Theory of Fun for Game Design

Free Theory of Fun for Game Design by Raph Koster

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Authors: Raph Koster
Tags: COMPUTERS / Programming / Games
work. We like to find ways to keep from doing something over and over. We dislike tedium, sure, but the fact is that we crave predictability . Our whole life is built on it. Unpredictable things are stuff like drive-by shootings, lightning bolts that fry us, smallpox, food poisoning—unpredictable things can kill us! We tend to avoid them. We instead prefer sensible shoes, pasteurized milk, vaccines, lightning rods, and laws. These things aren’t perfect, but they do significantly reduce the odds of unpredictable things happening to us.
    And since we dislike tedium, we’ll allow unpredictability, but only inside the confines of predictable boxes, like games or TV shows. Unpredictability means new patterns to learn, therefore unpredictability is fun. So we like it, for enjoyment (and therefore, for learning). But the stakes are too high for us to want that sort of unpredictability under normal circumstances. That’s what games are for in the first place—to package up the unpredictable and the learning experience into a space and time where there is no risk.
    The natural instinct of a game player is to make the game more predictable because then they are more likely to win.

    This leads to behaviors like “bottom-feeding,” where a player will intentionally take on weaker opponents under the sensible logic that a bunch of sure wins is a better strategy than gambling it all on an iffy winner-take-all battle. Players running an easy level two hundred times to build up enough lives so that they can cruise through the rest of the game with little risk is the equivalent of stockpiling food for winter: it’s just the smart thing to do .
    This is what games are for . They teach us things so that we can minimize risk and know what choices to make. Phrased another way, the destiny of games is to become boring, not to be fun . Those of us who want games to be fun are fighting a losing battle against the human brain because fun is a process and routine is its destination.
    So players often intentionally suck the fun out of a game in hopes they can learn something new (in other words, find something fun) once they complete the task. They’ll do it because they perceive it (correctly) as the optimal strategy for getting ahead. They’ll do it because they see others doing it, and it’s outright unnatural for a human being to see another human being succeeding at something and not want to compete.
    All of this happens because the human mind is goal driven. We make pious statements like “it’s the journey, not the destination,” but that’s mostly wishful thinking. The rainbow is pretty and all, and we may well enjoy gazing at it, but while you were gazing, lost in a reverie, someone else went and dug up the pot of gold at the end of it.
    Rewards are one of the key components of a successful game activity; if there isn’t a quantifiable advantage to doing something, the brain will often discard it out of hand. What are the other fundamental components of a game element, the atoms of games, so to speak? Game designer Ben Cousins calls these “ludemes,” the basic units of gameplay. We’ve talked about several of them, such as “visit everywhere” and “get to the other side.” There are many left to discover, we hope. In the end, though, they are almost always made up of the same elementary particles.

    Successful games tend to incorporate the following elements:
    Preparation . Before taking on a given challenge, the player gets to make some choices that affect their odds of success. This might be healing up before a battle, handicapping the opponent, or practicing in advance. You might set up a strategic landscape, such as building a particular hand of cards in a card game. Prior moves in a game are automatically part of the preparation stage because all games consist of multiple challenges in sequence.
A sense of space . The space might be the landscape of a war game, a chess board, the network of relationships between

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