Variance decompositions for extensive-form games

Quantitative measures of randomness in games are useful for game design and have implications for gambling law. We treat the outcome of a game as a random variable and derive a closed-form expression and estimator for the variance in the outcome attributable to a player of the game. We analyze poker hands to show that randomness in the cards dealt has little influence on the outcomes of each hand. A simple example is given to demonstrate how variance decompositions can be used to measure other interesting properties of games.

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