take a lot of thought to figure out that if you stay in that location you are going to be hit.
      • How much can the player process in the time allotted?
      • Are players getting mentally fatigued playing the game?
      Looser: System requires simulating multiple steps to predict an outcome.  On the other hand, in Triple Town, good players need to think dozens of moves ahead.  Thinking through all the various machinations necessary to get the result you want adds a serious cognitive load to the player.  A single mistake in the player's calculations yields unexpected results.
      • Do players feel smart?
      • Can players plan multiple moves ahead?
      • Can players debug why their plans didn't work?
      Option Complexity
      Steel Battalion

      Tighter: Fewer options are available to consider. In a recent upgrade system I was building I give players 3 choices for their upgrades.  I could have given them a menu of 60 upgrades, but that would be rather overwhelming.  By focusing the user on a few important choices, I give them the mental space to think about each and pick the one with the biggest impact.
      • Can I reduce the options?  
      • If I had to remove one choice, what would it be? Would the game be better?
      • Which options are the most meaningful?
      Looser: A large number of options must be considered.  In a game of Go there are often dozens of potential moves and hundreds of secondary moves.  This options complexity is a large part of why the game has been played for thousands of years. 
      • How do current options yield an exploding horizon of future options?
      • How do I re-balance outcomes to make more options useful?
      Social Complexity
      Death of Lord British in Ultima Online

      Tighter: Another human broadly signals intent, capabilities and internal mental state.  In an MMO, a player dresses as a high level healer and stands in a spot where adhoc groups meet up. There's a good chance you know what they'll do if you ask them to go adventuring together.  Or in a managed trade window, you know exactly what you are getting when he puts up a potion for your sword.  There is little ambiguity.
      • Can I make a character automatically signal future intent via their current actions?
      • Do the options collapse to a reasonable number so that I can predict what the other player might do if they are acting rationally?
      • Do I know enough about the goals and resources of the other player?
      • Have a spent enough time with the other player to model their internal state?
      • Are there predictable methods of interacting between players?
      Looser: Another human disguises, distorts or mutes intent, capabilities and their mental state.  
      • Can people communicate?
      • Can people lie and what is the impact of that?
      • Can people harm others? Can they help? Are there repercussions?
      • To what degree is my choice dependent on another player's choice?
      • What are group dynamics that influence behavior?
      Time Pressure

      Tighter: Requires simulating the model at the player’s preferred pace.  This is related to processing and option complexity since players can only execute their models at a given pace.  Players are more likely to make causal connections if the time pressure is greatly reduced.   For example, the game NetHack has complexly interwoven systems that require real detective work to decipher.  In order to increase the likelihood that players will make the connection, the game is set up as a turn-based game where players may take as much time as they want between turns.  You'll see that as the situation becomes more complex, even good players will slow down their play substantially so they can understand all the ramifications.
      • How much time does the player need to understand what is happening?
      • Can I let the player choose their pacing or do I need to force a universal timing?
      • What are the multiplayer ramifications?
      Looser: Requires simulating the model quickly.  In a game of WarioWare, there isn't really much complexity involved in each individual puzzle.  However, we can dramatically ramp up the cognitive load and increase outcome uncertainty by setting a very short timer. 
      • Would time pressure push the player's cognitive load into a pleasurable flow zone?
      • Is the player feeling analysis paralysis?
      • Is the player feeling wildly out of control?

      Applying the tightening techniques

      When I run into the common situation where players don't understand the system, I often use the tightening techniques to make the system's cause and effect relationship more crisply defined for the player.  In almost all cases, my changes are in response to observations stemming from playing a prototype myself or from watching someone else play a prototype.   I find them to be most useful as tuning techniques and less reliable for making grand plans in the absence of functional code.

      Gameplay is composed of loops and these loops have distinct stages (Actions, Rules, Feedback, Updating of the player's mental model).  Depending on where in the loop the observed issue might be, I use different techniques to tweak it.

      Action Problems
      • Option complexity
      • Pacing
      Rules Problems
      • Processing complexity
      • Probability
      • Indirection
      • Linearity
      Feedback Problems:  Feedback failures are the most common error I find when dealing when implementing known systems. Most new designer make feedback errors.  Intermediate designs often focus on feedback to the exclusion of other problem areas. 
      • Strength of feedback
      • Noisiness
      • Sensory Type
      • Hidden information
      • Discreteness
      Modeling Problems:  
      • Time pressure
      • Tapping existing mental models

      Tightness vs the stage of player mastery

      Skill loops build upon one another.  The jumping in Mario evolves into advanced platform navigating skills. What I find is that often the lowest levels of skill loops need to be the tightest. These are the systems you need to be most obvious in the first seconds of play...they are the gateway into the rest of the game, so to speak.  Keep the number of options low, tap into existing mental models and make the cause and effect as crisp and obvious as possible.  Then once the player is comfortable manipulating the basic system, you can introduce looser connections that take more effort to master.

      The player's perception of tightness and looseness changes over time. There's a mental chunking operation that occurs as we master skills. Sequences that were once confusing and complex get reduced down to easily repeated and manipulated patterns. So the higher level skills that are made of multiple chunked precursor skills end up feeling very clear and obvious. You'll often find controls that a new player describes as twitchy or sloppy are described by an expert player as extremely precise and tight. Mastery can turn loose systems into tight tools.


      New designers often treat the systems at the heart of their games as inviolate features of nature.  The properties of a sniper rifle, the combo system in Street Fighter or the energy system in a farming game are treated as mathematical facts.  You can tweak some values, but the basic system has always existed and will always exist.  Yet the truth is that these systems were invented and then adopted because they had useful properties.  They are easy to pickup, yet provide sufficient depth for long term mastery.  They are designed artifacts.

      We can design new systems that hit the sweet spot between mysterious and boring.  By looking at your new games through the lenses listed above (and likely some others that I'm forgetting) you can iteratively tune the systems, models and skills at the heart of your game to be more or less understandable. By following a methodical process of invention, you can take a weak game and turn it into a great game that dances hand-in-hand with player capabilities.

      take care,

      Understanding randomness in terms of mastery
      Posted by Lost Garden [HTML][XML][PERM][FULL] on 31 December 2012, 3:43 pm

      Instead of categorizing games as either 'games of skill' or 'games of luck', I see games with randomness as being a subset of 'games of mastery'. This view helps the designer see randomness in games as the intersection between both the player skill set and the game mechanics. By understanding the underlying skills involved in mastering randomness, we can build more meaningful games.

      Discerning cause and effect from noise

      One of the fundamental elements of any game is how the player learns to distinguish useful patterns from environmental noise. Without a mental model of how a system works, most games appear random or at least arbitrary.  (Randomness is a concrete property of a rule set. However perception of randomness is a state of mind that can exist independent of the rule set.)

      With time, experimentation and practice, some players build up a mental model with conceptual tools that let them manipulate the system to reach desired outcomes. They transform from unskilled players into skilled players.

      The idea of noise is a broad one. A cluttered scene with hundreds of objects is said to be noisy. A combat scene rife with particle effects and crazed camera angles also is noisy. Noise is the extra stimuli that hides the next conceptual insight.

      The perception of noise vary based off the player's skill in understanding and filtering various classes of noise. A chess board in the middle of a game is highly noisy to a new player trying to simply figure out how a knight moves. All the extra pieces and their subsequent movements are extraneous to what the player needs to learn next. However, that same chess board offers reams of insight to the advanced player. They are able to process the information and predict future outcomes based off their sophisticated cumulative models of chess cause and effect dynamics.

      Categories of noise
      Noise comes in a variety of categories that flow naturally from the basic skill atom we see in most game loops.

      • Action Noise:  Uncertainty, extraneous elements or unmastered complexity in the player action. 
      • Rules Noise: Uncertainty, extraneous elements or unmastered complexity in the processing of the blackbox rules. 
      • Feedback Noise: Uncertainty, extraneous elements or unmastered complexity in the stimuli that shows the effect of the player's action. 
      • Model noise: Uncertainty, extraneous elements or unmastered complexity in the player model of the situation. 
      Each class of noise has its own category of skills associated with filtering the meaningful signal. In a hidden object game, the visual complexity of the scene creates noise. Advanced players cope with this by mastering silhouette detection, efficient visual search patterns and object association skills. A good hidden object game players is measurably better than a new player.

      Randomness as a form of noise

      From this viewpoint, randomness in the form of internal dice rolls can also be treated as a class of rules noise. There other forms of randomness that map onto Action Noise and Feedback Noise, but randomness as rules noise seems to cause people the most trouble.

      Since randomness is just another form of nosie, we can expect it to have several key properties:
      • A model: There is often an underlying pattern or model that helps players deal with the randomness
      • Model ignorance: This model will not be readily apparent to new players. 
      • Learning curve: With time and education, players will learn how to appropriately deal with randomness. 
      • Learning variables:  There are also likely important variable for the system that make learning to deal with a system's randomness easier or more difficult. 

      Skills for player modeling of randomness

      Probability and statistics provides use with a set of mathematical skills for dealing with randomness.  Players instinctually use roughly equivalent concepts but modified by a set of well document unconscious biases.  Instead of summarizing all of probability theory, let's cover the symptomatic player behaviors you'll see in the field. 

      Existing heuristics
      When a player lacks a mental model for a phenomena, their immediate instinct is to adapt an existing model. They look for past experiences and skills that fit the current situation and then act accordingly. Players can pick from their personal experiences or they may use forms of social proof to follow what others are doing.

      There is strong evidence that many of our default heuristics for dealing with randomness are instinctual and perhaps biological. As such, evolution selected for survival, not necessarily accuracy. This leads to a wide array of biases such as loss aversion or difficulty processing large odds.

      In general, reliance on existing models is a poor method of dealing skillfully with random behavior. It is better than a purely random reaction in a pinch but is not well adapted to the engineered random systems players face in modern designs. The player can't know the properties of the random system beforehand and the wide range of different types of randomness mean that they will likely guess incorrectly.

      Perhaps the most confusing aspect of randomness it that it occurs as a result of an interaction loop. In a simple slot machine, you pull the handle once and get a single result. By its very nature, it is difficult or impossible to detect what that result might be.

      So the first skill players acquire is the ability to take multiple samples of the event. For very rare events, you may need to take large numbers of samples. For common, more predictable events, you may need to sample it less often.

      Sampling is a general skill that is useful for both complex, yet entirely deterministic systems and for systems with high amounts of pure randomness. Humans observe the vast universe through a tiny straw. Only by repeated and methodical exposure can we build up a more comprehensive image of what exists.

      Cost of sampling
      Sampling almost always has a cost. Here we see one of the more interesting economic decisions at the heart of random systems: Will the expense of sampling further result in enough improved understanding that I can then leverage in the future for outsize gains?

      Averages and Variability
      With large enough samples, most random systems become predictable. They tend towards an average with some variability around that average. Thus with enough sampling, the next skill that players learn is getting a feel for the 'typical result' and the likelihood of an 'atypical' result.

      Advanced players of Triple Town see luck as a very minor component of the game. As you plan out 30 or 40 moves into the future, you learn that there is a very good chance that you'll get a bush or bear within your window of control. You don't know the order, but there are tools for mitigating out of sequence drops. The learned mental map of average drop rates becomes a tool to be applied skillfully.

      Types of distributions
      Often the player sees a variety of different types of distribution. The normal curve, multi-modal or exponential distributions are most common. Advanced players get a sense of the distribution. What will outcome is most common? What outcome is least common?

      All actions in games have payouts. Sometimes they are explicit such as a pawn capturing a rook and removing it from the board. Sometimes they are implicit such as a gift to a player that may in the future be reciprocated.

      Through sampling, understanding averages, and understanding distributions, players gain a sense of the value of the payouts. In a sequence of player initiated causes and effects, how useful are the effects?

      Expert players weigh these benefits against the costs reaching that average outcome.

      New player mistakes due to model ignorance

      There are numerous and well documented mistakes that the naive player makes when dealing with systems of randomness. With training, many such players can overcome these. Some will not. Placing an inexperienced driver in the middle of a professional NASCAR race will likely end in physical harm. Even with training, a certain population will never become competitive drivers.

      Reliance on non-evidence based models
      Players use existing models without considering the evidence. For example, it is common to assume that because 1D6 results in an even distribution of values, 2D6 will also result in an even distribution.

      Not enough samples
      Players don't sample enough instances of the game to understand the typical outcomes.

      Low quality sampling
      Players sample, but don't actively look for patterns. Without consciously making observations and testing those observations against future results, critical signals are often ignored. Many players will perform actions, faintly register the results but never ask 'why'.

      Poor cost / benefit analysis
      During the learning stages of a game, players typically over invest in learning activities, beyond what is strictly necessary to accomplish the desired result. This is seen as 'play' or 'practice' depending on how experimental the routine ends up being.

      However, it is common for new players to invest huge amount of resources in activities with very little future pay off. They engage in 'play' behavior (not a consciously forward looking act) and find themselves never recouping. They misjudge when hold them, when to fold them or for that matter, when to walk away.

      Balancing for skill in games of luck

      Like any game of mastery, we have concepts of balance and progression in games of luck. Typical balancing techniques work

      Dominant strategies
      Is there an average outcome that is preferable? This is tricky to ascertain since you can still have a balanced random system where a single sampled event yield a rare outcome. When new players see this, they will scream at the top of their lungs that something is overpowered. With a reasonable understanding of combinatorics, you can guarantee that such events are interesting outliers. You can also gather metrics over a large population of games and verify that the 'game breaking outcomes' are in fact rare circumstance.

      Is there any benefit to even having these outliers? I think so. They certainly add a strong emotional drama to the game that would otherwise be missing. Also players are kept on their toes and must plan for blackswan events as much as the average events. That's an interesting decision.

      In Triple Town, the players that come back from a scenario with 5 ninja bears dominating their game end up being better players because of the experience. If that random outcome hadn't occurred, they would never have been pushed to take their tactical skills to the next level.

      Does the game structure allow for multiple samples?
      A single hand of poker is deeply imbalanced since it is prone to highly variable random outcomes. However, during a poker night or tournament, players churn through dozens of hands. This allows players to take multiple samples and use their knowledge of the game's random distributions to gain material advantages over weaker players. Thus, the right number of samples results in a more balanced game full of meaningful decisions.

      Progression considerations in games of luck

      You can use the following learning variables to create a progression system to help teach new players the subtleties of a random system. 

      Can new players learn foundational rules with a small number of samples? If you start players off with a random system that takes dozen or hundreds of sample to understand, they may quite before they accumulate enough experience. Instead, use system at are reasonably easy to figure out. In Triple Town, players get grass the vast majority of the time. This helps them learn how to build up more complex structures since they learn very quickly that there's a good chance that the next object is going to be grass.

      Existing schema
      Is there a known random system you can mimic in order to tie into existing heuristics? For example, many games use a 6-sided die since that is a model of randomness that many players have been using since childhood.

      Use of random systems that reveal structure upon inspection
      One of my favorite techniques is to pull random outcomes from a fixed pool. Thus the expert players learn what they are going to get, but not in the order they are going to get it. This is the basis of all card games that disallow reshuffling.

      You've got two key variables you can tweak for progression escalation:
      1. When the pool is small, players tend to learn it quickly. By increasing the size of the pool, you require additional mastery.
      2. Randomness without replacement ends up being reasonably predictable when sampled across the size of the fixed pool. So if your sample count is higher than the pool size, players will learn the pool quickly. If the sample count is less than the pool size, they'll learn it slowly (or never)

      Black hat techniques

      There are also cynical techniques that will result in players never learning the system. There are entire gambling journals dedicated to these methods since the number of human randomness hacks are quite large.

      • Obscuring average results through high variability and high sample requirements.
      • Use of artificial close calls so new players see patterns were there are none. There is a measurable sub-segment of players that process near misses as wins. These games prey on people who are essentially dyscadentic, or the random equivalent of dyslexic.
      • Use of social signals so players approach the game with a costly mindset.
      • Obfuscated odds combined with a high cost of playing.
      • Use of high odds that players don't process well. At a certain point the brain says 'many' and doesn't quite grasp that there is a good chance the universe may expire first.


      A well rounded designer does not remove randomness from their games. The world is a random place and learning to deal rationally with randomness is a critical life skill. Instead, they embrace the fact that players can learn to understand and master the game's random systems.

      It is your responsibility as the designer of random systems to facilitate masterful play. Put new players through a progression where you teach them the system's average results, outliers and distributions. Give them tools for managing and mitigating randomness. Create expert game modes where players roll the dice enough to manipulate the big picture.

      When you use randomness as an opportunity for mastery over noise, I think you'll find that games of luck become highly meaningful games of skill.

      take care


      Psychology of near misses

      Gambling addiction as a learning disability

      Coercive Pay-2-Play Techniques
      Posted by Lost Garden [HTML][XML][PERM][FULL] on 18 July 2013, 2:13 am

      Coercive monetization models are used by many of the large corporations that dominate the "Pay to play" (P2P) charts in retail, console and mobile.

      They employ carefully engineered psychological traps intended to defraud ignorant players of their money. This shocking expose shines a light on their dark, inhumane practices. Be forewarned: Despite extensive examinations of opinions similar to my own, I am intentionally unaware of any company that manages to use these systems of coercion in a positive manner.

      1. Purchasing sight unseen

      The primary method is to get a player to purchase something without ever playing it. If you can get players excited about a new game, most will buy it with little more to go on than a box shot and a video. Many secondary techniques tie into this basic strategy of deceit.

      Companies intentionally avoid releasing demos or providing free trials in order to increase the number of purchases independent of whether or not a player might enjoy the actual game.

      2. Use of propaganda to artificially increase excitement

      P2P publishers feed players videos, paid end caps, advertisements and canned previews. Often the marketing spend for a title is greater than the development budget. It is cynically assumed that if you shout targeted propaganda at an audience, they will buy in increased numbers.

      3. Limiting information to prevent alternate opinions

      Since no one can play the game, the publishers are able to keep any information about the game tightly focused on the most effective message that drives purchases. Heavy use of the captive fan press ensures that press releases are repeated verbatim.

      4. Distorted game design

      Since all that matters in order to make the sale is the initial propaganda, the actual game design is sacrificed. You make money by having a catchy theme, pretty graphics and the ability to turn out short sequential games rapidly. As a result, P2P encourages developers to short, consumable interactive sequences with shallow, low risk, well-worn mechanics. I hesitate to call them "games". Most are little more than a collection of puzzles or QTE that can be clicked through in 5 to 10 hours.

      Also because all that matters is if someone buys the box, game designers need not worry much about retention or engagement. Most P2P games are built with little care given to the final few levels. It is common that 50-70% of players never complete a P2P game.

      5. Targeting those least able to understand modern sales techniques

      Though it might be a stereotype, most P2P titles target poorly socialized teenage males. Unlike women, an educated demographic that makes the majority of purchasing decisions in Western markets, these younger males are likely to naively buy into the pre-sales propaganda without critically questioning its actual purpose. Now if these were shopping savvy 40-50 year old women, you might be willing to say "Let the buyer beware", but can we really expect an audience that has difficulty buying fresh boxers on a regular basis to purchase games responsibly?

      6. Bundling and time-limited sales

      One of the more effective methods of psychological manipulation is to bundle multiple products together and offer them at an apparent discount. Players perceive they are getting a massive value when in fact they are just accumulating more games that they are unlikely to play or even enjoy.

      This also preys upon those damaged individuals that possess strong hoarding inclinations. How many times have you seen players with vast collections of hundreds of uncompleted games? This is an obvious sign of mental illness which P2P developers are all too willing to exploit.

      7. Skinner Boxes

      Players end up treating game purchases like a slot machine. They may buy dozens of games in a year, but only one or two will be worth their time. This creates a random reinforcement schedule that sets up a form of psychological addiction. Players find themselves stalking the latest game sale in the hopes of getting a new hit of gaming goodness. Of course the system is rigged so that it is nearly impossible to know upfront whether the game in question is worth their money. So they press the 'buy game button' and spin the wheel. Oh, the Steam sales!

      In the process a few 'whales' spend hundreds or even thousands of dollars a month on games. Some even purchase meaningless, ostentatious 'arcade cabinets' or inordinately expensive peripherals that retail dealers call 'consoles'. Most of these claim their purchases are part of a healthy hobby and have no regrets. However, I've gone out of my way to find adults with poor spending habits that have stripped their meager bank accounts to 'collect 'em all'. Some young men holding down minimum wage part time jobs were forced to eat ramen in order to continue their spending spree. This deceptive form of capitalist gambling, aka 'shopping', ruins ruined lives.

      Other means of manipulation

      This small sampling of techniques points to the deep corruption inherent in both making and selling P2P games. There are numerous other other manipulative practices:
      1. Use of fake tribalism: "Genesis does what Nintendon't"
      2. Collector's editions: Use of socially questionable materialism to artificially increase ARPU.
      3. DRM: The pay before you play model leads directly to DRM as a means of artificially blocking non-paying users from trying the game and seeing if they might like it. Piracy becomes meaningless if you provide a long term service or hobby, but that is not the optimal strategy for money-grabbing P2P firms.
      4. $60 price tags: If you are selling a fantasy product, you might as well take any willing mark for as much as possible.
      5. False console cycles: With a mere billion dollars on fresh propaganda, P2P companies know that they can artificially stimulate a mass of people to invest in a new console and then repurchase their old games all over again.
      6. DLC: Since P2P is essentially about churning out cheap, consumable content, these "games" only get upgraded if the expansions take the form of cheesy modular DLC. Mechanical upgrades that improve the core gameplay or social systems are rare since there is little financial incentive.
      7. Overemphasis of reviews instead of actual player behavior: Good reviews are just another form of message control and propaganda. This is why dev bonuses are tied to Metacritic scores instead of statistically valid player metrics.
      There is a substantial human cost to these shenanigans. Through I have zero hands-on experience making P2P games (and honestly have no interest in them), several inexperienced indie friends attempted to make a P2P game. After one attempt in a crowded and competitive market, they failed to buy a Tesla. Since I personally enjoyed the prototype they showed me at a game jam, I think it is clear that all the blame for their game's failure (and subsequent public emotional turmoil) can be laid at the feet of the P2P business model. This is not the silver bullet you fantasized about as an inexperienced non-developer.

