The expected-outcome model, in which the proper evaluation of a game-tree node is the expected value of the game's outcome given random play from that node on, is proposed. Expected outcome is considered in its ideal form, where it is shown to be a powerful heuristic. The ability of a simple random sampler that estimates expected outcome to outduel a standard Othello evaluator is demonstrated. The sampler is combined with a linear regression procedure to produce efficient expected-outcome estimators. Overall, the expected-outcome model of two-player games is shown to be precise, accurate, easily estimable, efficiently calculable, and domain-independent. >