Abstract
This paper develops a simulator for matches in Major League Baseball (MLB). Aspects of the approach that are studied include the introduction of base-running probabilities which were obtained through a large data set, and the simulation of nine possible outcomes for each at-bat. Various applications to the simulator are investigated, such as the definition of a measure of the ability of a batter/pitcher, in-play strategy and the determination of the optimal batting order for a given team.
The author has been partially supported by a research grant from the Natural Sciences and Engineering Research Council of Canada. A special thanks to the Mathematics and Statistics Department at Laval for the use of its computing resources.
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