      In closing

      In the end, P2P hurts gamers and the game industry as a whole. I urge you as an ethical designer to reject this immoral practice. The egregious abuse of players by popular pay-2-play practitioners makes any use of P2P invalid. I question if it is even possible to make a moral P2P title. (Indies should especially distance themselves from this culture that is little better than legalized gambling.)

      What we really need is to make great games where players can try the games for free and then make an informed decision on whether or not the game is worth their money. In an ideal world, games should be meaningful long term hobbies that enrich a player's life, not some cynical scam job reliant on engineered propaganda spam, sexed up artwork, forced sequels and a captive press.

      Imagine games where players only pay their hard earned cash if they find the gameplay meaningful. They can try any and all of a game for free as long as they want. If they don't feel the game is adding to their life, then they can leave at any time.

      Sadly, such an honorable course seems unlikely. No doubt that we'd see overblown rhetoric and misappropriated science denouncing such an idealistic experiment by those deeply involved in coercive, yet highly profitable, P2P businesses.

      Yours truly,
      Monsieur Troll

      PS: When posting comments be sure to see if it passes the "I understand that this essay is satire" check. I'd hate for there to be any sort of embarrassing misunderstandings.

      PPS: These are exciting times where business models and design problems are evolving radically and rapidly every month.  That multiverse some call 'free to play' is mutating along dozens of different variables. The old familiar retail 'pay to play' model is also fracturing into something new.  If you think you grok how any current business model works, you probably are several years behind.

      The uncertainty and change can be scary. Maybe you recently played a game that was different than ones you played as a child. Or you heard some stories. And now you feel the urge to express your emotions via loud opinion spewed onto the internet. Oh look...more precious time passed while you were ranting and you learned nothing. 

      Polarized views backed by mere opinions fails to move the science and craft (and ethics) of making games forward. What are you personally doing with code and art and functional gameplay in order to carve out a viable, sustainable future for great games? Let's talk about that.  Mere gnashing of teeth, often witnessed in the same form as the essay above, is noise that drowns out thought. 

      A single game as a lifelong hobby
      Posted by Lost Garden [HTML][XML][PERM][FULL] on 21 July 2013, 1:21 am

      Do you finish one game and then move onto the next? This is the dominant pattern of play for gamers. What happens when players stop consuming and starts investing in a single evergreen computer game for years on end?

      Players of traditional games specialize

      Across the 5500+ year history of gaming and sports, players typically focus on a single game and turn it into their predominant hobby. A chess player may dabble in other games, but chess is their touchstone. They join chess clubs, they play with fellow chess fans and they spend 90% of their gaming time playing chess. Overall, players specialize.

      Such players do play other games, but to a far lesser degree.

      There are also communities that embrace the identity of being good at multiple games or sports. These are a minority.

      And some are inclined to claim all hobbyists are 'athletes' or 'players' and thus unified in some common tribe. Such verbal gymnastics rarely provide much insight into a dedicated hobbyist's specific passions or the nature of their community.

      Specializing in a hobby occurs for many reasons. Traditional sports or games often have the following attributes:
      • Evergreen activities: You don't beat them. You stop when you get bored. Usually they consist of nested loops that operate on time scales of up to a generation. Consider the nesting of Match : Event : Season : Career : Training the next generation.
      • High mastery ceiling: Most are nearly impossible to master completely. You can always get a little better. You can always get better at Go, Soccer or Poker.
      • Strong communities: There exist strong social groups of like-minded players that have their own group norms, hierarchies and support structures. To be a dedicated basketball player is to be part of an extensive basketball playing network.
      • Life long identities: Someone who excels in the game starts to identify as a member of that group. The game becomes source of purpose bigger than themselves. They can look back on their life and say "There were some ups and downs, but I'm secure in my accomplishments as a player of game X"
      • Grass roots or service-based business models: Any cultural structure can be fruitfully analyzed by understanding the flow of money. Many traditional games have extremely low barriers to entry. It costs little to access the initial equipment. Often items like decks of cards or chessboards are either communally owned or purchased by a family and one set of equipment serves multiple participants.

        At higher levels of play, cash flows into the ecosystem through purchases of more advanced or higher status equipment or various service, membership or event fees. In all cases, the businesses involved have strong financial and culture incentives to get you playing and keep you playing.

      Players of digital games consume

      The hobby of computer or console gaming follows a different usage pattern; gamers play a wide variety of games. NPD claims core gamers buy an average of 5.4 games in a 3-month period. In a recent discussion of Steam purchases on Kotaku, commentators chimed in that they had purchased 100 to 800 games. These are played for a period of time and then set aside so that a new game might get some play.

      These players specialize far less. They may prefer a genre of games such as RPGs or shooters, but they'll still consume many games within that genre.

      Why the difference in playing patterns? Commercial digital games have some distinct attributes that encourage serial play instead of evergreen play. Not all digital games fit this mold, but the trends are worth noting.
      • Complete-able games: Most computer and console games can be completed in 5 to 40 hours. It is rare that you find digital games that retain users longer than 6 months. Actual playtime is shorter than the official length since most players do not complete their games and even fewer play through a title more than once. Compare this to the generational nested loops of traditional evergreen games.
      • Narrative and Puzzle-focused gameplay: The majority of the gameplay is focused on high burnout single use puzzles or evocative narrative stimuli. Designers spend their budget handcrafting specific scenarios for maximum emotional impact the first time through.
      • Low mastery ceilings: Since the design goal is to move players through the content of a game as smoothly as possible, the game mechanics are generally balanced towards the average skills of first time players. It is rare and surprising when a single player narrative computer game offers examples of masterful play. All this leads to early burnout where players rapidly become 'bored' and put the title aside.
      • Weak player identities: It is difficult for a player to establish their identity around their excellence in any one game. To be a good Braid player just isn't that special. Lots of other people have walked the same path; there is little player creativity and outside the occasional Let's Play video, few people care.
      • Content-focused business model: Digital games businesses have a strong financial incentive to get you to pay upfront and then move onto their next title. Games are treated as a content or boxed product business. An optimal strategy is to put high quality boxes on shelf (either physical or virtual) and get people to buy as many boxes as possible. Since exciting content remains a large cost center, there is ever increasing pressure to make games flashier and more marketable on the front-end and shorter on the back-end.
      Shortness of play is perhaps the key reason why players end up consuming multiple games. With gamers spending 16-18 hours a week gaming, it doesn't take long to burn through a single title. When a single game fails to entirely fill a person's leisure time, players buy additional games. Only a set of multiple consumable titles provides enough engagement for someone to make a full-fledged hobby out of content-based games.

      This fits the general profile of a media hobbyist. As we shifted from evergreen hobbies to digital retail-focused games, we trained users to behave in a fashion similar to that of a reader who reads many books or a movie goer who watches many movies.

      A media culture

      To be a 'Gamer' is to buy into numerous requirements that only exist to enable the creation of easily consumable media products.
      • Reviewers exist to help players select their next media purchase
      • Critics exist to demonstrate how media conveys a message to society. They are trained (if they are trained) in other media-centric fields such as movies or literature. There is little systemic thinking since media is first and foremost not a functional system but an evocative stimuli.
      • The form of popular games is determined by whether or not it fits in a media box. Form is the standardized structure of a piece of media. The 2-hour narrative movie is a form of video. The 300 page novel is a form of writing. So too is the 14-hour adventure game or the level-based narrative FPS.
      • Stores and storefronts exist to sell the hobbyist a steady trickle of new media. Since media creation is expensive and the share of a player's time is small for any single piece of media, aggregators of content are typically 3rd parties that don't produce all the media themselves.
      • Communities are built around mass media that act as a shared experience for large populations of consumers. Big brands like Mario, Mass Effect or Final Fantasy form cultural anchors much like Star Trek or Star Wars. Comparisons, reminiscences and fan fantasies about future sequels or expansions are common.

      Digital evergreen hobbies

      Into this media-centric ecosystem we've seen the reemergence of major games that hew more closely to the traditional games of old. MMOs like World of Warcraft or MOBAs like League of Legends are services. A digital game like Minecraft ties into numerous communities and is often played for years. Some like Halo or Call of Duty cleverly camouflage themselves as traditional consumable boxed products all while deriving long term engagement and retention from their extensive multiplayer services. These games share many of the attributes of older hobbies:
      1. They attempt to be evergreen.
      2. They have high mastery ceilings and robust communities.
      3. Many, especially eSports, replicate the nested yearly loops of a traditional sport.
        Each of these games is a hobby onto itself. People predominantly play a single game for years. In one poll of 5400 WoW players, 49% claimed to never actively play another MMO.

        The rise of services

        This shift to services is accelerating, driven by business factors and steady player acceptance. Developers are slowly coming around to the realization that an evergreen service yields more money, greater stability and a more engaged player base. Experiments of the past few years with social, mobile and Steam games suggest that microtransactions will likely become a majority of the gaming market. They already represent 70% of mobile revenue and continue to grow rapidly on other platforms.

        This new revenue stream places new constraints on game designs.  Types of laboriously handcrafted content that was once feasible when your game was played 10 hours is no longer profitable if revenue trickles in over hundreds or thousands of hours of play.  Deep mechanics once again matter.  Communities you want to spend time in become a competitive advantage.

        There are indeed manipulative companies scamming settlers in this newish frontier. Don't act so surprised. This is the case for any frontier and this is not the first time games have attracted disreputable developers.  Look beyond the flashy, inevitable crooks, just as you looked beyond the licensed games, the porn games and the gambling games that infest your typical game markets.  Look at the big picture and observe where the new opportunities for greatness blossom.

        No, they won't cross over

        These new evergreen players become hobbyists, but not media-centric gamers. This is most evident in the audiences that play 'casual' social and mobile titles. Many of these players never bought into the current gamer culture. It is common to see someone deep into Candy Crush and when you ask them if they are a gamer, they will deny it. They do not 'game', they never have 'gamed'. They don't share a common heritage of Mario, Zelda, COD, Halo or any of the mass media touchstones that unite current gamers. What they have is a wonderful hobby that in their mind has nothing to do with existing computer games.

        There exists a fantasy that somehow new players will get hooked on one game and then transfer over to consuming other games. Since this assumes a play pattern of high volume serial consumption, I doubt that this will occur. Great evergreen games leave little room in a hobbyist's schedule for grand feasts of consumable content. You don't finish a great hobby and then look for your next dalliance. You keep playing the game for years or even generations.

         The perfect service-based game is one worthy of your entire lifetime of leisure.

        If this seems an exaggeration and current titles feel unworthy of this high bar, wait a while. Developers are very talented. And the financial incentives to build the perfect service-based game are strong.

        Not one gaming hobby but many

        So where does that leave our understanding of 'gaming?'
        • Some people avidly knit in their leisure hours.
        • Others play a creative game like Farmville, Dwarf Fortress, Minecraft or the Sims.
        • Others participate in a social online game like World of Warcraft, Eve or Facebook.
        • And then there is a small but active community of proudly old-school Gamers that like consuming puzzles and story media.
        What we currently think of as 'gaming' becomes just another hobby amidst a vast jungle of digitally augmented hobbies.

        There are those who might see this as a threat, but that is mere fear talking. Existing hobbies tend to last for at least a generation. Those who've tied their identity to consuming media-style games as their hobby will stop participating in the hobby when they die. I expect to see 80-year olds still buying adventure games because that is what they were raised on and that is what they love. Niche producers can make good money serving these avid fans.  The rise of new hobbies thus do not invalidate a current hobby.  In fact, you'll have media-centric games for at least the rest of your life.

         Though each hobby likely will need to compete for new members.

        Impact on the cultural ecosystem

        With this shift comes change. The following may challenge your existing expectations.
        • Specialized interests, not shared experiences: The drop rates on defense potions matters little to your typical gamer. Yet it is of earth shattering importance to the community of Realm of the Mad God players, impacting hundreds of hours of their life. At a certain level of mastery, the language used to describe in-game concepts becomes indecipherable to casual audiences. This inhibits communication with external groups, but facilitates bonding within the group.
        • Deep systemic analysis, not broad media criticism and reviews. Hobbies are predominantly comprised of human systems and communities, not texts to analyze or boxes to sell. Political, anthropological or economic forms of discourse are more appropriate yet there are few game critics trained in these fields. Successful commentators are typically past players with a master-level understanding of the hobby. They are rarely dilettantes flitting from media event to media event.
        • Unique cultures, not mass cultures: A hobby can develop a set of inward facing social norms. This can be a negative if extreme viewpoints are allowed to fester. It can also be a huge positive and promote inclusivity, equality and long term positive relationships. Each hobby is a cultural petri dish that need not adopt dominant tropes or values.
        • Participation, not marketing campaigns: New players of a hobby hear about it from a friend or stumble upon a free trial. They participate first and see if they enjoy the lifestyle that the hobby promotes. Big bang media events can flood the early stages of the acquisition funnel, but they do not directly result in revenue or a sustainable community. 
        One aspect that surprises me the most is the stealthiness of inwardly sufficient hobbies. A smoothly running process is barely newsworthy for those unfamliar with the hobby. Over 5 million people partake in Geocaching, one of the greatest modern games ever invented.  Yet other than the occasional human interest story, it rarely breaks into the public consciousness. What would a media-focused rag say?  "People are having healthy fun...still.  Just like they were last year." That's not news. There is no new box to hype or content to whinge about.  There's no advertising to sell. So silence is the default until you look inside the vibrant magic circle. Geocachers return the favor by labeling outsiders Muggles.

        Let a thousand flowers blossom

        The concept of one true gamer community will be less feasible as evergreen hobbies grow in popularity. Instead, we have a crazy mixing bowl of diverse, separate, long-term communities. Few will share the same values or goals. Few players will consider themselves having anything in common with players of a different game.

        Social organizations such as PAX will still promote common ground, much like the Olympics promotes common ground between athletes. But day-to-day cross-pollination will be rare.

        I personally value a wild explosion of diversity. We need less mass culture and more emphasis on vibrant, generative communities instead of passive industrialized consumption.

        The existing society of players may be tempted to deal with those not like themselves negatively through shaming ("I can't believe you play Farmville, stupid person!") Here's how we might instead react positively.
        • Freedom of Play: Like freedom of religion, any player has a right to devote their life to any game even if it isn't something enjoyed by another player.
        • Mutual respect: Any player deserves your respect for their hobby even if you do not personally understand it. Avoid stereotypes and engage with the person.
        • Willingness to explain: Any insider should be willing to explain to an outsider how their hobby works. Proselytize by inviting them to play with you. An open-minded outsider should be willing to listen.
        The fact that individual hobbies exist is not new. The shift comes from realizing that individual digital hobbies will soon to be the default play pattern. Adapt accordingly.

        take care,

        References and Additional Links

        Note: Gamers often wonder why Farm Equipment simulators sell.  Judged as mass media, they are horrible.  Judged however as an independent hobby, they have many of the attributes of an engaging lifelong interest.  If you laugh at them, it is because you are outside their tribe and ignorant. 

        Prototyping Challenge: 3D Modeling Tool for 2.5D RPG Art
        Posted by Lost Garden [HTML][XML][PERM][FULL] on 24 October 2013, 2:42 am

        I was creating some 2.5D art for an game jam recently in a perspective similar to a 2D RPG like Zelda. Naturally my next step was that I started thinking about how you might recreate this style using a custom 3D modeling tool. Yes, another art tool design challenge. :-)

        I’ve played with voxel editors in the past, but I’m not completely happy with the blocky results that they produce. So where's a quick and dirty minimalist 3D modeling tool design with the following goals:
        • Enable artists to make beautiful 3D models that include curves, ramps, intersecting shapes, and other sophisticated elements.
        • Make a 3D modeling tool that is as easy to use as a pixel art editor. In particular, I’ve realized that this editor can avoid a lot of the messiness that usually appears when you include 3D rotation.
        The result should be art that is still stylized, but has still has an immense range for a talented illustrator. I've made other attempts at this in the past, but I think this one has legs. :-)

        Target style

        I put together a set of 2D art for a future game jam. The resulting 3D modeler in this essay should be able to easily create everything in this image, plus a whole bunch more.

        When making this art, it occured to me that there is a rather magical property of the traditional 2.5D view that I don't think has been well tapped before. Once you adopt a forced 2.5D perspective, most 3D primitives are possible to be represented in a 2D plane. This makes a ton of traditional 3D operations dramatically simpler. You can think of a 3D space being reduced to a couple of 2D controls
        • Top Plane: The top of a cubic volume enclosing the primitive. 
        • Front Plane: The front of a cubic volume enclosing the primitive. 
        Here's an example with a cylinder and the planes made explicit

        With these, you can do basic moving and scaling of the object. The trade off is that you lose rotation.  My bet is that like voxel editing, you can lose rotation and still end up with a vast visual play space.

        If you get fancy, you can flip an object 90 degrees forward so that:
        • Front Plane: Extrusion, XY position
        • Top Plane: Scale, XZ position

        The basic flow of modeling

        Here's what you do to make a model. 
        • Add primitives to an object
        • Arrange (scale, position) and color them.
        • Combine these tile-like objects together in a game to create complex scenes.

        List of Operations

        Here's the list of features that a simple prototype of the editor would support.

        1. Add a primitive
        You can add a primitive to the scene
        • Cube
        • Cylinder
        • Arc (half cylinder)
        • Ramp (NSEW variants)
        2. Select a primitive
        Click on a primitive in the scene to select it.
        • 6 dots appear
        • The bottom 4 define the front plane.
        • The top 4 define the top plane.
        3. Move in XY plane
        Grab the front face of a primitive to move in the X,Y plane

        4. Scale in XY plane
        Grab the corners of the front face of the primitive to scale it.

        5. Extrude in Z
        Grab back corners or edge of the primitive to extrude it.

        6. Move in XZ plane
        Grab the top of the primitive.

        7. Select a color
        Once you have selected a primitive, click on a color from the color palette to change the color.


        There are a variety of limitations enforced that make modeling far easier and closer to pixel art.
        • Snapping: All operations snap to a 16x16x16 grid.
        • Primitive budget: Each object is made up of a total of 32 primitives.
        • No rotation of primitives. Again, this is a hard problem in 3D. So we avoid it.
        • Limited colors: All primitives use the same 16 color palette. This allows us to appear to make complex objects out of multiple primitives by simply connecting simple shapes of the same color.
        • Surface details are generated using other primitives. Primitives whose surfaces are coplanar are rendered cleanly as 2D textures. See bricks in the example above. Use creation order or order in the selection list to determine what shape is on top.

        Bonus features

        The above features are the minimal set.  There are other features you could add to flesh out the tool.
        • Selection list: A list of all 32 primitive in the object. Click on one to select that primitive. Thumbnails are a plus. Bonus points if you can rearrange these. 
        • Hiding/Showing primitives: There is an eye icon in the selection list next to each primitive and you can hide or show that.
        • Rounded corners: Give the selected primitive rounded corners. These are in 1, 2, 3 or 4 grid width rounds.
        • Flip Front / Top: Rotate the primitive forward or backwards 90 degrees. Example: A flat disc becomes a wheel.
        • Cutter object: The selected primitive now subtracts from the solid instead of adding. This lets you cut holes. 
        • Textures: In addition to colors, you can specify some simple textures.

        Special rendering tweaks

        There is a reasonable chance that objects will look like rather ugly without the right rendering. Play with this till you get something that works.  Here's what I take into account when drawing things manually.
        • Parallel Light source (think sun) from the top so the front is in slight shade.
        • Shadows on other objects. Slight ambient occlusion will tend to make the objects feel more connected. 
        • Shading objects darker near the bottom and lighter near the top help preserve a sense of depth.

        Test cases

        Making art tools without art samples is tricky. The following are test cases that you can try to replicate once you’ve built the basic tool.





        If anyone makes a prototype, I'll link to it here. 

        *Update!* Angry Octopus has a prototype.  (The more the merrier, so keep making 'em.)

        All the best, 

        Multiplayer Logistics
        Posted by Lost Garden [HTML][XML][PERM][FULL] on 31 December 2013, 2:52 pm
        How do we get players to play together in a manner that fits their schedules? This is a key logistical challenge a designer faces when building multiplayer games.

        The promise
        We are seeing a blossoming of innovative multiplayer systems. In previous eras there were a handful of default models that games might use (matches, play-by-mail). Games today exist on a spectrum from fully concurrent to fully asynchronous and everything in between. A game like Dark Souls is predominantly single player, but includes interactions that are asynchronous (the leaving of messages and deaths) or fully concurrent (the joining of another player into your game for PvP or Coop.)

        We are entering a golden era of multiplayer gameplay. Server costs are falling dramatically with the advent of cloud computing. Broadband internet and always on mobile connections are spreading rapidly across the globe. Business models like in game payments, crowd funding and service-based gaming are evolving to the point to financially support a broad range of long-lived communities. Designers are playing with these new capabilities to invent new forms of multiplayer gaming.

        The challenge
        However, multiplayer is both expensive to build and has a high risk of failure. Often teams invest 50 to 100% of their development budget into creating a multiplayer mode. It seems worth it. During development, the team plays every Friday and has so much fun they are convinced that multiplayer is what will turn their game into the next League of Legends or Counter Strike.

