Abstract
This paper explores the predictive power of perhaps the most well-supported human performance model in the context of a complex ecological task. The model is Fitts Law, which describes the classic speed-accuracy tradeoff of goal-directed motor behavior. The task is modern pistol shooting competition, which demands explicit cognitive strategy and full-body biomechanical coordination. Data obtained via video analysis indicate that Fitts Law can in fact predict human performance in competitive shooting. Speed-accuracy tradeoffs for target transitions are further investigated to determine an optimal pace for competitive shooting in order to maximize score. A Monte Carlo simulation is also offered which develops a probability distribution of possible scores based on accuracy and pace, all informed only by a calibrated Fitts model.
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