This post is part of a three-part Skeleton Code Machine series on player types: Part 1: The 8 Kinds of Fun, Part 2: Bartle Taxonomy, Part 3: Quantic Gamer Motivations.
Last week’s exploration of Marc Leblanc’s 8 Kinds of Fun really got me thinking about game genres, player types, and how we can better describe what we mean when say, “This game is fun!”
I made a brief mention of the Bartle Taxonomy in the post, and this week we do a deeper dive on that concept! Don’t miss the poll at the end!
The Bartle Taxonomy
Richard Bartle is the creator of the first MUD in 1978, and an MMORPG researcher.
In 1996 he posted an article called Hearts, Clubs, Diamonds, Spades: Players Who Suit MUDs. In it, he attempts to identify and describe MUD player types:
Four approaches to playing MUDs are identified and described. These approaches may arise from the inter-relationship of two dimensions of playing style: action versus interaction, and world-oriented versus player-oriented. An account of the dynamics of player populations is given in terms of these dimensions, with particular attention to how to promote balance or equilibrium. This analysis also offers an explanation for the labelling of MUDs as being either "social" or "gamelike".
His research began with asking players, “What do you want from this game?”
The “interest graph” (shown above) in the post has become well-known in the game design industry, and still has applications almost 30 years after its creation.
Let’s take a look at the X axis and Y axis of this quadrant-based model!
Acting vs. Interacting
The Y axis is Acting vs. Interacting. In this case, Acting refers to the desire to act upon something as opposed to Interacting which is to act with someone or something. Someone who wants to just master and beat the game might be more toward “acting” while someone more interested in socializing and exploring seeks “interacting.”
Players vs. World
The X axis is Players vs. World. In general this is the division between players who want to have other players around vs. players who prefer a solo world. Though that is not always the case. The desire for other players might come in the form of NPC relationships or the meta-players of Twitch and Actual Play communities.
The four types of players
What I find most interesting are the four quadrants proposed as combinations of Acting vs. Interacting and Players vs. World:
Killers (Acting + Players): Competitive and enjoy dominating the game and/or other players. They want to defeat opponents and win, including via take-that mechanisms. Griefers might fit this category too.
Achievers (Acting + World): Thrive on accomplishing in-game goals like leveling up, collecting legendary items, or maxing out skill trees. These players want XP, gold, NG+ modes, and achievement. The fun is in mastering the game.
Socializers (Interacting + Players): The game is a way to connect with other players. They enjoy relationships, forming alliances, and engaging in the social aspects of the game. Building communities, trading, and helping others can be enjoyable both in and out of the game.
Explorers (Interacting + World): The joy of discovery and uncovering new parts of the game. The gameplay is a tool used to explore the world and/or mechanisms. Finding Easter eggs and novel ways of solving problems are enjoyable.
While these types are based on people playing MUDs in the 1990s, it’s easy to see how they might apply to tabletop games. The interactions between these types (and mismatch between expectations) is something to consider in game design.
For example, an Achiever player who wants to master a board game and maximize their engine might be very upset by a Killer who can destroy parts of their tableau. Similarly, a Socializer might be disappointed in a low player interaction Euro-style game, while an Explorer might enjoy finding ways to unlock new strategies.
All models are wrong
“All models are wrong, but some are useful.” — George Box
There’s an aphorism in data science commonly attributed to British statistician George Box that says, “All models are wrong, but some are useful.”
I’ve always thought that to be a wonderful way of thinking about models! You can never make a perfect model or abstraction of reality (c.f. gemba), but that doesn’t mean those models and abstractions are worthless.
Bartle’s Taxonomy is imperfect. It has limited explanatory power as a universal framework. His sample size was fairly small and (probably) not particularly diverse. Some players can’t be pinned down to just one quadrant. Not every Killer is a griefer.
And yet, similar to the 8 Kinds of Fun, the taxonomy gives us an improved vocabulary to have discussions about play styles. We can use the quadrants to assess new mechanisms and predict who might enjoy them.
The taxonomy might be wrong, but it can certainly be useful!
Conclusion
Some things to think about:
The appeal of mechanisms: Consider plotting game mechanisms on the interest graph and seeing who they might appeal to most. It probably appeals to multiple types, but there might be a dominant type.
Players are not monolithic: You’ll never be able to fit all the players of a game into a single quadrant. It’s probably a good idea to have an “ideal player” in mind, but understand that there are an infinite number of ways that players will approach a game.
Imperfect models are still useful: Rather than dismissing models as being too limited or simplified, consider reading about additional models. Combining the knowledge and language of multiple frameworks can lead to having a helpful toolkit for game design.
Let’s try a poll this week! What type of player are you? Which of the four classifications best describes your preferred actions within a game?
— E.P. 💀
P.S. Exeunt Press will have a vendor booth at Save Against Fear!
Skeleton Code Machine is a production of Exeunt Press. If you want to see what else is happening at Exeunt Press, check out the Exeunt Omnes newsletter.
Admit it. One of you is a Killer (Acting + Players) type. ;)
I’ve recently come to realize that my regular D&D group is made up of socializers, while I am more of an explorer. It’s helped me identify points of frustration and understand my group better. It’s also helped me find other games that scratch that itch.