        The real test occurs when the game faces a live population of players. Upon launch, multiplayer games often see only a few weeks of active multiplayer activity. Too many people show up. Then not enough. Players visit sporadically and the player experience is deemed unreliable. The active matches trickle down to nothing. The traditional matchmaking lobbies (a design from the 1990’s) are left empty and will never be full ever again. The multiplayer portion of the game dies a sad sputtering death.

        I see this as a challenge of logistics. There were players who wanted to play. However the way that the game put those players together results in weak community that was unable to self sustain.

        Are there atomic elements of multiplayer logistics that lets us approach the topic of inventing new systems in a more rigorous fashion? Simply copying multiplayer patterns from previous eras works poorly. To invent new multiplayer modes, we must have conceptual tools that let us clearly and concisely manipulate topics like logistics, concurrency and interaction schedules.

        Concepts when talking about multiplayer

        Here are some concepts I think about when designing a multiplayer game.


        You can break up any multiplayer system into a series of interactions. An interaction is anytime players interact with one another via a game system (be it chat, hitting one another, etc.) These are the multiplayer verbs of your game. Usually a game has a set of single player verbs (move, quit, etc) and another set of multiplayer interactions mixed in. Interactions have a wide range of multiplayer properties such as frequency, scope, mode, etc.

        If you map an interaction onto time, it looks something like this
        • The player starts the interaction
        • They end the interaction
        • They wait for a response.
        • If no response is forthcoming, they leave.
        Interactions aren’t a new thing. The structure is identical to that found in atomic game loops. However, instead of a single loop you have something closer to a figure 8 with at least two participants. These concepts go back to communication theory that Chris Crawford adapted to games design theory in the 1980’s. This is fundamental stuff that all professional game designers should know.

        Initial loop:
        • Model A: Player formulates an action and a target player or group.
        • Action A: Player performs the action.
        • Rules: The results of the action are mediated by the game logic.
        • Response A: Player A sees the immediate results as generated by the game.
        • Response B: Player B sees the immediate results as generated by the game. Note that what Player B sees is likely different than what occurs for player A. This naturally leads to divergent mental models and enables gameplay concepts such as hidden information or Yomi.
        Reciprocating loop
        • Model, Action, Rules, Response B: The target players tries to understand what happened and formulates a response.
        • From here the loop ping pongs back and forth between participants.
        Frequency of interaction

        What is the frequency of interaction necessary to yield the impression of concurrency? You may find that you need to interact once every 5 minutes in a strategic game like Civilization while you need to interact every 200 ms to create the same impression in a twitch-based action game like Counter-Strike. See the article “Loops and Arcs” for a more detailed explanation.

        In general, the higher the frequency of interactions, the more information being communicated between players. This can increase the pace of relationship formation.

        As with many interaction variables, there are distinct phase changes in the players perception as the frequency hits a threshold. Simply by changing the spacing between interactions, we get radically different forms of play (and associated logistical challenges):
        • Real time: Players perceive interactions as ‘real-time’ when the frequency reaches the point where: A player starts and ends an interaction and then sees a response before they move onto other tasks; interactions overlap. Chat, for example, can feel real-time despite there often being more than a minute between responses. Real-time systems have less need for persistence but are often more expensive to run and build.
        • Asynchronous interactions: The frequency at which a player can start an interaction and end the interaction and then quit the game without seeing a response is seen as asynchronous. Generally you build in some sort of persistence so that a player that logs in later can see the results of the interaction and formulate a response.
        Types of interaction
        There are a variety of interaction types. Think of these as ‘how’ players interact. For a much more in depth description of all the various multiplayer interactions, see Raph Koster's seminal talk on social game mechanics.
        • Spacial avatar interaction: Two or more avatars interact with one another. Shooting players in Quake is the classic example. Following a player in Journey is another.
        • Spacial environment interaction: Players also interact through the intermediate environment. In Minecraft, players build castles that other players then explore. For a higher frequency example, in Bomberman, players place bombs that open up passages or do damage to others.
        • Decoration and Display: Players signal status, affiliations and history via what they wear or how they decorate their weapons, pets and houses.
        • Economic: Players give, trade or pay for various resources to transform or transfer to another player. This can be a typical sale of a sword to another player for gold. Or it can paying mana for a buff that boost the health of a nearby player. See Joris Dormans work on internal economies for more on this topic.
        • Text: The most common method of introducing language into an online game is through text. It tends to be low cost and there’s a rich set of tools (spam filters, stylistic conventions) for dealing with common issues. It tends to work best with a keyboard.
        • Voice: Voice offers additional nuance including emotions, age, gender and more. It has limits for group size, bandwidth and is notoriously weak when it comes to filtering.
        • Body language: In local spaces like on a couch or around a table, we pick up on high bandwidth communication such as facial expression, posture, body height and physical presence. When a tall pretty boy looks you in the eye and asks that you trade your rare treasure with him, you may be getting signals that go far beyond what is found in other types of interaction. This creates rich emergent multiplayer gameplay. However, it is also hard to mediate and incorporate explicitly into the game systems.
        Size of community
        There are also massive phase changes that occur as you increase the number of participants in a community.
        • 1 player: Mastery, progression, exploration, narrative are available as design tools.
        • 2 players: Communication, relationships, status, gifting, trade, cooperation and competition become available.
        • 3-4 players: Alliances, politics, gossip, othering/stereotyping become available.
        • Small group (5+): Group vs group interactions, Official leadership, role specialization, official punishment
        • Medium group (12+): Factions, barter economies, and banishment
        • Large groups (40+): Hierarchy (leaders and sub-leaders), Currency-based economies, role enforcement. Adhoc systems of government, public codification of social norms.
        • Very Large groups (200+): Merchant classes, market-based pricing, codified systems of government, underclasses, celebrity, propaganda. This is the point at which a players is guaranteed not to know everyone and official systems are required to make social norms work. (see Dunbar's Number)
        • Massive groups (1,000+): Polling, city-scale production efforts. There are very few dynamics that happen at this scale that aren't also explore with 200+ or even 40+ groups.
        I'm defining these groups in the context of player interactions.  The actual game population may be much larger.  For example with trade in Realm of the Mad God, we saw simple trade interactions happen with as little as two people even in populations that are in the thousands.  Two good rules of thumb when considering group size is to ask:

        • Who does this action impact or target?  This gives a rough estimate of the group size your system needs to support. 
        • Is a larger group size necessary for this behavior to emerge?  If not, you can usually get by by targeting your design at multiple instances of a smaller group size. 

        The actual transition points fluctuate around these numbers based off contextual factors. For example, the transition to the dynamics of a Very Large Group can occur as soon as 60 or 70 people if there are weak communication channels that stress a player’s ability to maintain relationships.

        Also, large groups are inevitably composed of smaller groups. So as systems are added, the dynamics of lower number groups are still present.

        The dangers of large group sizes: It can be tempting to make epic multiplayer games with thousands of interacting players that could theoretically all fit in the same room. However, the technology and design costs are high and the benefits weak. Past 150-250 players, your game is in territory beyond Dunbar’s theorized biological limit on maintaining meaningful relationships.  All those extra people end up just being treated as number or abstractions by your players. A simple sim or polling system can often capture the major benefits of the next highest group size. 

        Realm of the Mad God was completely playable as an MMO with action sequences of 40-80 players and trade / hub interactions of 150.  Players did not miss the 1000s of players. 

        This reality raises serious questions about the need for designs that emphasize ‘massively multiplayer’ experiences. Just because a concept sounds exciting (“a million people building a new society!”) doesn't mean it is a smart design. Human social capacities are limited and we can (and have!) over-engineer multiplayer systems.

        Scope of interaction
        How many people does a single interaction impact? A player can interact with a single individual or they can interact with one of the group sizes listed above.

        • Targeting a player interaction at small groups: With smaller group sizes you get communication similar to a conversation. There is a clearly defined interaction loop that can stabilize on a set of shared vocabulary and social norms quickly.
        • Targeting a player interaction at larger groups: With larger group sizes you see more broadcast scenarios and interactions are broader, less tailored to individuals. When interacting with large groups, it is common for the massive response to flood the recipient with too much information. Extreme reactions are also more common as people talk over and past one another.

        Degree of interaction
        • Parallel: Players can behave independently from one another. A ghost racing car rarely impacts another player. Often the primary benefit here is a sense of presence though it can also tie into lower frequency zero sum interactions like a leaderboard.
        • Zero Sum: The action of one player blocks or reduces the interaction of another player. In Habbo hotel, movement is a zero sum interaction since the placement of one character blocks another character from occupying the same spot. This was famously used as a griefing tactic to box in players.
        • Non-Zero Sum: The action of one player benefits another player. In Realm of the Mad God, shooting an enemy makes that enemy easier to kill for other players. Killing an enemy gives XP to everyone on the screen.
        Matchmaking is the computer mediated act of introducing players to one another so they might interact.

        This is a very broad definition of matchmaking, but is useful in the context of the wide range of multiplayer systems available. For example, a traditional console title might match players together by requiring players in a shared lobby to manually join a specific game. In Realm of the Mad God, players notice groups of players on a shared map and teleport to them. Both are forms of matchmaking, but they appear quite different in the player’s mind.

        You can treat matchmaking abstractly as another interaction with a wait time.

        Matchmaking window

        The time you have to introduce a player looking for a multiplayer experience to another player. If the window is too long (and the player is not entertained during the window), they will leave.

        Matchmaking failure
        When a player comes online and there is not another player immediately online, the players will quickly become bored and leave. There is often an implicit promise of a fun multiplayer experience and if you don’t deliver that in seconds, your game is judged as a failure.

        What can be frustrating to the developer is that another player pops in a minute later and experiences the same exact thing. If one players sticks around long enough, another player will show up.

        Calculating daily failure threshold: If the matchmaking window is W in minutes, then failure will occur when the daily active population is less than Minutes In a Day / W. So for example if people are only willing to wait half a minute, you’d need a daily active population of 1440 / 0.5 or 2880 players. Actual results will be lumpy because we are dealing with a statistical process and player populations peak around specific times of day.

        This may seem quite reasonable, but if you are matchmaking primarily with small groups of friends, players may feel like no one they know is ever on.

        When the player population is segmented by social groups, game modes, players skill levels, time playing and other factors, it becomes fragmented. This reduces the actual concurrent player numbers available to the matchmaking system and increases the chance of a matchmaking failure.

        Example of fragmentation: Suppose a game has 3 multiplayer modes and matches players into 10 skill categories. If the daily failure threshold is 2880 (from the previous example), then in the worst case scenario, you’d need 3x10x2880 or 86,400 concurrent players for everyone to get their first choice.

        Fragmentation creeps into a design. Someone wants to add another event or another game mode. The code is free, so why not? Surely the players will self sort. They do a little, but mostly they wonder why the matchmaking experience is so painful and then leave your game in frustration. Avoid fragmentation creep and put players together in big easily matched buckets when possible.

        Concurrency ratio
        Any game has a number of active accounts and a number of players that are online at once. Players cannot be playing constantly and are often offline For example, an MMO might have 100 active subscribers, but only 10 of those are on at any one time. This would result in a concurrency ratio of 10:1.

        Some typical concurrency ratios:
        • MMO: 10:1
        • Online Console Service (like Xbox Live): 25:1
        • Individual Console game: 150:1
        • Flash game: 250:1
        • Couch multiplayer: 1000:1
        The Active User Trap: One common mistake is that developers assume that high active player numbers will result in robust multiplayer communities. However you really need to look at actual concurrent users since many game types have extreme concurrency ratios. A game may have 1000 players but when each of those logins last 5 minutes and are spread over a week, you’ll average 0.5 concurrent players. If your matchmaking system doesn’t deal well with these sporadic, tiny populations, the game dies.

        Relationship strength
        Not all player interactions are equal due to unique relationships between players. Players build complex social models of other players both in game and out of game. Strangers are understood through simple, stereotype-based models. Close friends are understood through complex individual models built up over thousand or millions of minute reciprocation sequences.

        Building mental models of another human is a biologically expensive operation. We seem to be able to keep 5 to 9 detailed models active at any one time though we can store many more at various levels of detail. Friendship is rare, complicated and built over long periods of time.

        There are numerous benefits and trade offs that come from gaming with strangers or friends and friend-based play is often highly desirable. Games can help create friends by promoted repeated positive interactions. The higher the frequency, the quicker the relationship evolves.

        Relationship strength is a spectrum, but there are two commonly drawn categories
        • Multiplayer with Strangers
        • Multiplayer with Friends
        Multiplayer with Strangers
        Let’s tackle multiplayer between strangers online first.

        • Anyone playing the game can be matched with anyone else with little regard for existing social bonds.  This model becomes immensely attractive when there is a small initial player base. Often this means if 10 people are online, 10 people can be playing together.
        • Strangers, particularly young males, historically tend to compete with one another. This means that player vs player games that emphasize open conflict are an easy means of generate fun for some stranger populations.
        • Strangers have weak bonds and will not naturally engage in prosocial activities like collaboration.
        • Skill differentials matter since players tend to compete. This forces developers to focus on segregating experts from newbies and fragments the population.
        • Not all player populations thrive on overtly competitive gameplay. Some players prefer to collaborate. Others compete quietly for status by manipulating social relationships. These are difficult in stranger scenarios.
        Multiplayer with Friends

        • Players are much more likely to schedule time together to play.
        • Cooperative and communication heavy activities are considered fun.
        • Mentoring between divergent skill levels is more likely to occur.
        • Competitive play is still valid.
        • There’s often little overlap between existing social groups and interest in a specific game.
        • There’s often little overlap between existing social groups and share scheduled.
        • Friend groups are small. Engaged players typically have 5-9 close relationships. Casual acquaintances may be higher in number, but in practice may act more like strangers. If you have 10 friends and the concurrency ratio for a service is 25:1, you will essentially never stumble upon them online.

        Tools for dealing with multiplayer logistics

        So far I’ve just talked about the concepts behind multiplayer. Now we’ll dig into some common patterns that make use of these. There are three broad architectures:
        • Match-based games
        • Room-based games
        • Asynchronous games

        Tools: Match-based games

        Due to the long history of event-based matches in sports and board games multiplayer computer games often are organized into matches that start at a specific time and stop at a specific time or win condition.

        Matches are the default logistics model used for many console and PC-style online games. They are immensely problematic. The matchmaking interaction has a very narrow window during which it requires a full set of players to show up in order to enter the game successfully. If you don’t get in, you need to wait till the next match starts. If this time is longer than the wait window, you’ll quit. Considering concurrency ratios, fragmentation and the burden of a tiny matchmaking window, it is not surprising that only the most popular match-based online titles survive.

        Scheduled Events
        Ask people to show up at the same time. This essentially shifts play times so that they are on at the same time. Scheduling is an expensive planning activity on the part of the player. You’ll get a low overall engagement rate but those who do participate are likely to find others to play with. A special Halloween boss encounter in a MMO is an example of a scheduled event.

        Events can be scheduled by the game developers or they can be scheduled by the players. Player scheduled events have the benefit of stronger social ties in play. Folks that get together for a board game night are such an event. The downside is that arranging meeting is a convoluted process (as anyone that tries to set up meetings with more than 6 people can attest). It often requires leadership or persistence, attributes that are often in low supply for lightly engaged players.

        Regularly scheduled events
        If you can make the event regular, people will get in the habit of being at a particular place at a particular time. This reduces the cost of planning for the player and they can just reliably show up at a specific time instead of worrying about conflicts. A standard Wednesday game night for a guild is an example of a regularly scheduled event.

        Short matches
        If matches are short enough (2 minutes? 30 seconds?) players that don’t get into the current match wait less time than the matchmaking window and thus are still around when the next match starts. Online word games do this, but it could be readily applied to other titles.

        Spectating on matches while waiting
        If you can keep players entertained by letting them watch the game in progress, you can lengthen the matchmaking window. Games like Counter Strike do this upon entrance into a server and upon death.  Chatting is often tossed into this mix since it is a nice downtime activity that can build relationships.

        Bots during matchmaking to fill waits
        Instead of putting players in a queue where nothing happens, put them directly into a match with bots as the opponents.

        Getting bots that act like humans is often a tricky Turing test to pass. Not letting players talk and having a very narrow window of expression helps.
        When players learn this is happening they will start to distrust the game and question if all opponents are bots.

        Mechanical Interdependencies
        Create activities that require multiple people to show up in order to achieve success. Not showing up lets down the group and thus increases the social pressure to show up. This can take the form of explicit roles or by limiting resources so that players can’t accomplish large goals independently.

        Tool: Room-based games

        Ultimately match based games result in often insurmountable logistical issues for smaller games. A favorite alternative is room based games. Unlike a match which has a distinct start and exit, room-based games create a persistent playspace that players may independently join the game in progress (or leave the game in progress)

        Rooms have a maximum number of ‘slots’ or spaces for players to join them. Once the room is full, no more players may join. This dramatically reduces the load on matchmaking. All you need to do is find a room with an empty slot available and dump players into it.

        The downsides to rooms is that they eliminate certain game types. Group starting times are obviously out which eliminates most traditional sports. Games with progression arcs result in players that start at different types having differing levels of progress. You need to get creative.

        A game like Journey is essentially a room based game with join and leave in progress. The max slots was 2 and as long as there were two concurrent players you could have a multiplayer experience.

        Most MMO’s are room-based games with very large rooms.

        Join In Progress, Leave in Progress
        One reason why rooms offer such improved logistics over strict matches is that players may join or leave at any time.  Since it is highly unlikely that everyone will leave at once, especially in games with a predominance of parallel interactions, shortly after one person leave another person will join and you'll get a consistent average population in the room.

        Pure match-based games are often quite rare because many popular games treat the individual server as a room and the match-based elements are merely scoring atop a dynamic population of players joining and leaving in progress.

        Elastic Room Instances
        Create and remove rooms to fit that maximum currency. Given a room of maximum size N, you create new rooms so that the number of rooms equals Concurrent Player / N. So if 10 players are online and your default room size is 4, you’ll make sure there are 3 rooms to join.

        To collapse a room, just wait until it naturally empties out as players leave the game or kick people out due to some in-game event intended to free up the instance. Once the room is empty, delete it. By giving rooms priority, you can fill the highest priority rooms first and kill off the low priority rooms. The result is that almost all rooms are constantly full and only the remainder are left alone.

        We used this when creating world shards in Realm of the Mad God. The world generally felt full even when the concurrent population fluctuated dramatically.

        Default to single player gameplay for rooms with one player
        Room-based games have the ‘remainder’ issue. A given maximum room size rarely divides evenly into the concurrent population. If the room size is 2 and there are 3 players online, there will be 1 player placed in a new room by themselves.

        To deal with this scenario, it helps to have a game that is playable as a single player game until the next player joins the room.

        A retail game like Dark Souls assume very low concurrency and plays almost entirely as a single player game (with light async ghost interactions) The concurrent matchmaking is a silent parallel interaction that happens without interrupting the single player adventuring. Since having a second player in the right place at the right time is uncommon, the game instead treats it as a special occurrence. (Note that since Dark Souls promises a single player game, they make the concurrent multiplayer experience opt-in through the use of soapstones. The soapstones signal that a successful match has occurred and the player must accept it. Respect your initial promise when you mix single player and multiplayer interactions.)

        Asynchronous techniques

        A player completes an interaction and then the game signals to them that they have a very long period of time before the other player responds. The next day or so, the other player sees the first player’s action and composes their response. This can take place over days.

        Words with Friends is a modern example of this technique, but the practice goes back decades if not centuries (if you include play-by-mail board games). It is an intimate method of play that works well with text communication much like instant messages or email. Play-by-mail is very amenable to play between friends.

        A downside is that players are deeply impatient. A single turn may not be all that satisfying and then having to wait multiple days for a response has a major drop off in retention. There are still matchmaking issues if fragmentation is too high but the explicitly long wait window ensures players don’t get too worried that the system is broken (they may just not like the system).

        The other downside is that in turn-based games, the non-response of one player may block another player.

        High Capacity Play-by-mail
        One solution is for a player to start a large number of play-by-mail games. Given a response time of T days and a desired average wait time of W days, then the optimal number of games going at once is T/W. (So if you want a game popping in every hour and it takes 24 hours to response, then you need 24 games going.)

        One added benefit of all this is that player response times are semi-random. This acts as a random reinforcement schedule and can result in very long term retention.

        The downside to the technique is that it requires players to start up a lot of games in order to reduce the wait window and motivating players to do so is tricky. Automated game matching may be an answer.

        You can leverage active players to invite new players to the game. These players often have strong relationships with the player and can potentially act as a source of new players into the game.

        Match with friends
        Since async forms of multiplayer rely heavily on players to come back later, their game designs often relies on social connections outside the game as a form of additional pressure. If you can get people to invite or match with friends (as in Farmville) a lack of reciprocation in interpreted as putting their existing relationships at risk. The threat of being rude or seeming like you don’t care to someone you like is often enough of an incentive to encourage returning to the game.

        Systems that play off existing relationships run the risk of alienating players. Players not invested in the game tend to find mechanical interactions annoying. Authenticity and intentions matter when it comes to human relationships.

        In building games, you may create a persistent structure such as a town that other players can then visit independently of your presence.

        Clash of Clans uses this when players attack your town. The town is a persistent structure that then acts as a level for the other player to conquer.

        Visiting usually boils down to a simple resource exchange despite the trapping of being something more meaningful. The issue comes from questions of what happens when multiple people visit at once and the solution is to spin up different instances.

        Jason Rohrer’s The Castle Doctrine uses the unique design of making visiting a blocking interaction. This opens the possibility for permanent changes being made to the visited location. One can imagine more complex versions of musical chairs as the foundation for some innovative designs.

        Record players behaviors and then play them back alongside the player in a similar environment. This works particularly well with parallel interactions like you see in racing games. It can also work with the rare non-zero sum interactions like you see in multiple time track games like Cursor 10 or Super Time Force. Ghosts gives a sense of presence but removes the matchmaking time constraints.

