Player Typologies in Role-Playing Games

I recently ran into a blog post discussing role-playing games using the play modes from various typologies since the 70s, including for example the Threefold Model, GNS and how the fifth edition of Dungeons & Dragons frames player preferences. The problem with these typologies is that they are typically based on people’s personal experiences at the gaming table (a valuable source of information!), but lack a systematic way of collecting and validating that information.

Fortunately, there is a research field that is interested in how and why people play games: game studies. While there are important differences between mainstream game studies and understanding role-playing games, I still think game studies has the best information on the issue currently available.

I’ll show how to make sense of play style preferences using game studies, but first, I’ll discuss some background: to my understanding, Edwards’ GNS model is one of the more influential ways of understanding play styles, so I’ll use it as an example to explain what we want out of play style models and what problems they might have. Edwards’ model also tries to explains things outside play styles, but I’ll ignore those parts of the model for now.

First, I think the greatest accomplishment of these models is to notice that not everyone is having fun playing role-playing games and instead of blaming the people in question, setting out to explain why different people prefer different things in their games. This is immensely important: while many role-playing games have had sections advising game masters on how to run games, they’ve often identified different play styles as other people playing the game wrong and given game masters tips on how to manage these players. I personally remember reading a section on a book for Vampire: The Masquerade on how to manage bad players.

A typical way to create a play style model is to play role-playing games for a while, notice that people engage with the game in different ways, think about the issue for a while, and group your observations into categories. There are two problems with this approach:

1. You might not be the perfect observer, mistaking why people do certain things and having your interpretations colored by your personal play preferences.
2. Even if you roll a critical success on your perception check, you’re only observing a small group of people: those that play with you.

Edwards’ model shows both problems. He generalises from his immediate surroundings to all players, and is so sure about his observations that when people point out that their play style isn’t captured by his categories he doesn’t believe them.¹

The way to solve these problems is to have good theory and good data. In this case we have one, but not the other, so the answer is still a bit tentative. Before we jump to that answer, let’s see how we got there.

Game studies approach to player types starts before we have what is generally considered game studies. Richard Bartle was playing a MUD at the end of the 80s, when someone posted the question “What do people want out of a MUD?” onto the games bulleting board. He acknowledged that he had no training in psychology, but thought that he should still try to figure out the answer. He looked at the answers given in the message thread and grouped them into four different player types (achievers, explorers, socialisers and killers), turning that answer into a highly cited publication. The method was not that different from the one used in role-playing games discussions: Bartle used the preferences of a few dozen MUD players playing a particular MUD to generalise about universal player preferences. He maintains that his model turned out to be surprisingly accurate, but other people have since approached the question with a bit more data.

This question was picked up again a decade later, with a dozen papers being published by mid-2010s. The typical approach is to use either behavioral or psychographic data and do some kind of quantitative analysis to it – often factor analysis. I won’t go into the details of the methods used, but the important part here is that combined, these studies cover thousands of different players in different contexts.²

These studies have been helpfully summarised by Juho Hamari and Janne Tuunanen in 2014. They find that the research is mostly in agreement on player motivations, which they call Achievement, Exploration, Sociability, Domination, and Immersion. The names for these categories are pretty good, but for clarity:

1. Achievement: progression and achievement in the game.
2. Exploration: solving problems, finding things, exploring worlds.
3. Sociability: forming communities, social interaction and helping others.
4. Domination: gaining power over other players in the game.
5. Immersion: immersion in stories or fantasies.

When discussing these categories, it’s important to remember that they are modes of engagement, not types of players. It’s possible to prefer different types of engagement in different contexts. It’s also possible to move between motivations within one play session: perhaps I like examining the personality of my Dungeons & Dragons character by having intensive, dialogue-heavy scenes with the other players (immersion), but don’t let that get in my way when it’s time to kill some monsters (achievement). Or maybe I like Vampire: The Masquerade larps because they allow me to both enjoy the social intricacies of 500-year-old institutions (sociability) and plot my way to the top of the social hierarchy (domination).

Now, I mentioned that you need both good theory and good data? Unfortunately, we lack the latter on people who play role-playing games.³ My best guess is that all of these play motivations are present in role-playing games, but how they are distributed is harder to say. It seems likely that they would resemble those found in digital role-playing games, especially MMORPGs, but that is just my informed guess. If you’re looking for something to study about games, this is one area that could use some more attention.

1. From “GNS and Other Matters of Role-Playing Theory, Chapter 2”:

   “Now ask, ‘What makes fun?’ This may not be a verbal question, and it is best answered mainly through role-playing with people rather than listening to them. Time and inference are usually required.”

   “For a given instance of play, the three modes are exclusive in application. When someone tells me that their role-playing is ‘all three,’ what I see from them is this: features of (say) two of the goals appear in concert with, or in service to, the main one, but two or more fully-prioritized goals are not present at the same time.” ↩

2. Digital role-playing games are actually overrepresented in this sample through MMORPGs. This is because game studies has had a persistent bias of studying a lot of MMORPGs, especially World of Warcraft. ↩

3. There is a study that tries to find out the play motivations of “hobby game players”, but that includes all kinds of other things besides role-playing games. They also have a serious bias in their data and fail in their theoretical framing, which makes the results pretty suspect. ↩