Free Theory of Fun for Game Design by Raph Koster Page A

the players during the bridge game.
A solid core mechanic . This is a puzzle to solve, an intrinsically interesting rule set into which content can be poured. An example might be “moving a piece in chess.” The core mechanic is usually a fairly small rule; the intricacies of games come from either having a lot of mechanics or having a few, very elegantly chosen ones.
A range of challenges . This is basically content. It does not change the rules, it operates within the rules and brings slightly different parameters to the table. Each enemy you might encounter in a game is one of these.
A range of abilities required to solve the encounter . If all you have is a hammer and you can only do one thing with it, then the game is going to be dull. This is a test that tic-tac-toe fails but that checkers meets; in a game of checkers you start learning the importance of forcing the other player into a disadvantageous jump. Most games unfold abilities over time, until at a high levels you have many possible stratagems to choose from.
Skill required in using the abilities . Bad choices lead to failure in the encounter. This skill can be of any sort, really: resource management during the encounter, failures in timing, failures in physical dexterity, and failures to monitor all the variables that are in motion.

    A game having all of these elements hits the right cognitive buttons to be fun. If a game involves no preparation, we say it relies on chance. If there’s no sense of space, we call it trivial. If there’s no core mechanic, there’s no game at all. If there’s no range of challenges, we exhaust it quickly. If there’s no multiple choices to make, it’s simplistic. And if skill isn’t required, it’s tedious.
    There are also some features that should be present to make the experience a learning experience:
    A variable feedback system . The result of the encounter should not be completely predictable. Ideally, greater skill in completing the challenge should lead to better rewards. In a game like chess, the variable feedback is your opponent’s response to your move.
The Mastery Problem must be dealt with . High-level players can’t get big benefits from easy encounters or they will bottom-feed. Inexpert players will be unable to get the most out of the game.
Failure must have a cost . At the very least there is an opportunity cost, and there may be more. Next time you attempt the challenge, you are assumed to come into it from scratch—there are no—“do-overs.” Next time you try, you may be prepared differently.
    Looking at these elementary particles that make up ludemes, it’s easy to see why most games in history have been competitive head-to-head activities. It’s the easiest way to constantly provide a new flow of challenges and content.

    Historically, competitive game-playing of all sorts has tended to squeeze out the people who most need to learn the skills it provides, simply because they aren’t up to the competition and they are eliminated in their first match. This is the essence of the Mastery Problem. Because of this, a lot of people prefer games that take no skill. These people are definitely failing to exercise their brains correctly. Not requiring skill from a player should be considered a cardinal sin in game design . At the same time, designers of games need to be careful not to make the game demand too much skill. They must keep in mind that players are always trying to reduce the difficulty of a task. The easiest way to do that is to not play.
    This isn’t an algorithm for fun, but it’s a useful tool for checking for the absence of fun because designers can identify systems that fail to meet all the criteria. It may also prove useful in terms of game critique. Simply check each system against this list:
    Do you have to prepare before taking on the challenge?
Can you prepare in different ways and still succeed?
Does the environment in which the challenge takes place affect the