        The downside is that ghosts usually works poorly with blocking or zero-sum interactions. The other downside is that if the ghost data and the environment get out of sync, then the ghost data becomes invalid. These can be alleviated slightly by either skipping blocked actions or falling back on AI behaviors that manage exceptions

        On a more abstract level, ghosts are just tracks of player data that can be replayed on any sort of trigger. They can be triggered at the start of a race, when the player comes onscreen or when the player uses the special amulet of Ally Summoning.

        General practices

        This essay has covered a lot of ground (and is still incomplete!), but I’ll leave you with a few quick recommendations.
        • Don’t fragment your matchmaking population. Be very wary of the point at which your concurrent game’s matchmaking fails due to high concurrency ratios.
        • Use room-based methods where possible, not match-based play.
        • Persistence is your friend since it enables asynchronous interactions.
        • Relationships are your friend since they increase retention. Try to build them where possible.
        • Prototype early and deal with low populations density issues during the prototyping phase.


        I remain quite excited about new multiplayer games. When I look at the theoretical advances being made with game grammar via Joris Dormans internal economies and some of the multiplayer concepts in this essay, the unexplored space for new forms of game seems vast. If you want to make your mark on our modern world, make a great multiplayer game. Solve the logistical issues that prevent people from playing together and build a game that spreads quickly and easily throughout communities.

        take care,

        Notes and references

        Topic for future investigation
        Concurrency is a statistical process; there’s a chance of a player being on at a given time. This whole topic could stand to be dealt with in a mathematically more rigorous fashion.

        Essays and books

        How game forms are shaped by their environment
        Posted by Lost Garden [HTML][XML][PERM][FULL] on 25 May 2014, 8:12 pm

        We often consider artistic works from a creative or cultural perspective, but I find it just as enlightening to examine them from an economic or evolutionary lens. How does the economic environment within which a developer finds themselves shape the form that art takes?

        As a case study of this in practice, I’ve been fascinated by a class of content-focused game that’s recently found a stable niche in the maturing mobile, PC and console markets. In mobile, we see examples like Sword & Sworcery, Device 6 or Monument Valley. In PC, you've got Kentucky Route Zero, Proteus and Gone Home. On console the trend is less pronounced, though Journey and Flower share some aspects.

        These games generally have the following characteristics
        • Strong focus on evocative content: Most of the game is composed of arcs that deliver heavily authored payloads. The player’s cognitive load is consumed by interpretation of stimuli not the planning or execution of actions.
        • Light use of systems: Mechanically, the games tend to have limited interactive loops. There is little room for play within a mechanical space. The systems used are often highly traditional with a long history within other genres.
        • Short playtime: Often 1-3 hours.
        This form thrives not due to some sudden explosion of artistic appreciation within the human race, nor due to universally-applicable intrinsic attributes of Truth and Beauty. No, instead these games thrive because they competently execute a development strategy that matches well with the current socioeconomic environment.

        Form shaped by environment risk

        Form is an accepted and standardized structure for a work of art. A painting stretched on canvas painted in oils that fits roughly on a living room wall is a common form of painting. A haiku is a form of writing.

        Unlike many media, the forms that a game might take are still quite fluid. Where authors of literature might feel locked into to well-established structures such as poem, short story, essay or novel, game forms are both broader and have less sharp boundaries. They vary radically in mechanics, scope, topic, number of participants, and hardware. The difference between a game of Tetris and a game of Charades can seem far vaster than that of a Shakespearean play and an encyclopedia entry. And as a designer, you often get to chose the unique form of your game.

        How risks shape game forms

        However, different forms of game have different levels of risk and trade offs. There’s internal risk such as design risk, technical risk, production risk. And then there's external risk such as distribution risk, market fit and many others. If any one of these aspect of the project fails, the development investment is lost. Any game design can be judged by the costs associated with building the game, the benefits of success and the downsides to failure.

        Fig 1. Valid terrain based off existing environmental risks

        These are not abstract decisions. Most developers (even large ones) operate a paycheck or two away from bankruptcy. Paying the rent and putting food on the table are very real concerns. Many smart teams therefore choose projects of a form that minimize overall risk in order to dramatically increase their chances of future survival.

        Thus game developers have a great incentive to evolve game forms to fit whatever environmental pressures are present. If something changes in the environment that increases a type of risk, then you’ll see developers selecting, from this vast palette of potential forms, the options that mitigate that risk. Picture a thousand little Brownian developers blindly adapting their game forms to half felt market forces and thus converging on useful strategies.

        Using survivors to determine dominant strategies

        The process of evolving games forms can feel invisible. The vast majority of projects that don’t balance their risks correctly, fail and sink out of the cultural consciousness. Most creators are barely conscious of their influences and constraints. All we really know are the the survivors.

        When you see a new species of game thriving in the marketplace, you can start to ask some interesting questions. What are the culling mechanisms that let those games survive? What strategy was used that gave them an advantage over other possible designs? The things that make it through the filter give you some insight into the shape of the filter.

        Some forces at play

        What are some meaningful forces acting upon the modern indie developer attempt to sell a game for a fixed upfront price?
        • Digital distribution and cheap tools: At the heart of the emergence is ability for small teams to build and release games at low cost. However, those markets are now maturing.
        • A large audience trained on content consumption: The past decade of AAA titles perfected a variety of secondary content delivery standards via cutscenes, level design, voiceovers, etc. Gamers know and understand these methods. Over the decades, we've built up the equivalent of a trained audience that knows how to read.
        • Average revenue for a product is dropping. In fact they are close to zero in mobile markets. The exponential distribution of revenue looks more L-shaped, with small number of titles making the majority of the money and no middle market to speak of. You have hits or failures with little in-between.
        • Price per unit for games with an upfront cost is less than $0.99. As Steam opens up further, bundles proliferate and consoles introduce more free games, expect further price erosion for premium titles. You need to reach more people to make less money.
        • Discoverability is weak. Discovery mechanisms are weak and heavily gated. Channels are also flooded with games of difficult to determine quality. A game benefits from being able signal quality 1 to 30 seconds of exposure since that is likely all the time it will get.
        • Cost of production is increasing: Cheap tools bring the capital cost down, but labor costs remain stable. The need to hit ever increasing levels of quality results in an escalating cost curve. Five years ago, a hit premium game on mobile might cost $50,000 to build (including sweat equity). Now, for less revenue, you’ll see costs range from $200k - 1M (or higher). This expense is almost entirely due to content and feature competition: more art, more animation, increased use of 3D, more ‘required’ features.
        So it is hard to stand out, hard to make money and very easy to spend more than you make.

        A content-focused strategy

        Given such a landscape, what is a species of game that might survive? We are looking for solutions to the problems listed, but also ways of tackling multiple problems with the same resources. Efficient solutions survive.

        Fig 2. A strategy that mitigates technical and design risk.
        While taking on some distribution risk.

        Note that the following is by no means the only strategy. If you look around at other thriving developers, there are many alternatives. Nor is it a preferred one. This strategy has no inherent value beyond its functional benefits. Nor for that matter is it likely that the half-blind creators explicitly planned out their strategy. Like the flying fish and the (sadly extinct) flying shark, common strategies converge unwittingly from disparate perspectives as if shaped by an invisible hand.  Environments have local maxima whether or not we are smart enough to perceive them ahead of time.

        With those disclaimers duly dispensed, consider a content-focused development strategy for small teams...

        Reduce costs
        • Target a smaller scope: Content is expensive, but what if you make a game that is 1 to 3 hours, not 20 or 30? This simple change means you can cost 1/10th what a bigger title might. This is the defining economic attribute of this game form.
        • Remove systems and features: Trim as many standard elements as possible and focus the game focus on one or two key features. Dear Esther, you walk around. In Gone Home, you walk around and click on objects. NPCs? Cut. Combat? Cut. Branching narratives? Cut.
        • Keep your team small. Since labor is your largest cost, a small team means lower investment. Team members should being able to execute multiple aspects of development so you don’t need part time specialists.
        • Keep your development cycle short(er): Spend 9-12 months on a title, not 18-24 months.
        • Excel at what you attempt: It helps to have at least one or more people who are world class. Then build your game around their signature style. This makes up for some of the inevitable weaknesses that arise from small teams sizes, wearing too many hats and short schedules.

        Reduce distribution risk
        • Make high impact video and images. Since you have limited contact with potential players, you want the briefest glimpse of a game to excite them. Gorgeous visuals, evocative narrative hooks that can be grasped in a couple seconds work well. All many buyers need to see of Monument Valley is a single screenshot.
        • Form relationships to amplify your signal for free: With a small team and a low marketing budget, free distribution is ideal. By forming relationships with journalists, streamers, taste makers and platform curators, you may get a mention or a feature. Of course, what you provide in return is a sellable story or validation of their long simmering world view. ‘Games as art’ is currently easy topic to bond over and all games with this form make the most of it. 

        Reduce design and production risk
        • Rely heavily on static content: Art and video rarely fails on a functional level. There’s a risk in discovering an artist initially, but once on board, a competent artist tends to continue to produce competent art. Especially over short production schedules. You already need to make high impact visuals in order to get distribution, so there’s synergy here.
        • Use existing mechanics: New mechanics take time to discover and often don’t work out. Invention is hard. By using well proven traditional mechanics, it is unlikely that the systems will delay your game. Turning a page or clicking a hyper-link is quite reliable.
        • Reduce systemic emergence: Unplanned surprises hurt the schedule and cost you money.

        Reduce technical risk
        • Use existing technology: Well proven, simplistic technology. Again, you can get away something that simply puts quality content on the screen
        • Avoid complex technologies: Technology that require strong expertise such as multiplayer servers or advanced 3D rendering is likely to blow up. So don’t do that.

        Reduce audience risk
        • Make the game easy to finish: You want people to play the game, finish it and then talk to their friends while still in midst of the afterglow. This is a fast virus, not a slow one. Challenge is a useful tactic in other contexts (Dark Souls, Spelunky), but it is a poor fit when you want to deliver your beautiful load of content as smoothly as possible.
        • Keep content highly interpretable: To offset the risk of the game being too short, you can implement content that either vague or open to many interpretations. This means that quality of your content can be lower without anyone being able to concretely describe it as such. A certain air of mysterious brilliance can act as a prophylactic against common criticisms; seed the doubt that a player may simply be unschooled in Imperial fashion.
        • Engage the community: Ideally, you kick off a secondary wave of community engagement as players and critics invent their own detailed explanations for what may in fact be random (yet highly evocative) noise.
        Notice how all these pieces fit together into a coherent strategy. A small team with a strong artist and / or writer makes a short, attractive game that sells a light narrative. This also happens to be small enough a scope that they can finish and release it. Such a game is pretty enough to be featured and can be easily talked about. There’s also little risk for the player...they get this nice watchable nugget of content that’s super cheap and feels like a reasonable value relative to other comparable consumables like books or movies.

        A deeply conservative take on games

        This strategy formula isn't new in the grand scheme. Cheap, consumable content differentiated on gatekeeper-approved quality variables is at the heart of most media markets.

        In grand spectrum of possible games, the crop of boutique content games is one of the most conservative possible development strategies. Rosy cheeked media critics who might imagine the real history of games started in 2007 are likely excited by such titles. However, when compared to the rich systemic and narrative experimentation of the last 30 years, these forms are ultimately a retreat; survivalist risk mitigation marketed as hip cultural advancement. Such games tacitly give up on the idea that games could be a different type of thing than traditional media and adopt whole hog similar methods and limitations. At the crudest level, you flip pages, you see content.

        One should tread lightly in labeling this as a ‘bad’ change. Evolution does not judge. This strategy works. Good, passionate people are making money and surviving to build another game. That’s all you can really hope for as a game developer in a staunchly capitalist world.

        The future

        Since we are dealing with a conservative product strategy, comparable markets suggest where these might evolve over the next 5 years.

        Fig 3. Increasing costs put new pressure on the content heavy form.
        Player desire for the new form increases the overall market opportunity.

        • Rapid market saturation: Since costs of entry in terms of skills and technology are quite low and first movers have almost zero competitive moats, new entrants should flood the market. This reduces the average success rate; most will not be profitable.
        • Costs increase: As more entries appear, quality becomes more important. Those with cash spend more to keep or capture profitable audiences. Form-specific blockbusters emerge that spend the maximum amount to get the maximum audience. (I've called these genre kings in the past).
        • Shorter length: Increased costs put pressure on decreasing the length even further. At some point players may decide that even an amazing 20 minutes is not worth 99 cents.
        • Use of portfolios: Anthologies, bundles or subscriptions to content streams (aka magazines) are common methods of paying a population of authors in a hit driven ecosystem. If this shift in market structure occurs, middlemen begin dictating tastes even more strongly.
        • Attempted differentiation based off thematic genre: Essentially the market fragments. As customers become trained in this new form, they’ll start to prefer specific types of content, much like we we see romance or mystery novels. First movers in thematic areas could tap a new sub-niche.
        • Fragile specialist firms: Developers will need to specialize in this specific form to produce the best of breed content. However, this makes them inflexible when the need arises to adapt to new forms. We've seen this situation play out in the past with adventure games.

        It may seem silly to predict a future of saturation and collapse when there are so few of these games around. Yet markets are never eternal. Due to the lack of competitive moats, this one will mature rapidly and any golden period is likely to be short.

        Fig 5. Fragmentation into sub-forms due the changing landscape

        In some sense, these short content focused games have made a deal with the devil. They've reduced their inventive mechanical scope and deliver all their value through highly polished content. However, one constant of the game industry is that content costs are always rising on a given platform. The cost curve is the monster that eats our industry. It is great to trim 1/10th of the content in a game to get your costs down, but what happens when the cost of making content then jumps by 10X? That brief advantage disappears.


        Though I don't personally make short content-driven games, I find this lens immensely useful in understanding how and why my work impacts the world. All art is shaped by the economics of a specific time and place. All standardized forms of art are but niches within a socioeconomic ecosystem. They are not eternal, they shift over time. Knowing that common forms are not some absolute truth empowers the clever and observant developer.

        It pays to ask: Who is making money? How do the developers, journalists, museums, critics or other middlemen benefit from promoting the works that they promote? Any creative work that depends on money-making institutions (big or small) is a commercial artifact, shaped by commercial constraints. None of us are truly independent creative entities. That’s at best a pleasant illusion, a lie. We all create within systems that cull our impassioned work with pragmatic brutality. We also, like it or not, preempt this culling through self-censorship.

        The flip side of this analysis is to look at the failures.  Ask who is doing something different and failing? What structural and environmental factors explain why they are not making enough to eat? Once you've identified the problem areas, is it possible to spot gaps and come up with a new strategy that lets you thrive?

        When you see a new form of game emerging, ask why. Seek to understand the confluence of forces. Then use this rich understanding to invent your own unique form of game. Do your part to ensure that the evolution of games never stagnates.

        take care,

        Loot Drop Tables
        Posted by Lost Garden [HTML][XML][PERM][FULL] on 7 December 2014, 10:00 pm
        Many games have loot. Usually this drops randomly. Loot drops are a pretty mundane topic, but one that almost every designer runs into at some point. Here are some best practices I've encountered over the years. Many thanks to everyone who contributed to these tips and tricks.

        Your basic loot table

        The goal is to drop some set of items at a given probability. Let’s say when you defeat an enemy, you have a chance of getting shield, a rare sword or nothing at all.

            name: sword
            weight: 10
            name: shield
            weight: 40
            name: null
            weight: 50

        • Item: An item is something you want give the player.
        • Loot Table: A set of items is put into a loot table. This is just a bucket of items. For example a loot table might include: Sword, Shield, Null.
        • Weight: An item has a drop weight: 1 to 10,000. For example a sword might have a drop rate of 10.
        • Null items: One of the items in the loot bucket is 'null' which means if that is rolled, no loot is given
        Rolling for loot
        • Total probability: First, sum all the weights in the bucket. In the example above, that's 10+40+50 = 100. They don't need to add up to 100 since these aren't percentages.
        • Next assign each item a range. Sword = 1-10, Shield = 11 to 50, Null = 51 to 100
        • Generate a random number from 1 to 100.
        • Compare that number to the ranges. That's the item that drops.
        • Reroll: Generate multiple random numbers to simulate multiple rolls.
        So what does this look like to the player? We've got a 10% chance of dropping a sword, a 40% chance of dropping a shield and a 50% chance of getting nothing.

        As the designer, I could go in and change Null's weight to 100 and now I've got a 6.6% (10/150) chance of dropping a sword, a 26% (40/150) chance off dropping a shield and a 66% (100/150) chance of dropping nothing.

        Mapping onto other common random systems

        This system is a simple restating of many other familiar methods of randomness. It is a fun superpower to train your designer brain to be able to switch between understanding any randomness issue in terms of loot tables, cards or dice.

        Imagine deck of cards that you can shuffle and draw from.
        • Each type of card in the deck is an item.
        • The number of cards of a given type is that item’s weight
        • Shuffling the deck is equivalent to assigning each item to a range and generating a random number.
        • Drawing a card is the equivalent of selecting the item that drops.
        Now a normal deck of cards has 52 cards, but with loot tables, you don’t need to operate with that constraint. Your decks could have 1000's of cards and a vast array of types. Or they could have tiny decks that are the equivalent of a typical poker hand.

        Dice also map onto loot tables.
        • Each individual die is a loot table.
        • The sides (1-N) are items (labeled 1 through N)
        • Each side gets a weight of ‘1’. (Unless you are using weighted dice!)
        • Multiple dice can be represented as rolling the same loot table multiple times. So 2D6 is the equivalent of sampling a 6 item loot table twice.


        Now that we’ve defined a basic loot table, what else can we do with it?

        Variation: Items sets
        You can also drops sets of loot. An item doesn’t need to be a single thing. For example, I could extend it so that the players gets a shield and a health potion if that option is selected.

            name: sword
            weight: 10
            name: shield
            name: healthPotion number: 2
            weight: 40
            name: null
            weight: 50

        Variation: Always drop
        A common need is to flag an item so it always drops. One convention is that items with weight '-1' always drop.

        Variation: Repeatable randomness
        Sometimes you want to be able to repeat a random roll. For example, when a player saves a game and then is able to reload to avoid a bad loot drop, it can lead to very grindy player behavior. If there is an exploit that ruins the game for them, most will happily go for it.

        Most contemporary pseudo random number generators use a seed value. As long as you can save that seed value, you can run the random number generator again and get the same result.

        Variation: Rolling without replacement
        The problem with the system above is that players may, through chance alone, always roll 'null'. This is a common complaint by players. “I played that encounter 3000 times and never got the MegaGoldenLootGun!” This can happen.

        In statistics, there are two fundamental types of sampling:
        • Sampling with replacement: You pull the numbers out of the bucket and then after you've recorded what you got, you put them back in. So you have the same chance of getting the same thing again in the next draw.
        • Sampling without replacement: You pull the item out of the bucket and once you’ve recorded it, you set it aside. You have a lower chance of getting that item again and thus a higher chance of getting the remaining items.
        Tetris uses sampling without replacement. Each set of Tetris pieces is in a loot table. Every time you get a specific piece, it is removed from the bucket. That way they guarantee that you’ll always get a long piece if you wait long enough.

        Here’s how you implement rolling without replacement in a loot table.
        • When you roll an item, reduce its weight by 1. This shorten its range by 1 and shortens the max range by 1 as well.
        • Keep the player's modified loot table around for the next time you roll.
        Variation: Guaranteeing specific drops
        Sometimes even rolling without replacement isn’t fast enough and you want to guarantee a loot drop. Blizzard does this for certain rare drops so that players don’t grind for very long times.

        You could just increase the weight, but a low chance of getting something with a guarantee can feel very different over multiple plays than a slowly increasing chance of getting an item.

        Here’s how you implement guaranteed loot drops.
        • When you roll any non-guaranteed item, reduce all non-guaranteed items weight by X%
        • X = 100 / Max number of rolls you before the guaranteed items drop.
        • Keep the player's modified loot table around for the next time you roll.
        • Suppose you want the sword to always drop after 5 turns even though it it only has a 10% chance of dropping.
        • So X = 100 / 5 or 20%.
        • So every time you don’t roll the Sword, the weight for the Shield drops 8 (40*0.2) and the weight for null drops 10 (50*0.2)
        • After 5 turns, the weight for all the other items will be 0 and the sword will have a 100% chance of dropping.
        Variation: Hierarchical loot tables
        Loot tables are generally source for new resources. However, you can easily run into situations where you are dropping too much or too little of a particular resource. Some sort of constraints would be helpful.

        One solution is to use hierarchical loot tables without replacement. When a particular resource runs out, the player doesn’t get any more. We’ve used this for our daily coin awards. We want to give out 100 coins a day, but no more. But we want to do it as part of the loot system.
        • Create two tables: Rewards and DailyCoins.
        • Have the main loot table reference the Daily Coins bucket.
        • When Daily Coins get picked, roll that table and see how many coins you get.
        lootTable: Rewards
            name: sword
            weight: 10
            name: dailyCoins
            weight: 40
            name: null
            weight: 50

        lootTable: dailyCoins
          type: noReplacement
          refreshRate: Daily
            name: coin, number: 1
            weight: 10
            name: coin, number 10
            weight: 4
            name: coin, number: 50
            weight: 1

        In the example above, a player has a 40% chance of getting coins. Then we roll the dailyCoins table and see that they can win a maximum of 100 coins a day with 10 awards of 1 coins, 4 awards of 10 coins and 1 award of 50 coins.

        When the dailyCoins loot table is emptied, they’ll get nothing until it refreshes after a day.

