SEAM methodology for context-rich player matchup evaluations
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We develop the SEAM (synthetic estimated average matchup) method for describing batter versus pitcher matchups in baseball, both numerically and visually. We first estimate the distribution of balls put into play by a batter facing a pitcher, called the spray chart distribution. This distribution is conditional on batter and pitcher characteristics. These characteristics are a better expression of talent than any conventional statistics. Many individual matchups have a sample size that is too small to be reliable. Synthetic versions of the batter and pitcher under consideration are constructed in order to alleviate these concerns. Weights governing how much influence these synthetic players have on the overall spray chart distribution are constructed to minimize expected mean square error. We then provide novel performance metrics that are calculated as expectations taken with respect to the spray chart distribution. These performance metrics provide a context rich approach to player evaluation. Our main contribution is a Shiny app that allows users to evaluate any batter-pitcher matchup that has occurred or could have occurred in the last five years. One can access this app at <https://seam.stat.illinois.edu/app/>. This interactive tool has utility for anyone interested in baseball as well as team executives and players.
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