Why should I bother trying to establish a relation between the complexity of a game and its success? Real data on sales and perceived complexity suggests seemingly conflicting evidence. We all know Tetris, which doesn’t seem to be complex at all, but is one of the most successful games that ever existed. On the other hand, one could argue that Grand Theft Auto is equally successful1, while being more complex by multiple degrees. Does this mean that any relation between complexity and success is purely coincidental? Or do we have to dig deeper to grasp the coherence? Just follow me on my way of reaching clarification and engage in a discussion at the bottom of this page.
Complex, or not complex: that is the question
I won’t start with an introduction about what complexity is or is not. I think we all (we, who play games) have a feeling for what complexity is, especially when we encounter it in the games we play. In this blog post I am referring to the complexity of gameplay only (in the sense of complex gameplay mechanics). Of course, there are more levels, on which a game can be complex. I propose the following classification:
- Gameplay complexity: Characterized by sophisticated gameplay mechanics including interrelations between different in- and output variables (Tower Defense <-> Anno).
- Narrative complexity: Elaborated decision trees with impact on key elements of the game (Super Mario <-> Heavy Rain).
- Skill complexity: Requires fine dexterity and accurate timing in the execution of physical actions to manipulate game states (Minesweeper <-> Street Fighter).
- Cognitive complexity: Includes higher cognitive skills like spatial & temporal mental transformation, planning and reasoning (Tetris <-> FoldIt).
But let’s get back to the topic: Imagine you have the honorable task to design a game. How many features are too little and how many are too many? How complex must your game be to squeeze the most fun out of it?
There is one evil superstition circulating, that casual gamers demand simplicity and core gamers complexity. Although this might be true in many cases, explanations are not theory-driven but occur in hindsight. Furthermore, no one really knows how to define a casual or a core gamer. But before talking about the when and how, let’s talk about the why.
Complexity and fun: a love-hate relationship
Complexity is in its perception subjectively, which can be explained best with the concept of Flow3. You probably heard about Flow many times already, so I won’t go into detail (for more information about this topic take a look at this blog post2). For Flow (the mother of fun as we could call it) a necessary condition is the right balance between challenge and skills. Obviously, an increased complexity comes often with an increased level of challenge. And when we use fun as “just another word for learning” (like Raph Koster does in his book “A Theory of Fun for Game Design”4), we can assume (and as gamers we really know) that the skill factor is successively improving as a function of playtime. So what does this mean? Complexity increases fun and contributes to long-term motivation when it unfolds at the right time and at the right speed. But beware of exposing too much of it too early: you will make your users run (not in-game but away from it). This is exactly what tutorials and balancing (the guidance of mastery) try to prevent.
Complexity: getting the right dosage
One main principle in user-centered design is KNOW YOUR USERS. This doesn’t mean that we simply label our users as core or casual gamers. A tactic I suggest is to develop research-based personas. To identify the right degree of complexity for your game, your persona template should include:
- Basic demographics, such as age (for spotting limitations in cognitive abilities and information processing) and gender (for gender-related preferences).
- Preferred platform like browser or mobile (which has an influence on the expected mean playtime per session and the design-relevant ease to access/use for complex features)
- Personality attributes like frustration-tolerance and need for cognition (to determine how eager for rewards your users are and how to design the balancing curve).
- Of course you can add more points, depending on what makes sense for your game vision.
Notice, that this data can be helpful to build a conclusive theory-driven game design but is no guarantee for success. No matter, how detailed your use cases are and how well you mastered the method of cognitive walkthrough, you still have to do extensive user testing in order to get it right.
1. List of best-selling video game franchises, http://en.wikipedia.org/wiki/List_of_best-selling_video_game_franchises, 06.11.2012.
2. Flow, Games and User Experience – Part 1, http://blog.bigpoint.net/ux/flow-games-and-user-experience-part-1/, 06.11.2012.
3. Csíkszentmihályi, Mihály (1975), Beyond Boredom and Anxiety, San Francisco, CA: Jossey-Bass, ISBN 0-87589-261-2
4. Koster, Raph (2005). A Theory of Fun for Game Design. Paraglyph Press. ISBN 1-932111-97-2.
Note: This piece originally appeared on the Bigpoint company blog.