        Variation: Conditional drops
        Sometimes you want to test if you should drop the items base off some external variable. In Realm of the Mad God, we wanted to avoid free riders getting loot for a boss kill without doing at least some damage. So in the loot table, we added a check. If a valuable item in the loot table was rolled, then we'd check to see if the player had done more than X% of damage to the enemy.

        You could also build in switches for which loot it valid based off player level or even enemy level. I tend to instead use multiple smaller loot tables, but the system is flexible enough that you can easily architect your data with a few large tables and use of conditionals.

        Variation: Modifiers
        You can also modify the quantity or weight of a drop based off some external logic. For example, a player with a skill in harvesting could yield 2x as many of a particular item drop compared to a player without that skill. Or you could modify the weight. A high level character might have a -50% weight for all items marked lower than their level. (Thanks to a Reddit commenter for this idea)

        Other uses

        Drop tables are commonly used for dropping loot. But I also find them useful in other areas.
        • Procedural generation: Use a table to build weapons or characters from components
        • AI: Use a table to select behaviors such as attacks or moves.
        This may seem a little silly..surely there are better ways to model AI! However, one way to think about randomness is that it is a very rough first order model of any system. How does the human brain model a system? We make an observation about a system. We note the frequencies and tendencies for those observations to reoccur. It is only much, much later that we start to understand ‘why’ something happens or the causal relationship between parts.

        In physics, we often joke that in order to model a cow, a complex biological organism, the first step is to ‘imagine a spherical cow’. By creating a simplistic, easy to work with model, we can often generate useful insights at a very low cost.

        Many times, a drop table is a ‘good enough’ human-centric approximation of a complex system. For many systems, most players will never move beyond a basic probabilistic understanding so modeling more complexity is a waste of time. Efficient game design is an exercise in modeling elements only to the minimum level necessary to create the desired experience.

        Consider: D&D modeled entire universes with what were essentially loot drop tables. That was a deliberate focus on minimizing systems that were in many ways just secondary flavoring to the core roleplaying.

        A loot drop table isn’t the only tool you need, but in many scenarios, it is good enough.

        Procedural generation thought experiment

        Here’s a simple procedural generation system using drop tables. There are lots of other ways to do this, but this is more to get your brain thinking.

        Let’s say you want to build a procedurally generated enemy
        • Start by making a list of unique enemy parts. Maybe your enemy is made up of a type of movement, a type of attack, a defensive buff and a type of treasure.
        • Make loot tables for each one of those parts.
        • For each item in the loot table, give it a power value based off how powerful you think it might be. for example, a knife attack might be weak so it only has a power of 5. But a large hammer attack might have a power of 15.
        • Create another loot table of buffs. These are modifiers to various attributes. For example, ‘Strong’ boost a value on an attack by 20%. You can have debuffs as well ‘Weak’ might diminish a value by -50%. These have reduce the power value of a part.
        Now let’s generate an enemy
        • Set a target: Set a target power for your generated enemy. Say you want an enemy of power 40
        • Roll: Roll each of the parts once and add them into a list.
        • Score: Add up all the power values to get a score.
        • Adjust: If the sum of the parts is over the target, add a debuff or roll for a lower power part. If it is under, add a buff or roll for a higher power part.
        • Repeat: Repeat this process until you hit a desired error threshold (distance from power 40) or you've exhausted the number of iterations you are willing to spend.
        You now have a procedurally generated enemy. There are tons of tweaks you can do to this basic system, but it works most of the time. As an exercise, think about:
        • Exclusion lists: If two parts are picked that are on the list, throw the enemy away and reroll.
        • Multiple constraints: Parts are scored on multiple criteria. Note, the more constraints you add, the less likely you are to converge on a viable result.


        Any time there’s a discussion of randomness, there’s a huge number of secondary issues that come into play. I recommend the following for further reading:
        Resist being dogmatic about randomness. Be a broadly educated designer whose aesthetic choices are based on hands on experimentation. A good rule of thumb is that you can't intelligently critique a design tool until you've made a couple games that use it successfully.

        Anyway, this is just how I've done loot tables; a mundane part of any working designer's life. I'm curious if other folks have other ways of managing loot (and randomness) that they love and live by.

        (And before I forget – I've recently freed up some time to do some games consulting. Ping me if you need help with your games!)

        take care,

        Top 5 design debates I ignored in 2014
        Posted by Lost Garden [HTML][XML][PERM][FULL] on 23 December 2014, 4:42 pm
        Back in the 80’s and 90’s, when conversation about game design was first bubbling up out of our community of insecure practitioners, a few polarizing topics would arise again and again. You’ll recognize them:
        • The correct definition of ‘game’
        • Narrative vs Mechanics
        • Randomness vs Skill
        • The importance of realism
        • Casual vs Hardcore
        Many were (and are) merely the irritated observations of game players picking at specific games. However, with a flip of the rhetorical switch, players become designers expressing a universal design truth. Opinions inevitably differ and thus positions harden in the absence of data. And it snowballs from there.

        Thankfully, as a developer community, we've grown older. With time and the accumulation of thousands published games, experienced game makers have a lot more insight into how game design actually works. It turns out there’s plenty of room for nuance.

        There’s also the growing maturity to ignore false dichotomies and worn out talking points. Honestly, we don’t have time any more. We should be making great games, not arguing ancient design politics.

        In the spirit of becoming a forward looking designer, here are my top 5 design debates that I've ignored in 2014.

        #1 The correct definition of 'Game'

        I've seen a metric ton of definitions for game over the years and have dabbled in crafting them myself. Not a single one has been useful to me in my daily practice of making great games.

        Why this discussion is outdated
        Games are vast and varied. A single definition tends have one or more of the following issues:
        • Overly broad: The definition is unable to provide any direction or guidance.
        • Overly narrow: The definition eliminates useful tools and influences from other areas of systems, thought or art.
        • Overly convoluted: The definition is only useful to lawyers who care primarily about edge cases and not about getting things done.
        Alternative discussions to have instead
        I focus on finding and exploring useful design tools. I don’t need to care about the definition of ‘woodworking’ in order to be damned happy that hammers and nails exist. The same goes for games. I focus on scaffolding. And loot drop tables. And internal economies.

        A useful goal is to find general tools that a smart designer can use to radically improve their work. Like any tool, they should to be applied in the proper context. So they are rarely universal or one-size fits all. And like a craft tool, they need to be applied with skill. They aren’t a pattern that you toss at a problem and get a fixed result.

        Recommendation: Build your flexible design toolbox. Master those tools. Apply them where appropriate. Ignore pedants obsessed with defining ‘game’.

        #2 Narrative vs mechanics

        Science was once plagued by the idea that certain behavior derived entirely from genetics (nature) or entirely from environmental effects (nurture). This turned out to be a naive simplification of a vastly most intricate and interrelated system genetic predispositions, environmental triggers and feedback loops.

        Narrative and mechanics have proven to be similarly intertwined.

        Why this discussion is outdated
        In the end, the human brain has neither a pure systemic understanding the world. Nor does it have a purely narrative understanding of the world. Memory, learning, emotional triggers, cause and effect all feed into how our brain adapts to environmental mechanics and then flow out again as a social response.

        So the model suggested by the supposed conflict is simply broken. There is no ‘versus’.

        There are many explanations for how this argument even arose. My favorite: A cocky tribe from old linear media clashed with an isolated tribe of game makers. They fought a stupid fight about authority and status that had almost nothing to do with making games. Meh.

        Alternative discussions to have instead
        A modern discussion could include:
        • What existing schemas are activated by my game?
        • How should we implement learning and scaffolding structures?
        • What is the impact of various forms of stimuli within game loops?
        • How should we tighten or loosen our systems of cause and effect?
        • What are systems of pacing?
        • What social role does narrative serve? How can we engineer human systems to encourage it?
        Theories like Interaction Loops or Emotion Engineering integrate narrative and mechanics. In the process of banging our heads against building great interactive experiences, we've been forced to break down ‘narrative’ and ‘mechanics’ into atomic chunks and see how they fit in practice. Let’s discuss the rich synthesis of story, world building and mechanical techniques that thrives in interactive systems.

        Recommendation: Consider how narrative emerges from existing mechanics. And consider how theme illuminates mechanics by activating existing mental schema. We need holistic, integrated models. Ignore antagonistic dichotomies.

        #3 Randomness vs Skill

        There’s been a sad resurgence of this 80’s wargamer rant. Randomness is obsessively derided as less masterful or strategic relative to pure skill games.

        Why this discussion is outdated
        Randomness is just another design tool. Used with skill, it yields some amazing games.
        • Random systems are rife with mastery. ‘Randomness’ can provide strong elements of mastery, in terms of learning distributions, managing options and adapting to new situations.
        • Games involve loops. Random outputs almost never occurs in isolation, but are part of an internal game economy. Randomness is often an essential tool for creating strategic variation and context.
        • There are different, equally valid playstyles. Not everyone is a rigidly intellectual young man who desires only mental-skill games that let them dominate others. Some play to relax, some to socialize, some for physical mastery, some to feel part of a shared purpose. Randomness can be a beneficial tool when designing for these players.
        Alternate discussions
        • What games use randomness in interesting ways?
        • How does your game use randomness as skill?
        • How does randomness map onto noise?
        • What are other noise generators? Complexity noise, social noise, feedback noise, etc.
        • How do we make people better through play?
        Recommendation: Practice using randomness where appropriate. Explore the space. Make a game with randomness that is about mastery. If you happen to be someone that values intellectual rigor over chance, make a game for someone other than yourself. Stretch your humanity.

        #4 Realism

        Past futurists sold a vision where games must inevitably become indistinguishable from reality. We marketed the hell out of that vision to the point it became dogma. You bought a new console, a new video card, a new computer to creep ever closer to the dream. You argued for 1080p as a paladin fighting for the glorious Holodeckian cause.

        Why this discussion is outdated
        Realism in graphics or simulations no longer is a dominant goal for most game developers. In practice, it turned out it wasn't really an essential feature for a successful games. In our far future era, you can snub realism and still make a billion dollars with a game like Minecraft or Puzzle & Dragons.
        • Realism has niche appeal. It is an aesthetic choice that tends to appeal to a singular sub-culture that we've trained with our decades of marketing. Cartoons, text and other stylized forms of representation are also appealing.
        • Realism can be an unnecessary expense. We sometimes wholesale replicate reality when we don’t know what specific stimuli actually appeals to players. It is sort of a shotgun approach that wastes vast amount of effort to hopefully make something interesting. A substantial portion of the exponential escalating cost of game development can be attributed directly to the pursuit of realism.
        • Simulation adds design risk: Many simulations are complex and difficult to manipulate. They also are not inherently emotionally satisfying. Insisting on mechanical realism while simultaneously trying to make a fun game tends to yield failed game designs.
        • Games are also endogenous systems of value. They are like little self contained baubles of math that set up interesting internal relationships. A game like Tetris has immensely value independent of references to the real world.
        • When players ask for realism, they often aren't asking for realism. The desire for realism is often best understood in terms of how players learn and apply existing mental schema to new system. A request for realism could be: A new player asking for a metaphor that helps them understand an abstract system. Or it could be an advanced player pointing out unnecessary edge cases. Both these have solutions outside belabored realism.
        Alternative discussions to have instead
        • What is the right art style for your audience?
        • What are the trade offs between art style, production concerns and budget?
        • What sort of math or systems are interesting independent of their appearance in the real world?
        • How do we make game-like, cartoon-like, info rich, surreal virtual reality games?
        Recommendation: Ask what utilitarian feedback your game truly needs. Invest your art resources making those elements amazing. Ask what level of modeling a system needs to create rich gameplay. Invest your design resources to create a tiny rule set with deep emergence. Be smart. Be frugal. When someone demands realism, try to figure out what they really want.

        #5 Casual vs Hardcore

        There’s a set of cultural stereotypes that casual players act one way while hardcore players act another. A surprising number of design decisions are made based off these stereotypes.

        Why this discussion is outdated
        The casual and hardcore stereotypes suffer from the problems typical of stereotypes. They are gross simplifications that yield the incorrect design decisions.
        • Many of the stereotypes are simply wrong: The longest average playtimes? Not console or PC. Handheld games, particularly those ‘kiddy’ Nintendo titles dominate session length. Regular daily play happens more often on smartphones and tablets than it does on consoles. When I look at data, there are very few ‘casual’ or ‘hardcore’ stereotypes that hold true. And when they do there are massive exceptions. 
        • The variation within a specific game is huge: You've got a half dozen or more distinct playstyles within almost any game of reasonable complexity. Each game is a vast city with many different people living within it. Mere averages tell you very little about how to improve the state of your game.
        • The market is shifting: Service-based games are driving for improved retention by doubling down on play. Women are playing more. Console owners are aging and slowing down. A lot of the old lessons about demographics and play styles have shifted. And they’ll continue to change in the future.
        I see ‘casual’ or ‘hardcore’ as poisoned tribal labels like ‘gamer’ or ‘skinner box’. Mostly they are just weaponized stereotypes, deployed to enforce perceived group boundaries. They have little productive place in a modern design (or marketing) discussion.

        Alternative discussions to have instead
        • How do you break out of thinking in cheap stereotypes in order to gain an advantage over the dinosaurs that don't see the market has it truly exists?
        • How do different groups unique to your game behave? (Hint: We can get the data!)
        • What motivates the groups unique to your game?
        • How do you include diverse hooks to appeal to multiple passionate audiences?
        • How do you make a targeted niche game using iteration with a live community?
        I personally tend to make games that look 'casual', but consistently melt the brains of self identified 'hardcore' players trained on endless tutorials, cut scenes and QTEs. Some of the best players are smart 30-40-year old women that have the intense mental stamina for activities like logic, planning and creative thinking. They thrive on hard games. My market doesn't even exist if you see the world through a 'casual / hardcore' lens. Yet there it is, merrily enjoying games amidst the vast diversity of this planet's billion odd players. 

        No one really makes 'hardcore' or 'casual' games. At best, we use existing markets, tribes and distribution channels to get a tentative foothold in a player’s psyche. But then it gets complicated. Embrace the complexity of your players. Learn who they actually are. Create elegant solutions that serve your many types of players.

        Thoughts for 2015

        If you happen to find yourself facing these 5 topics: Turn away. Our creative lives are limited. Pour your time into something productive.
        • Teachers that spread these memes: Consider teaching modern game design tools. Cull disproved dogma. 
        • Academics that expound on these ideas: Stop naive theory crafting and start referencing nuanced data from working designers.
        • Students that gnaw at these bones: Arguing ancient talking points in comment sections gets you nowhere in life. Make games instead. Base your design conversations around your hands-on experiments. You'll learn more, faster. 
        Goodness knows that conversations on dead design ideas will not end. Players and their innumerable derivatives (fan press, forum warriors, cultural critics, etc) continue talking about these topics. Some talk for entertainment. Some for status. Some for business. Some talk about their game experiences in order to process them mentally and emotionally. For many of these purposes, simplistic polarizing hooks are more enticing than deep comprehension.

        So these inane design views become practically tradition, or at least common hazing rituals. Like yelling at televised football games. Or laughing at trucknuts. Sure, players aren't having a productive craft conversation, but they shouldn't be judged by the same rubric. Consider their chatter a cultural performance.

        As for designers, you have a different role to fill. Recognize when you are accidentally acting like a uninformed player or student. Instead of getting caught up in the babble of ill-informed internet backwash, try talking directly with other working designers. Build tools and knowledge together.

        Here's to a more productive 2015,

        Minimum Sustainable Success
        Posted by Lost Garden [HTML][XML][PERM][FULL] on 12 April 2015, 11:35 pm

        Let’s dream for a moment about sustainable game development.

        Game development is inherently unstable. Technology, markets, profit margins and teams shift regularly. Any of these can quickly destroy a previously comfortable business. Individual game developers end up dealing with unexpected layoffs, last minute moves across the country (or across the world) and a level of uncertainty can damage our relationships and long term happiness.

        In order to simply make ends meet, you end up compromising your dreams, for years. Or decades. Game development exemplifies Schumpeter’s creative destruction on an accelerated scale with intensely personal consequences.

        So what is required to build an oasis? A place where, at minimum, one might make games at least without having your beloved team or your bank account regularly exploded.

        This essay covers some of numbers behind reaching success as a developer of premium games in the current market. I don’t offer solutions, but you may find some of the concepts useful.

        The uninteresting case

        There are obvious examples of extreme success. If you happen to make a game that personally earns you 10 to 30 million USD after taxes, you can likely devote the rest of your life to game development. You may not have enough to fund larger teams, but given reasonable budgeting, you’ve at least covered your expenses until death. For every additional teammate you need to make games, add another 10 million to your lifetime game making budget. (You may not want to actually spend your own money, but that’s a different discussion)

        For those of you who find your gilded selves in that particular pickle, well done. None of the rest of this essay is meaningful to you.

        Minimum Sustainability

        What are the borderline cases? Imagine a glider that slowly drifts downwards, but manage to catch just enough of an updraft to never quite crash.

        The following are some ideas pertinent to surviving long term in a hit driven media industry.
        1. Defining success: Success rates, Size of success, Variability
        2. Tactics for surviving the odds: Budgeting, Prototyping, Hobbies, Revenue streams

        1. Defining success

        Success rates

        In the 90s, Sierra expected 1 out of 4 games to be a success and pay for the other products that failed to turn a profit. Recently, Mike Capps, the previous president of Epic, claimed that he couldn’t promise more than a 10% chance a game would be a success. If you made 10 games, on average, you’d expect only 1 would be considered a success.

        Success rate is simply the ratio of ratio games that hit some threshold of financial success vs the total you’ve released. It is never 100% and can range from 1 to 25% based on the particular market you are in.

        Over time success has been dropping. 25% is almost never seen in modern game markets. Tools are cheaper, distribution platforms are more open and there’s simply a much larger supply of games today than there have been in the past. The number of game players has increased as well, but far slower than the vast increase in developers. Given a set of equally competent games, only a fraction will become profitable.

        I typically think of success rates in the context of experienced developers. These are numbers coming from professional developers that are already using every trick in the book to mitigate risks. They are making sequels, they are leveraging existing relationships, they are selling to their fan bases.

        When I talk about probabilities in game development, I’m by no means saying that success is all due to luck. Instead, it is merely acknowledging that even when you do everything you possibly can there are still huge risk factors that are out of your direct control.

        You might as well plan for only a small chance of success with an individual game. This isn’t being negative. Smart people make good money off probabilistic systems every day.

        Size of success

        How big of a success is actually a success? There are many definitions of success out there. For the purposes of this essay, let’s consider making enough money to not go bankrupt the first tier of success. At the very least that means paying for your failures.

        The first thing to realize is that not all profitable games provide long term success.

        If you make 10 mobile games for $100,000 a pop.
        • Brutal failures: 3 make a total of $153.02. They didn’t get featured by the app stores and were lost in the sea of obscurity. Pretty common, though people tend to be shy about discussing their failures.
        • Moderate failures: 4 make $50,000!
        • Break Even: 2 games break even. Everyone talks about them as if they were a success.
        • Success: Only a single game earns $1 million. It needs to earn 10X its cost to cover your million dollars in total dev costs.
        What happens if that profitable game make $600,000? It earned 6X its costs! You made a profit of $500,000, enough to make 5 more games. However, you are still on the long road to bankruptcy, despite an apparent success. There’s only a roughly 40% chance those 5 swings at bat will result in a success. Long term, you’ll find yourself out of money or in debt.

        I regularly hear press or indies trumpeting that a team broke even or doubled their money on a project and I cringe. I’m happy that they got a scratch off ticket to play again. But these are the same developers that are quitting the industry or sunk into despair when a game or two later they’ve run out of money.

        It is a disservice to other developer to claim that a breakeven project is a financial success. Break even means almost nothing. You are still on the knife’s edge of baseline survival and should operate financially exactly as if you had achieved nothing.


        Even studios that have successes that are 10X their average project cost still end up going under.

        Flip a coin 20 times. On every 1 out of 2 times should be heads. But you don’t get a pattern of alternating heads and tails. You get streaks. You may see 10 heads in a row. This is within the bounds of chance. However, if you really needed tails to come up, you are in a lot of trouble.

        Random systems have natural variability and game development does as well. The best team in the world can strike out 10 times in a row. It is just as likely for your failures to be front loaded as it is for your success. So not only do you need your success to pay for the average rate of failure. You need it to pay for the worst possible luck.

        The more buffer you have, the longer bad luck streaks you can survive. At the very least, add a few expected failures into your success rate calculation. It isn’t a perfect tactic, but it helps you deal with bad luck in addition to mere average luck.

        What I personally consider a successful project
        At Spry Fox, in the past 5 years we've accumulated the following numbers:
        • 31 projects started as prototypes.
        • 20 smaller prototypes that also didn't pan out. Some took months, others took days.
        • 11 released projects
        • 4 that didn't make money (both brutal and moderate failures).
        • 4 break even projects
        • 3 outright successes.
        For us a success means a released project makes back 5 to 10X its production cost. That is what pays for all the prototyping, failed projects and general poor dice rolls.

        I was surprised to note that of our prototypes, roughly 1 in 10 end up being a successful project. I assumed we had a lot more horrible prototypes than apparently we do. For released projects, we are closer to 1 in 3 being successful.

        That’s better than expected. But it does make me mildly worried that a bad luck streak is on the way. It would be completely fair to suggest that our successes were front loaded and our actual success rate is lower than the current small sample indicates.

        However, the most important aspect of these numbers is that we are aware of them. They limit how much we can spend on a project and how much we could keep in reserve.

        2. Tactics for surviving the odds

        There are a vast number of techniques that help deal with the variability in game development. The following, however, are ones that don’t fundamentally alter the odds. They help you survive the odds, which is a very different goal.

        Basic Budgeting for Sustainability
        It is very common to spend too much money making your game. At minimum ask the following questions:
        • Target Revenue: How much do you expect to make?
        • Success Rate: What is chance of making that much money?
        Your budget is likely Target Revenue * Success Rate. So if there’s a 10% chance of reaching $500,000, you should spend $50,000 on each project. That’s 1 full-time experienced developer for 5 months assume pay of $10,000 a month. Or if you underpay yourself relative to what you might make at comparable jobs and spend 10 months at $5,000 a month.

        These numbers should look scary. They suggest that the vast majority of indie developers are ripe for financial ruin and are operating primarily on hope instead of any rational financial strategy. I think that’s accurate.

        Low cost prototypes
        Notice that the numbers I shared for concept success rate are quite similar to Mike Capp’s 10%. However, our released games have a much higher success rate (30+%). The reason for this is that we prove out the gameplay early using a low cost pipeline of low cost prototypes.

        These prototypes cost dramatically less than a released game. Some of those 30 prototypes only took a couple days with a single programmer. By disproving bad ideas early, we put real money into games that have a much higher chance of success.

        Releasing on multiple platforms
        Each time you release a game on a new platform, you get to roll the dice all over again. And you do it a much lower development cost. Triple Town was only a break even game on the eInk Kindle. It was a true success on Android and iOS. If we had stopped after the first release, I would have considered Triple Town a financial failure.

        Using designs and technology that quickly and cheaply transfer to new platforms reduces your porting costs and decreases the size of success you need to remain in business.

        Operating as a hobby
        One of the trickier aspects of sustainable development is the need to pay for food and housing. What if you can pay for those costs through some other means than games making money?

        Some typical paths.
        • Contracting: You can save up money working for someone else and then spend that money on a period of full-time development. The cost here is two fold. Development goes more slowly and long term you average wage is lower.
        • Working at night: You work a full time job doing something else and then spend evenings and weekends making your game. The cost here is that work goes much slower. It is also not likely to be your best work since it is difficult to maintain quality while working more than 40 hours a week. You also bear the opportunity cost of sacrificing your leisure time to making games.
        • Supportive spouse or family: Someone else in your family makes enough money that you have the leisure to work on games full time. The costs to the artist are generally low. The dominant one is a reduction in household family income. A great situation if you can manage it.
        We don’t talk about it much, but a large number of successful ‘professional’ artists are in a relationship with someone else that pays their way. They aren’t successful entrepreneurs with a deep understanding of sustainability. Instead they are full-time hobbyists in a fortunate financial situation. They accumulate excess leisure time and spend it on game development.

        This sort of blessing is very difficult to admit. But embarrassed silence dupes less fortunate artists into pursuing an unrealistic fantasy of how to thrive. If you are a kept developer and are living off someone else’s money, talk about it. Indie finances could use a little sunlight.

        Longer term revenue streams
        Premium games tend to have spiky revenue streams focused around launches and special sales. Financial instability is built into the business model.

        Here are the most common ways of adding a dash of stability.
        • Franchise: A long term game franchise where sales come from promoting sequels or remakes. This tactic is regularly practiced by conservative large companies, but also works for smaller operations like Spiderweb Software
        • Eternal updating: Continually update a game and making some noise about it. Toss in some sales. For most titles, this tends to drop off after a year or three. A consumable game tends to not be an evergreen business asset.
        • Freemium: Make a game service and build a stream of revenue. This requires that you know how to run a freemium business. It is an uncommon skill set for an indie, but quite valuable.
        These give you a base layer of predictable revenue. As long as your burn rate as a company doesn’t go wildly over your income stream, you can keep making games.

        These revenue streams have been our goal as a company. We are looking to build long term games that produce a steady stream of revenue from a community of dedicated players. This isn’t an easy target to hit, but at least we are building games with that conscious aim in mind.


        The big lesson is that your exposure to luck is something you can manage. Think about releasing a portfolio of games, only some of which will be a success. And you should budget in such a manner that you can afford to make that portfolio. Blowing your existing capital on a single title is almost always a dumb idea. Sometimes it pays off. Most of the time, it doesn’t.

        However, it is also worth realizing that playing the premium market straight on is, by many measures, a sucker’s game. The standard bet is to lose money on 5 to 10 games and have one success that lets you do it all over again. For most companies, the house always wins in the long run.

        Perhaps the longer term solution is to run your games as a service. Try to create a product that produces reliable cash flows. This likely require a certain level of business thinking. You are making a financial machine that lasts instead of a Hail Mary piece of art that vanishes.

        Autumn of Indie Game Markets
        Posted by Lost Garden [HTML][XML][PERM][FULL] on 17 November 2016, 12:21 am
        Photo by Rosa Dik

        Ah, the fall. A time to reap what has been sown and contemplate the cycles of the seasons.

        If you are a smaller game developer, you’ve likely noticed some cyclical shifts in how we make games. Games are looking nicer than ever, don’t they? That quality bar keeps creeping higher. With so much work to do, your team is a bit larger. And with so many mouths to feed, it feels riskier to lose everything experimenting on wacky new game mechanics. Luckily, it is pretty clear which genres will yield the breakout hits you need to keep going. It is too bad that there’s a such an abundance of similar games; it feels like you can’t even give them way.

        What changed?

        Remember when we had a revolution? One person teams could make original games with minimal content and strike it rich. Doodle Jump was a thing! A hit indie game like Braid cost a minuscule $200k to make. A developer and some lovely art and there was a complete top tier game. Press wrote about it.

        But it feels if such games were released today, they’d likely be left to rot in obscurity. A modern hit by a “small” team is a game like Battlerite. 25 developers, lush 3D graphics, external funding. An order of magnitude increase in costs over a period of eight years.

        To everything there is a season, and game markets follow predictable patterns of growth, harvest and if you’ve been luckily enough, stockpiling for the coming frost.

        Have you been making games for less than 10 years? Are you a newer smaller indie developer who has only ever known the bright fields of opportunity known as Steam, console downloadable or mobile platforms?

        Here’s what is coming. Here is what happens when game markets mature.

        Memories of spring

        Historical context matters.

        A new game market opens when a new way of reaching eager players appears. In the early 2000s, digital distribution was a technology that cracked opened an industry previously dominated by retail sales. Apple and Google enabled phones to download games. Microsoft, Sony and Nintendo enabled consoles to download games. And Steam created a cohesive and reliable ecosystem for PC players to download games.

        If you don’t remember the retail era it is hard to overstate what a radical change digital distribution was to the dominant business models. In retail, about 15% of revenue went to the developer. The rest goes to marketing, publishing and the retail store itself. This creates a power differential that tends to squeeze creativity out of game developers. Forget tales of wide-eyed idealism. Retail game development was a factory job that churned out games tailored to the whims of a giant box shipping machine. This was a mature market with most major game developers owned art and soul by middlemen publishers or platform owners. AAA still follow this model to a large degree. Good people, bad system.

        Two things happened when digital distribution hit. For the first time in ages, we saw high demand and low supply.

        High demand: Platform owners pushed their new distribution platforms heavily. A platform much preferred a guaranteed 30% cut of digital, especially when compared to a paltry 0-20% cut of retail. Valve bundled Steam with their top selling games. Microsoft gave away prime real estate on their console dashboard. Apple and Google directed users to go through their storefront in order to do pretty much anything. The result is a torrent of customers flooding through these digital stores wanting to buy cool stuff for their cool new toys. Put a pretty picture and a buy button and bam, you’ve got a sale.

        Low supply: But there wasn’t anything to buy. A lot of traditional game publishers didn’t want to risk being beholden to some new platform master. Every digital storefront is essentially a monopoly with the potential to exert absolute dictatorial control. So most publishers held back. A few fringe game developers put up games. These were the hippies and hobos whose niche products never broke into the more mature retail markets.

        And their games sold like hotcakes. In large part because there was nothing else to buy. For a while it felt you could put almost anything up on a digital market and turn a profit.

        Short hot summer

        With digital distribution, anyone with a computer could make a game and release it. And because they kept 70% of the revenue, they needed to sell a lot fewer copies to make ends meet. This means lots of little game companies. Call them ‘indies’.

        Most were untrained. They didn’t understand how to run a business. Many had never made a professional game before. So they experimented, often wildly. Bizarro mutants popped up. Journey. Day Z. Tower Defense. What can you do with the internet? Or Flash? Or a touch screen. Or a one person team? Who knows; let’s just try something. Will Wright, gushed about the “Cambrian explosion”. New genres were born. That was 2008.

        What a time. I look back on it fondly.

        End of the growing season

        Low barriers to entry
        But low market barriers mean new developers just keep flooding in. And the nature of digital distribution means games never truly expire. So the back catalog of great games grows larger and larger. This is no longer a low supply market.

        Fixed demand
        Nor is it a high demand market. Consoles are stable. Smart phones (aka phones) are no longer setting growth records. PC sales are dropping. All those digital customers are a known quantity, divvied in zero-sum fashion across the various DRM locked platform fiefdoms.

        What happens to a market when demand is fixed and supply is high? Competition. Here’s the traditional logic. The following sequence has played out across thousands of games and dozens of markets.
        • Standardization: Players form communities around the most popular game types. This creates a standardized demand.
        • Competition: Developers try to capture the entertainment dollars of these communities by releasing games in the same genre. For example, they might release a MOBA.
        • Winner takes all: Players gather around one or two high quality, well marketed examples within genre. Those games earn the vast majority of all revenue.
        • Escalating costs: In order to win that top spot, Developers invest heavily in art, narrative, marketing events and monetization. Maybe you can beat your competition by simply doing more.
        • Bloat: This results in larger developer team sizes. Larger teams burn more money, leaving less margin for mistakes.
        • Risk avoidance: A culture of risk avoidance dominates. You must make proven games with proven themes resting on proven mechanics for a proven audience. Layers of decision hierarchy grow to eliminate exuberant impulses. ‘Wasteful’ experimentation is deprioritized. All focus is on servicing the nuanced needs of expert (high value) players in an existing genre.
        What success looks like
        There are three broadly successful long term strategies for independent developers in this newly competitive market.
        • Become a genre king: Have a hit game in a popular genre. Invest those profits in ensure that you have the best developers, community and marketing to own that audience. Set the standard that all others hope to achieve. Be what Blizzard was to MMOs. If you pick the right maturing genre, you can gain 10 to 20 years of stability.
        • Dominate a niche: Find a niche that only appeal to a wealthy but passionate audience. Become hyper efficient at serving that niche. This isn’t so different from being a genre king except no one cares about you. The press barely cover you. The broader population of gamers doesn’t really know you exist. But a small devoted community cares. So you scope your company to the tiny size it needs to be to serve a tiny market. Artemis Spaceship Bridge Simulator or SpiderWeb’s retro RPG games are good examples.
        • Manage a brand: There are a handful of companies that have a powerful brand they used to secure funding. During hard times, they essentially freeze dry themselves. This minimizes costs until the next deal comes along. Jackbox is the most common game industry example.
        False success of having a hit game
        There’s a ton of money flowing through a maturing market and occasionally it arcs over to the random indie in the right place at the right time. Zot! A jigawatt of revenue powers them for years(!) without additional income.

        But the result is a lesson in exponentials. Ever play one of those new fangled idle games like Cookie Clicker? As markets mature, escalating exponential costs rapidly consume existing savings. For example: A top shelf ‘Triple-I’ indie’s last game cost $200,000. They made back $2,000,000 in sales. But their next game costs $2,500,000. Maybe they make that back also. Maybe they don’t. The money in the bank only gives them 1 or 2 additional swings at bat, not 10.

        We now use the term ‘Triple I’ for medium sized teams that had hit games, but we used to call that same spot in the ecosystem ‘midtier developers’. They all died off as markets continued to mature. It becomes increasingly hard to roll a hit every time. In the end, they had no sustainable advantage.

        Selling the farm
        So not everyone can stay independent. There are three common outcomes for those forced to give up ownership.
        • Hobbyist: The team becomes a non-commercial endeavour. Either people get a day job and work a few hours at night. Or their family support them. Or they get grants from some institution interested in their work. Or they make games as students and change careers later.
        • Hire yourself out: The team becomes a contractor to someone with money. This can be via a publishing deal. Or via outright purchase. Or you actually sign a contract to perform specialized labor like porting or multiplayer development. Mega studios love hired help.
        • Extinction: The team goes out of business. That whole ‘indie’ thing was neat while it lasted.

        First frost

        You may be curious what winter looks like. Here’s what is coming up for PC, console and mobile.

        Consolidation: When a bigger company eats a smaller company..or a smaller company implodes and a bigger company hires their employees, we are seeing something called consolidation. Lots of little studios turn into a smaller number of bigger studios.

        Consolidation is a longer term process that will play out over the next 4 to 8 years. These forces don’t apply equally to every team. Some developers earned enough from a hit game they can ride along for many years without confronting their inability to make another hit game. Others are willing to starve for a few years longer before they make any hard decisions. Be patient.

        Distribution scarcity: It has already become increasing difficult to get your game in front of new players. The sheer number of games is part of the issue. Also audience capture and advertising cost (see below) limit the general availability of free customers.

        Audience capture: The available audience will actually shrink as high value players are locked into long term service-based games like MMOs or other F2P titles. A player doesn't ‘beat’ a game like Clash of Clans; instead they play one game exclusively for years. F2P companies will attempt to stretch the lifetime of their player to decades. These players are no longer looking for a fresh new games so they are typical unavailable to studios making new games or trying to replace churned players.

        Majority of studios priced out of buying ads: The ad market sells its inventory to the highest bidder (across a myriad of categories) And for games, the highest bidder is the game with the strongest Life Time Value (LTV). Do you have a high LTV game in a particular category? Great, you can buy ads that juice your player acquisition. If you have a low LTV game (all premium games, most experimental games, most independent games) effective ad-based distribution is priced out of your reach.

        Fewer, bigger hits: As the market consolidates around a handful of high value genre leaders, they will earn enormous amounts of money. The downside is that fewer small developers will capture enough sales to stay independent.

        Rise of new publishers: Larger organizations with strong marketing and business development can mitigate some of these trends. They also can build portfolios so that if some games fail, successes still keep the whole afloat. That organization usually is called a publisher. Expect a number of publisher to start snapping up contracts for games from the more capable indie developers. Indie developers get cash to offset the risk of their game failing and and publishers get another chance of owning a hit game.

        Rise of first party: Longer term platforms will start taking full ownership of any genre that is a guaranteed money maker. This vertical integration pays off. Platforms can capture all revenue that goes through the game, direct players to their games via promotional spotlights and reduce the riskiness of dealing with a volatile 3rd party developer.

        Future Springs

        We should celebrate the perennials planted during this amazing cycle. Or at least the tulip bulbs that may one day bloom.

        Grassroots game development will continue to thrive
        I don’t think we’ll ever go back to the bad old days of early 2000 where ‘breaking into the game industry’ was an actual barrier. Several trends mean the flood of new developers will not cease.
        • Tools: The cost of tools has dropped dramatically. And the tools that exist such as Unreal or Unity are of unprecedented power and polish. Anyone with time and passion can makes games and I suspect it will only get easier.
        • Schools: Students want to make games. Schools can charge those student enormous fees to teach them how to make games. This dynamic will exist independent of whether or not there are paying jobs waiting for those students.
        • Open distribution: There are multiple ways to make your game available to knowledgeable players. Steam, Android and iOS stores have minimal gatekeeping. Sites like have no real gatekeeping. The vast swath of humanity that doesn’t know about your game will never find out about it from these locations, but at least it isn’t blocked from publication. For the hobbyist developer, even a couple dozen downloads from friends and family can be inspiring enough to encourage further game making.
        Expect a situation closer to what we see with writers, painters and musicians. Schools enable the necessary but time intensive acquisition of game making skills. The commercial market for those skills remains difficult to break into without elite level portfolios. However, there’s still a vast community of extremely low income developers making games because their passion is stronger than the need to be wealthy. In my dreams, this group of game making hobbyists regularly gets together for wine and moral support. And maybe even funds the occasional indiegogo when one of them needs a new liver.

        There will be new markets
        VR is one obvious new market. VR isn’t quite able to stand on its own, but platform owners seem committed to market building. If they collaboratively spend a billion or so to seed VR content, that’s a new billion dollar market for game developers.

        And VR is not one new market. A rolling wave of multiple VR and AR markets will appear over the next decade as new technology leapfrogs past efforts. Each will be characterized by tech giants engaging in market building. That's an opportunity. Early PC development was likely the most similar sequence. We can have multiple Cambrian explosions.

        The seasons turn

        I hail from Downeast Maine where growing seasons are short and harvests valued. The spring is a (muddy) revelation. The summer a miracle. Even fall is greeted with a delighted grin. Yes, the wind blows so hard it is hard to walk straight. Yes, the frost will kill our gorgeous garden. But if we’ve planted well, the root cellars are at least full. And we’ve got hot apple cider.  And if we haven't, we'll do what we need to do to make it through. Even if that doesn't involve owning our own garden.

        The key to my admittedly insipid joy is to realize that the world runs in cycles. We can bemoan the loss of summer, but it does little good. Instead, as winter settles in, put wood in the stove, put on some tea and let the infinite snow silence the cacophony of the world. Take some time to think. What did we do wrong during the last big opportunity? Take some time to dream. What would we do right if we had a chance to grow again? A long term view means that there will be many seasons of growth, harvest and frost.

        Some form of spring will return eventually.

        take care,

        Game design patterns for building friendships
        Posted by Lost Garden [HTML][XML][PERM][FULL] on 27 January 2017, 3:58 pm
        In November of 2016, a small group of veteran game designers got together in a remote portion of Texas for a think tank called Project Horseshoe. Our workgroup dug deep into how design can help build meaningful relationships within games. You can read the other reports here:

        Our group consisted of:
        • Daniel Cook, Spry Fox
        • Yuri Bialoskursky, Electronic Arts
        • Bill Fulton, Microsoft
        • Michael Fitch,
        • Joel Gonzales,


        The issue
        In many online multiplayer games, players enter as strangers and remain strangers. Due to a variety of unquestioned logistics, economic and social signalling choices, other human beings end up being treated as interchangeable, disposable or abusable. We can do better.

        When we throw players into a virtual world without understanding the cascading outcomes of default human psychology, we are little better than an unethical mad scientist replicating Lord of the Flies. As game designers, we’ve been building destructive dehumanizing systems. We should take responsibility for the bullying, harassment and wasted human interactions that inevitably results.

        Let’s instead design games that help strangers form positive pro-social relationships.

        New tools
        There’s a mature body of research going back to the 1950s concerning how to create systems and situations that facilitate positive relationship building between strangers. Given the right context, people will naturally will become acquaintances. And a smaller number will become friends.

        Much of this research focuses on describing how friendship forms in observed communities. Or how an individual might go about developing friendships. We propose intentionally using these psychological insights in a highly scalable online game designs to engineer potentially millions of healthy player relationships. Many games accidentally separate players and decrease the chance of meaningful human contact. What if we design our games to be more socially meaningful?

        We can’t force two people to become friends, nor should we want to. But we are in a unique position to build systems that create fertile ground for friendships to blossom. And by carefully nurturing positive relationships, we can simultaneously avoid naively birthing poisonous cesspools that actively fosters hate.

        This paper cover a simple design checklist based off well supported models of friendship formation. Put it into practice and you will create games that build stronger player relationships and stronger communities. In addition to making the world a better place, your games will likely have better retention and improved monetization because you are creating value for your players that speaks to their deeply human psychological needs.

        General Model

        To build friendships, your game should facilitate four key factors. When these are present, friendships tend to form.
        1. Proximity: Put players in serendipitous situations where they regularly encounter other players. Allow them to recognize one another across multiple play sessions.
        2. Similarity: Create shared identities, values, contexts, and goals that ease alignment and connection.
        3. Reciprocity: Enable exchanges (not necessarily material) that are bi-directional with benefits to both parties. With repetition, this builds relationships.
        4. Disclosure: Further grow trust in the relationship through disclosing vulnerability, testing boundaries, etc.
        What sort of friendships does this model cover?
        We define a friend as another person with whom you have a mutually beneficial long term relationship based off trust and shared values.

        There’s a spectrum of friendship ranging from acquaintance to best friend. Different cultures have very different definition for what it means to be a ‘friend’. Americans for example, tend to call relatively distant acquaintances ‘friends’ while a country like Germany may reserve the term for two of three closest relationship. In this paper, we treat friendship as a spectrum that ranges from stranger all the way up to deep intimate friendship.

        In particular, we focus on the transition from stranger to acquaintance. This is the step that most often falters in modern game designs.

        What types of games can use this friendship model?
        For the purposes of this paper, we are interested in a specific domain:
        • Online: Players are not in the same physical space.
        • Mediated: A computer mediates all interactions between the players. Rich in person channel of communication like one might find in a board game or sport are not available.
        • Synchronous: Players are interacting in real time via keyboard, mouse, mic, controller, voice, emote, etc.
        Other types of games benefit as well, but they have their own complexities that are outside the scope of this essay. Local multiplayer taps into high bandwidth interpersonal communication and often occurs between existing acquaintances. Asynchronous multiplayer relies heavily on a strong reciprocation loop to compensate for a weak sense of proximity.

        1. Proximity

        What is Proximity

        The first factor to consider is Proximity. Social proximity is the likelihood of players seeing and having the opportunity to interact with one another in a game space. This space can be virtual like a chat room. Or it can be spatial like a room in a game match.

        Think of proximity in terms of simple logistics. If players can’t see one another they can’t initiate the reciprocation loops and any friendship is impossible. Without proximity, friendship is impossible. In some sense this is an obvious requirement, yet in many games we create strong barriers to simply being together.

        Concepts for Proximity

        A high density game is one with a low amount of distance between players so they are likely to bump into one another. A low density game is one with a large amount of distance between players. Often we design in terms of ‘number of players’ and independently think about ‘size of map’. However, density, the ratio of these two factors, is often the key attribute to balance.

        Frequent serendipitous meetings
        Due to high density, people are likely to ‘randomly’ bump into one another repeatedly. This creates exposure and familiarity between strangers. Meeting the same person again and again feels like magical fate, but it is primarily the outcome of well designed statistics and logistics.

        Crossing class, race and age boundaries
        The single most effective method of creating friends that cross traditional social boundaries is to put two people together in close proximity. People form friendships with those that are nearby and if their choices are limited, they’ll form choices with those that would not be their instinctive (often biased) choice.

        Connection to other requirements
        • Reciprocation: Being the in same space yields parallel play. This eventually leads to low cost reciprocation loops between players
        • Similarity: Being in the same place lets players observe similarity. Note that in studies of friendship formation, being in close proximity is a stronger predictor of friendship formation than being alike. However, the impact of distance falls off quickly and once players start rarely being close together, they will start forming friendships predominantly based off similarity.

        Proximity Patterns

        Player Identification
        Other players need to be identifiable. If you see someone a second time, would you know it? Names, unique clothing, identifying animation or abilities all help players understand that they are seeing the game person again and again.

        Persistent spaces
        A consistent persistent space that players can join and then later rejoin provides a means for players to find and associate with players that they deem worthy of friendship. There are many variations of this:
        • Dedicated servers: Something like Minecraft has a vast number of player run servers. These create memorable locations tied to permanent communities.
        • MMO shards: A player is associated with a particular long lived world instance. This creates a cohort of players that advance through the content together and then to run into one another frequently.
        • Persistent sessions: In match based games, you can keep players together when the next match begins.
        • Chat rooms: A common chat room or group where players seen names also acts as a persistent space even though it is completely abstract in nature.
        Shared Events
        You can increase density by taking players that are spread across time and incentivize them to all show up during the same time. Many games suffer from low player density because concurrent players are spread across multiple time periods. A play session may only be 30 minutes (or less in the case of mobile) so even if you have 1000 players who play on a server, your concurrent player number would be less than 10. Think of your game in terms of concentrating player density across time.

        Shared events help this situation by asking those 1000 players to all show up at 8pm on a Saturday night. Suddenly, your sparse world is full of players.

        Recurring events
        A shared event that reliably occurs every week at exactly the same time helps create that repeated interaction that is common with persistent spaces. Having a clearly published schedule of recurring events is a great method of increasing density and serendipity.

        Persistent Cohorts
        If you’ve got a matchmaking system, it can give priority to those that you’ve played with previously. Or if you have an MMO shard, the game can seed it with those that are started at roughly the same time period. The result is a group of players that are moving through the content together.

        Opt-in persistent social groupings like a guild or a clan are another self selected space for those that are further along in their friendships. It is often a greater commitment to join these groups, but the result is frequent interactions in denser social spaces.
        • Guild halls create a small space for guild members to run into one another more frequently.
        • Guild chat focuses conversation between guild members
        • Guild targeted boss events provide focused group activities.
        Elastic Instancing
        Often we create instances or servers, fill them up with a cohort of players and then fail to remove the room when players inevitably churn out. This leads to a large number of low density servers and weaker friendship opportunities. Elastic instancing has the stated goal of maintaining an optimal density of players.
        • On demand server creation: New instances are only created if the concurrency is high enough. When new players start playing, we fill them into any open slots on current servers. When there isn’t enough room, we create a new server.
        • Server merging: If the population of server drops below some optimal threshold there is a mechanism for merging server population. This takes a huge variety of forms based off the game type. This is easier in non-persistent game since you can merge servers when each match ends. This is more difficult in persistent games.
        Hubs and choke points
        Players move around in many games. If you create a location they need to return to or move through on a frequent basis, they tend to run into other people more often. Think about your game in terms of how players flow through it. Hubs are central areas in a hub and spoke system that players must pass through. Often utilities like stores or guild features are located in or right off of a hub area. Choke points are similar to hubs in that players flow in from a broader lower density area or set of areas through a narrow location on their way to somewhere else.

        Proximity anti-patterns

        Lack of identification
        Many games weaken identifying signals. For example, true friendship is impossible in a game like Journey because the identity signals are intentionally weakened. People swap in and out of a given game session without the player realizing that their partner has changed. Some MMOs have a fixed set of class art. You are a wizard or a fighter and all wizards look the game. This short circuits the player’s ability to identify their friend.

        Fluid identification
        Similar to lack of identification, some systems allow users to change their identifying characteristics on a regular basis. If the primary method you use to know if you’ve played with someone is their user name, and the system allows for freedom to cheaply change that user name, other players will not be able to track changes across time.

        Disposable People
        An important psychological considerations for persistent spaces is that players should have a strong belief that they will have future interactions with the people that they see. There’s research that suggests we have two sets of social norms: One for real people and another for ‘disposable people’; those that we’ll never seen again. These behaviors may be very close in the polite individual, but they can end up being negative and dismissive. If players see others a disposable due to proximity being low and repeat encounters uncommon, they’ll tend to act worse towards strangers. This leads to a downward spiral for the much of the community.

        Large group sizes
        Very large group sizes greater than Dunbar’s number (80 to 150) are difficult to comprehend. The overall principle is that systems need to operate at human scales (numbers and quantities comprehensible by a biological human.) We are ultimately building systems for people and homo sapiens have strong cognitive and physical limitation that we need to take into account if we want to produce the experience we desire.

        Don’t fall for the engineering or marketing mindset that says bigger numbers are better. A guild system that allows for 100,000 members is functionally worse in most cases than a guild that is capped at 150 because you’ve likely reduced social density, created swaths of disposable people and generally built a system that doesn’t fit with human biological constraints.

        Very dense group sizes
        With dense crowds of people it is difficult to see a person, difficult to identify a person and difficult to track a person. In Realm of the Mad God, we had dozens of people piled up on top of one another. This made for a great feeling of being in a crowd, but it was hard to actually see your friends.

        Many gameplay modes
        When games create many gameplay modes, they create more game play surface area over which players are spread. This makes any sort of match making more difficult and results in lower concurrency for each mode.

        A better pattern here is to rotate through the game modes so that everyone is playing the same mode at each point. Or tie modes to timed events. Players still get some variety, but the populations aren’t split up.

        Frequent splitting of groups
        In match made games, the match ends and players may be thrown into the matchmaking again. As a result they are matched with completely new players and thus any burgeoning relationship is extinguished.

        Separating friends by skill
        Games with a heavy skill component may match players in different skill categories. Or players that were in a cohort together are split because one player proves to be highly skillful.

        There are many forms of gameplay that are enjoyable to mixed skill players. Cooperative games, team vs team games, party games, games of chance or discovery, build or creative games all work. Try making one of those.

        Separating friends by progress
        Games that focus on leveling and power acquisition often have very large power differentials between players. If two friendly players want to play together, they may not be able to because either the newbie is so weak as to be useless to the higher level player or the higher level player gets so little reward from helping out the newbie that the friendship is the waste of their time.

        Barriers to repeated play sessions
        A difficult aspect for many match-based games is to get the same people to play together again a second session. This point came up repeatedly as the key challenge in forming friendships within a typical multiplayer console title. Treat putting players together for multiple matches and multiple sessions as a critical design goal.

        Artificial friendships
        If we automate or manipulate these proximity processes too heavily, players may feel that their friendships are artificial and therefore less valuable. Heavy handed matchmaking, ‘friend suggestions’ or automated reciprocation loops cause players to imagine that their relationship is formed for purely utilitarian (or nefarious) reasons and trust in other players drops to some utilitarian level. To be fair, this is mostly a theoretical concern since as of this writing most games encourage friendships lightly or not at all. But as our techniques become more broadly practiced, this issue is worth watching out for.

        2. Similarity

        What is Similarity?

        The second factor to pay attention to in our friendship formation model is similarity. Similarity is how closely we share various aspects of our personality and background with another person. The more similar one person is to another, the more likely a friendship will be initiated. On first sort, we judge another person based off their visible traits, their affiliation with known social groups and any values we infer based off our stereotypes. With increased contact, we also filter by communication style and personality (see OCEAN).

        If social proximity is the barest logistical necessity to form a friendship, similarity is the the criteria by which we decide who we will invest in further out of all currently available options. We can only invest in so many friendships so we filter out dissimilar people. Without similarity, friendship is possible but unlikely.

        If you believe in the value of multiculturalism or other philosophies that celebrate human variety, this topic may raise an eyebrow. However, people’s reliance on similarity to filter others is one of the more strongly reported effects across decades of study. However, we see this as a tool to create rich social tapestries from complementary backgrounds and not some preordained reinforcement of the current social order. Designers in virtual environments have immense control over what players see as similar. We should use that power to mold the societies we desire.

        Concepts for Similarity

        Similarity lowers the cost of social negotiation
        Shared contexts, values, and identities bring along with them social assumptions, common language/vocabulary, and models for interaction. It is easier and quicker to negotiation a cooperative, mutually beneficial set of norms if two entities share a strong common base.

        Perceived similarity matters more than actual similarity
        Humans are remarkably poor judges of others. So they tend to rely on superficial details to determine if someone is actually similar. In studies, this perceived similarity is a greater predictor of long term friendship than objective measurements of similarity.

        Similarity in virtual environments can be generated
        In the real world, similarities are often difficult to change. Players bring along much of human history when it comes to various religious, racial and language differences. Surfacing that baggage immediately typically results in players using it to filter out possible friends.

        Luckily, in virtual social spaces, the specific simulated cues that each player sees can be intelligently curated, often on a per player basis. The biases of the real world need not damage a first impression inside your game.

        Self reports are often highly inaccurate
        The traits that people say they look for in a friend are rarely what they actually use to filter out potential candidates. For example, comparable physical attractiveness and comparable intelligence correlates highly with friendship formation attempts. However, polite society looks down on stating that you are friends with someone in large part because they are devastatingly handsome. Much of the machinery of detecting and acting upon similarity is either sub-conscious or impolite to discuss publicly.

        Similarity patterns

        Visible Distinctions
        The earliest element players latch onto visual similarity. Titles, achievements, badges, equipment, names all work. Think of your similarity signals in terms of depth engagement.
        • Glanceable: What do people see in the first 200 ms? This is the most impactful location for leveraging visual similarity. Silhouettes, colors, large scale animations are used by players to judge one another.
        • First session: What do people see in the first play session?
        • Multi session: What addition signals are revealed via special abilities or viewing the player in unique, uncommon situations.
        Faction Identity and Conflict
        A shared tribe create a strong feeling of acceptance. All social groups are composed of a core shared identity, a boundary that define who is outside the group and a set of others who are known to be outside the group.
        • Define a group identity. Determine how one player will be able to quickly display and observer membership. For example, in World of Warcraft, Alliance players all come from a specific set of racial classes. There are dominant color schemes and silhouettes that makes quick, accurate identification easy.
        • Define the Others, those outside of the group. In World of Warcraft, there is a clear opposing team, the Horde. They are shown in faction specific lore to be less worthy than the player’s current tribe. Differences are accentuated.
        • Define an expensive boundary for crossing between groups. This acts as an economic wall that encourages any resources to be directed back towards the player’s current tribe. Enforcing systemic costs for interacting with the Other results in increased polarization. If you are in a PvP situation and an enemy group can kill a player, they will naturally seek the safety that comes from belonging to a friendly tribe.
        The result of a strong tribal identity with a clearly defined Other often results in strong friendship formation. They clearly understand who they could make friends. And they have clear reasons to build those friendship in the face of an organized adversary that would swamp an unconnected individual.

        Note that factions lead to some of the ugliest aspects of human culture. The very aspects that make tribes a powerful organizing forces also result in hideous abuse and bullying of those they dehumanize. At potential fix is to use AI opponents in a PvE conflict. Or in survival type games, use environmental obstacles. Often it is better to Other a digital illusion than a real human being.

        Shared experience
        A shared experience also triggers similarity. For example, when players go through a boot camp or hazing ritual as an introductory experience, they can refer to that as a common moment. In an MMO, players might go through a particularly difficult dungeon and wear a token from it as a sign of pride. The higher the cost of the hazing, the more long term the resulting self identification. There’s an element of cognitive dissonance at work. A player thinks “If I invested in X, it must have been worth it.”

        Hard-fought matches, difficult raids, long periods spent grinding or leveling all can work as shared experiences. Near-wins are more emotionally intense than a clear win. Brutal losses can also create definitive bonding experiences. Many religions use repeated stories of shared persecution that function as a means of increased bonding between members.

        Shared Interest
        Players who are players the same class or role within a game have a potential affinity. Or players that are on the same quest or have a shared public goal. In the game Realm of the Mad God, bonding was often as simple as two players shooting at the same enemy.

        Establish Aspirations
        Humans look to other humans when determining how they should act. And most of the time, they give greater weight to those members of their community that have high status, aka celebrities or leaders. By highlighting celebrities within your game, you create a template for players to to compare both themselves and strangers to.

        Two things will happen. Players will start to conform to the ideals shown by the celebrities. And they’ll see others that conform in a positive light. Essentially the celebrities create a beacon of artificial similarity.
        • Publicly showcase players that fit the team’s desired ideals. Name, avatar and the emotional reason why they are important are key elements. Interviews, viral clips of how they play and other concrete elements help cement the norm you are trying to promote. Think of it as an advertisement that tells players how to act by giving them an example.
        • Beware of showcasing only top players on a leaderboard. For example, you might choose to emphasize norms like generosity, self sacrifice or community service. Leaderboard players can accidentally showcase negative traits like aggressively uncontrolled competition.
        • Give opportunities for other players to mimic dress, class, abilities of highlighted celebrities.

        Similarity anti-patterns

        Surface real world similarity can lead to premature disclosure
        For example, highlighting that a player is a woman in real life might result in a spike in abuse inside the game. The intent may be to encourage women to find other women, but if it occurs too early in a relationship, the overall impact is negative. See section 4 on Disclosure for more details.

        Negative Othering
        Exclusionary group dynamics can calcify and reinforce the negative consequences of othering. Systems that create homogenous groups in opposition to other groups result in the following issues.
        • Poorly met internal needs. As social energy is dedicated to maintaining the group cohension, less energy goes towards serving individual needs. This results in churn.
        • Poor onboarding of new players. The barriers to entrance into the group actually hurt its growth since very few pass the increasingly rigorous purity tests. This result in the group’s membership churn not being replaced so you get declining player populations.
        • Stagnation. Rigid social structure means the pure group has difficulty adapting to environmental and social changes.
        • Bullying and abuse of those deemed outside the group.

        3. Reciprocity

        Our third factor in friendship formation is Reciprocity. Reciprocity is fundamentally about using iterative exchange to negotiate social norms and build trust. If Proximity and Similarity are filters on who becomes friends, Reciprocity is the mechanical engine that make friendship function.

        Any reciprocation loop can be analyzed as a simple turn-based game between two players. Use these steps to talk about the reciprocation loops in your game.

        Player A moves first
        • Player A performs an action that targets Player B
        • This action has cost to Player A: This is an economic cost in either tangible resources or time, attention, or social status.
        • This action has a benefit to Player B.
        • Player B observes feedback that result from Player A’s action
        • Player B updates their mental model of Player A. This includes a summary of historical interactions, aka a relationship.
        • Player B weighs the benefits of future action and makes a choice on what to do next.
        Player B responds
        • Player B performs an action that targets Player A.
        • This action has a cost to player B
        • This action has a benefit to player A
        • Player A observes feedback that results from Player B’s Action
        • Player A updates their mental model of Player B
        • Player B make a choice.
        • The loop restarts.
        That’s a single iteration. Reciprocation loops are typically repeated multiple times, accumulating economic and social capital to both parties. Learn to see them. Walk through them step by step to diagnose exactly where your social loops are failing.

        Concepts for reciprocity

        Exchange is substantially non-material in nature
        The language of reciprocity comes from the world of economics. One might imagine that friend formation is reduced to a merely capitalist construct of exchanging material good and weath. Nothing could be further from the truth.

        A valid reciprocation loop could include exchange of any of the following:
        • Recognition or attention: A shared glance is a reciprocation loop.
        • Common experience: A shared experience in which both react and see one another react to the same situation is a reciprocation loop.
        • Conversation: Two people talking is a reciprocation loop.
        • Complementary roles: A tank and a healer in an MMO exercise a form of economic specialization that costs neither side anything material. This ends up forming a reciprocation loop.
        Medium of exchange
        In order for reciprocity to function, there must be a medium of exchange, there must be a bidirectional flow between both parties. This covers a huge range of possible interactions.
        • Chat, Voice, Video
        • Visual space with movement
        • Trade systems
        Perceived benefit
        Both sides need to feel that they benefit from the relationship, if not short term, at least over the long haul. This need not actually be factually true. See asymmetry below.

        Friendships fail when exchanges aren’t appropriately reciprocated
        Each time an overture is made to another person and that overture is not returned, the relationship between those two becomes more distant. A failed reciprocation can take multiple forms
        • Player B ignores the overture. Communication is messy, so if it was low enough cost, Player A may attempt again.
        • Player B reciprocates, but does so inappropriately. They give too much or too little. They give the wrong sort of response. The negotiation of norms is going poorly and the relationship may end.
        • Player B explicitly rejects the overture. The relationship momentum falters and may degrade.
        • Player B uses the overture to harm Player A. Any relationship begins to degrade rapidly.
        You need to design unreciprocated exchanges as much as you need to design reciprocated exchanges.

        You also need to consider that human find making overtures risky and rejection emotionally painful. We are wired to form friendship and when we are rejected, it is one of the deepest cuts a person can experience. So when you design for failure, consider how to soften those failures. Consider tools like: Kindness-focused language in feedback dialogs, reframing the rejection, deniability or immediately redirecting to other relationship opportunities.

        The good news is that lapsed friendships that lack negative exchanges are easier to restart than new friendships. You have a common base of social norms already negotiated. This acts like a foundation of similarity in boosting re-engagement of the reciprocation loop.

        Self reporting is biased
        This is a tricky thing to ask friends directly about economic aspects of their relationship. Friends tend to downplay any short term or medium term benefits so as not to jeopardize long term relations. Think of it in terms of game theory using the following strategies:
        • Someone signals short term interest: If one participant signals that they are reciprocating for short term benefit, the other participant may try to optimize for as much benefit to accrue to themselves before the relationship ends. Minor low cost exchanges are now weighted against the relationship endpoint and may not be initiated or returned. With this strategy, friendship quickly collapses.
        • Both signal long term interest: Alternatively if both participants signal that they are reciprocating for long term benefit, the minor exchanges are worth it when compared against any benefit that may pay off in the future.
        • Someone falsely signals long term interest: Now if one person is engaging for short term benefit and one for long, it still pays to signal that you are invested long term. Since if you signal your actual short term interest, the relationship enters into a failure cycle and collapse before any benefits accrue. 
        This dynamic substantially biases any self reporting around friendship.

        Symmetry and asymmetry
        When friends describe their friendships, they take great pains to couch them as symmetrical. How one person benefits is always equal to how another person benefit. Due to the fact that self reporting on friendship is biased, our model of how friendships should be balanced is highly questionable.

        Many social relations and exchanges are in fact inherently asymmetrical but reciprocal (parent/child, student/teacher, etc.). Many friendships are initiated by low status individuals seeking a relationship with a higher status individual.

        Escalation of costs as friendship deepens
        Friendships start out with very low cost overtures and then as each exchanges is reciprocated, the average cost increases.

        This makes sense from an investment perspective. Early on, a person doesn’t know if the stranger will reciprocate. It makes economic sense to invest in many very low cost exchanges in the hopes that one of them will pay off. If most of them fail, it is fine since the cost isn’t high.

        Later on, a person has established a history of reciprocation. They can be relatively confident that a long term associate will respond in a predictable fashion even if the exchange is of higher value.

        Some friendships eventually falter as the cost of each exchange grows too high. But some will continue escalating to the point where nearly no cost is too much. This is seen in marriages, families, and some long term friendships.
        • Design a friendship progression curve for your game.
        • Put less expensive interactions at the beginning. Encourage players to build up skills first in safe spaces. Most League of Legends players play single player or cooperative PvE games first before they risk competitive PvP.
        • Defer high time and resources commitment interactions later. Raids open up after you’ve been playing the game for while.
        Limited number of deep friendships
        Since deep friendship come with expensive long term reciprocation loops, most people can only afford a limited number. Dunbar suggest that there are biological limits on how many people we can form relationship with and that these cluster in ever decreasing circles of friends.

        Pick which groups you are designing for.
        • 1500 people: People whose face your recognize. These are lowest investment relationships.
        • 500 people: Acquaintances. People whose names you know.
        • 150 people: Casual friends. People you hang out with occasionally. This is this largest typical group size.
        • 50 people: Close friends. The sort you might invite to dinner.
        • 15 people: Confidants. The sort you’d tell intimate details of your live.
        • 5 people: Close support. These are highest investment relationships, but you only get a few.

        Reciprocity patterns

        Spatial positioning
        In a game with spatial positioning of an avatar (like Diablo or any FPS), the mere act of trying to stay close creates an early stage reciprocation loop. A player moves to a location. This is an invitation. Another player responds by moving in the same direction. Such move and response actions are very low cost on the part of the players so they aren’t risking much by engaging. This is the primary form of reciprocation in a stranger-friendly game like Journey.

        In games with rotation, players can also face one another. This is another social gesture that forms an early reciprocation loop.

        Emotes or signalling
        Games often include emotions like a wave or dance animation. One player will start with a gesture and other nearby players will either repeat the gesture or iterate on it with some contextually interesting variation. This may turn into a synchronized dance session or a private emote-based language that was negotiated over multiple play session.

        Chat is one of the richest methods of building social reciprocity. By tapping into language, chat enable socializing, humor, information exchange, the establishment and reinforcement of norms.

        Beware premature disclosure (see disclosure below)

        Trade (Gifting)
        Exchanging virtual goods allows for a wide range of material economic transactions. Players can become a reliable supplier or a reliable purchaser. In our capitalist culture, this form of relationship is familiar to many and thus players easily fall into the appropriate roles. Trade also opens up gifting and twinking, two practices in which virtual goods are exchanged for status or goodwill but not currency.

        Negotiation heavy trade such as barter is often as much about having a conversation that builds a social relationship as it is about economic efficiency. Be aware that highly efficient, low conversation trade systems such as auction houses can actively remove reciprocation loops from a game and thus damage the social foundation of your title.

        Mutual Support
        When players can help out other players, they will often fall into patterns of reciprocal helping one another. One player covering another as they rush a point. In turn that player is healed by the person they helped. This tit-for-tat occurs even when players have symmetrical abilities.

        An extension of mutual support is creating specialization for each player. Unique roles that create dependencies result in reciprocation loops. The MMO trinity of Healer, Tank, DPS class naturally clump together in order to increase their overall efficiency.

        Allegiance systems
        You can also build asymmetric hierarchies of mutual dependency. The MMO Asheron’s Call implemented a system where new players could declare their allegiance to more experienced players in return for help within the game. This created an improved new user experience and in return, the patrons earned a portion of their vassal’s experience. The patrons could in turn be vassals of higher patrons and everyone had a huge impetus to ensure that those below them did well. (

        In the Xbox version of Shadowrun, players could resurrect dead players and earn a portion of their kills. However if the patron player died, all resurrected vassals would also die.

        Face to Face interaction
        In many real world studies simply being in the same space isn’t enough. You need to see another person’s face and be able to respond via glance or micro-facial expressions. This is not typically captured in games, but it likely will start to show up as VR and facial scanning technologies become more prevalent.

        Reciprocity anti-patterns

        Zero Sum interactions
        When there are limited resources in play, a player is forced to choose between spending a resource on a relationship or keeping it for themselves. Early in a relationship, the perceived cost and sense of loss aversion makes players selfish so they are less likely to initiate experiments. Instead use non-zero sum interactions early on in player relationships and carefully introduce low cost zero sum interactions once players have formed stronger bonds.

        Ideally, zero sum interactions are opt-in and used as an explicit means of taking a relationship to a new level. For example, a player might choose to pay a fee to help level up a guild. The currency used for the fee is useful elsewhere for selfish purchases so the player ends up signaling their sacrifice and dedication to the group above their individual needs.

        Trade scamming
        In systems that allow the trade of material goods, be wary of tempting players to scam one another. Players with weak bonds will see an unsecured trade as an opportunity break trade promises by taking something without giving a promised item in return. This reduces trust in the environment and makes it difficult for all players to form friendships.

        A better system is a secure trade window that requires both players to confirm their promise and then reliably automates the exchange in the background. Ask yourself: Do the designed methods of player interaction facilitate trust? Do they protect against the bad actor’s worst instincts?

        Lack of predictability
        The bigger picture here is that good social norms, the foundation of friendships, rely on predictability. We build a model of how another person will interact and then base complex and expensive plans how know that person will reliably react as expected in a given context. When player behavior is encouraged to be random or unreliable, it is much harder for players to form social norms. You perform a gesture toward another player and get something random back instead of converging on a predictable social pattern.

        For example, if your guild just killed a huge boss, there might be a social norm that you divide the loot. However, the system is left open ended and instead a single player takes the loot and leaves. The very player freedom that exists at that decision point results in highly unpredictable outcomes. Some games can survive this (games like Eve have various forms of community censure that turn turncoats into economic and social pariahs). Most games treat these moments as incidental social friction not worth polishing out. However, these ‘minor’ issues slowly poisons the whole community’s ability to make deep long term friendships.

        Extreme power differentials
        In many leveling-based system a large power gap forms between new players and old players. This economically segregates communities and in extreme examples there is nothing that a powerful player needs or wants from a low power player. The game design has created an high economic barrier between two humans that is totally artificial and unnecessary.

        A good tool for solving issues like this is to ensure opportunities for economic and social dependency between any player in the game independent of power level. Create ties between players that make it beneficial to become friends. Hunt down and eradicate all systems that force players to dismiss one another as useless.

        Over designing for freeloaders
        A freeloader is a player that benefits from a community without contributing materially to its success. American culture specifically puts a large amount of effort into reducing freeloaders, often at the expense of community. By policing and punishing the few, the community becomes more selfish and less likely to form positive friendships.

        Most community systems, especially ones based on non-zero sum resources, are remarkably stable in the face of moderate free-loading. Players may complain due to their existing cultural biases, but the end result is a stable and happy society. Ask yourself if the freeloaders are actively hurting other players. If they are, see if you can shift the design toward non-zero sum interactions. If they aren’t, feel free to ignore the problem and stop wasting precious design cycles on a non-problem.

        High initial interaction costs
        If an early interaction is too expensive, players won’t initiate the reciprocation loop. One solution is that the system can pay the cost early on to prime the pump. For example, social games allowed players to give gifts to other player, yet those gifts cost the giver nothing. They were created from thin air.

        You do need to be careful as then people can think that they are being paid to be friends. When priming the reciprocation pump, Give the absolutely minimal, non-distorting incentives. Slowly increase what how much the system subsidizes that first interaction and look for behavior shifts at each cost increment.

        4. Disclosure

        Our final factor in friendship formation is safe disclosure. As players get deeper into a relationship, the nature of the reciprocation loops change from superficial mirroring to riskier trust building interactions. Key to the creation of deep friendships is the ability to friends to disclose new or secret information to another person.

        Games that lack the tools for disclosing personal info between two people will never facilitate deep relationships. They may never even facilitate shallow relationships since players see that there will never be a long term future for any relationship they form in the game. However, disclosure is a highly risky action and teams will often try to cut it from their designs. Sharing information before a relationship is strong enough can result in broken or antagonistic relationships.

        Concepts for Disclosure

        Risk is inherent to disclosure
        When a person discloses personal information to another player, there’s always the chance it will break the relationship. Up until this point, players have typically been performing low cost, non-zero sum interactions that are tightly constrained by game systems or social convention. Personal information brings in external history, gender, age, religion, race, values and other delicate factors that may cause the other player to fail to reciprocate or otherwise pull back from the relationship.

        If failure to reciprocate hurts emotionally, failure to reciprocate a personal disclosure hurts substantially more. Disclosure is a laying bare of the soul for many and the fear of rejection is immense. If your game moves relationships to this point, you are making more than mere entertainment. Your game facilitates moments that uplift or scar players in formative ways.

        What constitutes disclosure is highly specific to a given person and relationship
        The exact contents of a ‘disclosure’ depends on what might threaten a specific relationship at a specific stage with a specific set of participants. So we are dealing with an ill defined concept. However, the participants have a refined sense of what constitutes a disclosure so it is best to let them decide what to disclose and when.

        Disclosure patterns

        Rich communication tools
        The concepts involved in disclosure cover a huge breadth of the human experience. Emotes aren’t enough. To enable relationship building levels of disclosure you need to give players rich communication channels.

        There’s substantial discussion within many design teams on whether or not to include chat. The costs are easy to list. Chat that happens too early in a relationship can trigger unpleasant early disclosure and abuse. It can be used to spam players. Children using chat are at risk of being contacted by sexual predators. There are legal and moral considerations. Developers need expensive moderators or filters to manage these downsides. Many modern teams look at this list and run as far away as possible.

        However, when you cut out chat, you are gutting your long term community. Players will remain strangers and never form long term bonds with one another. Every relationship is at best like a game of Journey where anonymous people have fleeting encounters that never result in any long term impact or friendship. Remove chat and you remove 95% of all positive social behavior.

        When we build human systems, we should be wary of building systems that filter out our humanity.

        Luckily there are ways to have your cake and eat it too.
        • Make the tools for disclosure opt-in: Unlock chat between two people after they both agree they want their relationship to go further.
        • Give rich tools for opting out: Give players robust tools for filtering and blocking other players that abuse chat.
        Quiet Opportunities to Talk
        Relaxed environments where players are doing some low intensity activity will naturally result in players chatting with one another. In action games, players are often alway highly engaged with the moment to moment gameplay. There’s no space to chat. As a designer, you need to explicitly carve out these slower moments in your game pacing.

        Common examples include
        • Healing time in MMOs.
        • Lobbies in FPS
        • Post match chat
        • Private chat channels
        • Guild chat channels
        Mechanics that encourage disclosure
        Simple interactions derived from party games can provide people with personal information about yourself like humor, status, competence, history, etc. After all, a party game is just a mechanic to encourage personal disclosure.
        • Disclose or Punish: This is a typical truth or dare type activity. Note that even though it encourages a player to disclose, they always have an out so they aren’t forced to prematurely disclose something.
        • Safe spaces: Create spaces where anything can be said but where acting on that knowledge outside the safe space is highly inappropriate. Confessionals and psychiatrist sessions follow these rules. In Japan, people are encouraged to go out drinking with their co-workers. It’s an established norm that when a person is drunk, you’re not meant to take what they say personally, which allows people to provide feedback without repercussions.
        • Open reciprocation loops: If you give something a person and then request voluntary disclosure, they are likely to participate in order to complete the reciprocation loop.
        Mechanics that loosen inhibitions
        These are less common in computer games, but very common in real-life
        • Wearing silly outfits: Anything that shifts a player out of their current social context and identity lets them experiment with new roles.
        • Alcohol: Moderate drinking tends to loosen tongues. Note that this may risk premature disclosure.
        • Physical interactions: Many icebreaker games involve breaking through personal spatial boundaries. This rapidly creates feelings of intimacy that otherwise might never appear.
        • Commitment activities: Have a player do something rather difficult or expensive. Then put them in a place where they invalidate their personal and emotional investment unless they disclose.
        • Group encouragement: If you can get a large group of people apparently disclosing, then an individual will feel more comfortable with disclosure.

        Disclosure anti-patterns

        Premature disclosure
        System often discloses information about a person before they’re ready to share that information. The designers often think they are being helpful, but in reality they are forcing reciprocation loop to jump to an advanced stage before trust is built. The result is typically highly negative interactions between strangers.

        When a player doesn’t have trust built up with another person, they use any subtle clues to activate stereotypes. Stereotypes aren’t inherently bad; they are merely pre-existing schema that are used in the place of actual experience to quickly determine how to act. However, negative stereotypes end up destroying opportunities to create friendships based off personal experiences with another person.

        Example of premature disclosure
        • Showing real name. Real names include a variety of personal information about country, gender, and race. Let players select their own names or autogenerate a name.
        • Defaulting Voice Chat to ON: Voice can reveal age, gender and native language. Default it to off.
        • Showing location. Location can show nationality. Don’t show login location.
        • Purchased items (in F2P): Showing a player has purchased an expensive item. Or that they have only cheap items. Ensure items that can be purchased can also be gotten through other means.
        Highlighting dissimilarities
        When a user discloses or has information disclosed about themselves, it may in turn expose any dissimilarities they may have their current friends. This can cause the friends to rethink the relationship.

        Bringing in non in-game similarities or relying on default real world similarities
        Disclosing non in-game or real world similarities and assuming that they will carry the same weight in the game as they do outside of it


        So far we’ve considered a lot of theory about how friendship works and how it might be encouraged within a game. However, in modern game development, it is not enough to theorize and then build something. We also need to measure if we’ve achieved our friendship goals. And then when we inevitably realize we’ve missed the mark, we can use the tools covered in previous sections to iterate towards a better state.

        This leads to a vexing question: What friendship metrics can we measure across our games?

        We want to measure behaviors that may indicate a ‘friendly’ relationship between players in multiplayer games. Because we want these metrics to apply to most games, we will avoid ‘in-game’ metrics, which would have to be customized to the specific design of the game.

        Key concepts in measuring friendship

        Co-play experience
        People playing together.
        • Co-play: 2 players playing in a WoW dungeon together
        • NOT co-play: 2 players in different WoW zones chatting
        Repeated co-play experience
        People playing together after having played together in a previous play session. We’ll refer to the first co-play as co-play(1) and the second as co-play(2). This extends up to co-play(N).
        • Repeated co-play: 2 players playing in a WoW dungeon together the day after completing a quest together.
        • NOT repeated co-play: 2 players playing in a WoW dungeon together immediately after completing a quest (e.g., no substantial break between them)
        ‘Friendship’ behaviors
        Behaviors that imply an attempt to initiate or lengthen a co-play experience, or that may lead to a co-play experience in the future.
        • Friendship behavior: Invite to a group; staying in a group to continue co-play.
        • NOT friendship behavior: Attacking an enemy; healing a teammate
        The challenge of strangers
        For most commercial games, marketing campaigns used to acquire customers end up bringing in mostly strangers. So any friendship systems need to be tuned at launch to deal with large populations of people who don’t know one another.

        There are methods of important friends into a game but often the “Friend Graph” in a social network like Facebook maps very poorly onto the “Activity Graph” of a game, especially a new game.

        The challenge of Co-play(2)
        Looking across many games (and decades of design experience shared between all the authors) we observed a key challenge: Getting players to go from Co-play(1) to Co-play(2). Matchmaking creates co-play(1) with strangers very well; the hard part is getting people who played together once, to play together another time.

        Existing design solutions are weak and teams rarely if ever measure this critical statistic.

        Metrics for measuring friendship

        How much ‘friendship’ is happening in the game?
        This represents an overall metric of ‘how much repeated co-play’ is happening in a game. This metric applies more easily to discrete session-based games (Call of Duty match) than larger game experiences where players may be present but not co-playing (different WoW shards; same WoW shard but different zones). A way of quantifying this:
        • % of people in a session who the player has played with before. This is a representation of how many ‘familiar faces’ are in a match. If a player has never played with anyone in the match before, that match as a 0%. If a player has played with all the other players, then that match is a 100%. Notes:
          1. Multiple matches in a row with the same stranger should NOT count as a ‘friend co-play’ experience. A reasonable break between sessions is necessary to establish whether the co-play experience is intentional.
          2. This is a personal property; other players in that same match may have different %, depending on their unique social graph.
        • Average % of friends across all matches, by player. This a representation of how ‘friend-filled’ a player’s experience is with the game. It can help identify who is having a lot of intentional co-play experiences (playing with ‘friends’ vs. incidental co-play experiences (playing with a constantly different set of strangers). Sudden drops in this metric may indicate an attrition risk (player has lost of a co-play partner).
        • Global stats can be computed across all player-matches. This is a representation of what the typical player’s experience is of repeated co-play. It is probably most useful to identify the % of players who are at what thresholds of amount of ‘friend-filledness’ in their play experience.
        Note: these metrics assume that players are repeatedly playing together intentionally, and were not put together by the system repeatedly.

        Measures for pre-cursors of “intentional co-play”
        Beyond the above binary metric (intentional co-play: Yes/No), there are some useful pre-cursor metrics for likelihood of intentional co-play in the future:
        • Have the other on a list. Being on a ‘Friends’ list, or a ‘follow’ list, or guild list, etc. all enable better ability to do other behaviors that are pre-cursors to co-play. However, a large friends list does not necessarily result in more co-play.
        • Invite the other to co-play. Inviting someone to co-play is (obviously) a good pre-cursor metric. Some additional measures:
          1. Co-play invitation gets accepted.
          2. Accepted invitation result in co-play immediately.
        • Attempt to communicate with other. Sending a message, talking, etc. may all increase chances of future co-play. However, some communication does not lead to play (idle chat), or may even decrease the future co-play likelihood (rude chat).
          1. Response from other. Communication attempts that receive a response are often (but not always) more likely to lead to a future co-play experience or future precursor behavior.
          2. Note: sentiment analysis (algorithm to determine the positivity-negativity of text) is becoming more accurate and faster to do, and so measuring these kinds of precursors is becoming increasingly feasible.
        Examples of ‘Friendship’ behavior metrics, in game
        Because in-game ‘friendship’ behaviors are specific to the game design itself, it isn’t possible to do a framework that is complete. The list of metrics below is intended to be examples for how to do that.
        • Gifting. In games where gifting is possible, gifting can be considered either a pre-cursor to co-play, or even co-play itself.
        • Assisted kill. In games where killing enemies results in ‘assist’ stats, it is possible to determine which player was ‘playing with their teammates’ more than others.
        • Vote-Kick called. In games where people can kick a teammate off the team, which players call votes on each other, and how they vote are good indicators of anti-relationship behavior.
        Case study
        Reinforcing in-game relationships via displayed metrics in Shadowrun.

        The basic Shadowrun resurrection mechanic worked as follows:
        • Player 1 has a cost to resurrect player 2.
        • If Player 1 dies, then player 2 dies.
        • But, player 1 gets half of the money player 2 makes.
        • Goal: Make transparent system, system is revealed through stats.
        • Goal: Caused gratitude to be felt. “Did they exchange Packets?”


        “Friendship” systems deal with potentially intense emotional territory for players. The concepts we discuss in this paper should be treated with care. You are dealing with real humans and real emotional outcomes.

        Most friendships formed in games will only be acquaintances
        We use the word ‘friend’ but in truth the chances of making a deep friend in a game are very slight. We simply don’t have the mental bandwidth (see Dunbar’s groups) to have that many deep friends. So more likely is that our games are creating shallow networks of friendly acquaintances. However, think of the game as building a friendship funnel that players progress through. It isn’t a bad thing if only a few make it through to each deeper stage of friendship as long as some make it through.

        Players may grow wary of overt manipulation
        People dislike other people telling them they should be friends or pushing them towards friendship. Software can tell players things about themselves they don’t really want to know. For example, don’t have software define things like a marriage system and then tell two people they should be married. Instead, create opt in systems that encourage buddy behavior. Then give them tools to create ceremonies or the ability to mutually opt into a public badge that say ‘married’.

        Asheron’s Call encouraged aggressively trying to recruit a lot of people hoping some of them stick. Backlash risk of this is once newbie finds out what other person was getting in return. “Did you just want me because I’m rich?” causes you to question other relationships. People smell out rubber bands. Create plausible deniability of purely economic behavior when encouraging friendships.

        The relationship between behavior and affects
        If you have two people who communicate a lot, it could be constant fighting! Be wary of numbers going up if you don’t track why they are going up. The classic example of this in modern times is the dramatic collapse of games at Zynga even though internally key metrics were increasing.

        Grief-test your systems
        The systems that help people form powerful friendships are very open to abuse. The need for disclosure in particular causes issues, but most of the anti-patterns listed above have some elements of griefing or abuse. Assume players will attempt bad behaviors and have plans in place for when this occurs. If your systems assume humans are always angels, you encourage their demons.


        We believe two things when we discuss friendships:
        1. The facilitation of meaningful relationships between other human beings is a noble design goal.
        2. Games are uniquely suited to facilitating relationships.
        To make friends, you need multiple people, a reason to bring them together and some form of repeated mutually beneficial interaction. Multiplayer games have all these elements. Every piece of a game can be designed to remove walls and build social connections. What an opporutnity!
        • We can design our matchmaking and logistics system to encourage proximity
        • We can design our social signaling, characters and tribes to generate perceived similarity
        • We can design the economics of reciprocation loops at all stages of friendship formation
        • We can incrementally enable safe disclosure based off idle friendship formation pacing.
        Often we think of computer games as a single player medium for storytelling or some other evocative experience We put games in the same category as books, movies, comics, etc. However, it is also interesting to think of games as intentional human processes; rule-based machines composed of living, breathing, growing people. They operate on the same scale as sports, religions and governments. Such engineered human processes can help players thrive in designed virtual spaces and ultimately in their real lives.

        As game designers, this is one of our great powers and responsibilities. We design these machines. We are responsible for growth and nurturing of the machine’s players and communities that they form. The human process of friendship formation is an essential game design tool. Wield it wisely.

        Other reference material

        Early theory of friendship formation
        Festinger, L., Schachter, S., Back, K., (1950) "The Spatial Ecology of Group Formation", in L. Festinger, S. Schachter, & K. Back (eds.), Social Pressure in Informal Groups, 1950. Chapter 4.

        Why do we form friendships
        “From an evolutionary perspective, friendships may be seen as an unnecessary and costly relationship that involves altruism to a non-kin, non-mate individual who may contribute little to an individual’s reproductive success.”

        Social media’s effect on the math of dunbar’s number friendship

        How we evaluate the value of a person when considering friendship
        • Stimulus: What do we see on the surface. Physical attraction or similarity
        • Value: Compare values. Do they value the same things as we do.
        • Role: Do we have complementary roles so we can form a working relationship.
        Only half your friends consider you a friend
        Friend graphs are often non-bidirectional. However, they tend to be presented as equitable in order to preserve the network for future opportunities.

        Social Penetration Theory
        “As relationships develop, they penetrate deeper and deeper into private and personal matters. This exposes vulnerabilities, so trust has to be developed along the way.”

        Weak ties
        “In the familiarity of strong ties we use simple restricted codes, where much is implicit and taken for granted. In communicating through the weak ties, we need more explicit elaborated codes for meaning to be fully communicated. When elaborating, we have more scope for creativity and the thought that it stimulates makes innovation more likely.

        The more weak ties we have, the more connected to the world we are and are more likely to receive important information about ideas, threats and opportunities in time to respond to them.

        Societies and social systems that have more weak ties are more likely to be dynamic and innovative. If the system is mostly made up of strong ties, then it will be fragmented and uncoordinated.”

        Selection of friends based off Big 5 personality factors
        “...individuals high on Agreeableness tended to be selected more as friends. In addition, individuals tended to select friends with similar levels of Agreeableness, Extraversion, and Openness.”

        Real names lead to increased harassment

        Building Web Reputation Systems

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