Social and Behavioral Sciences Commons^™

Data Clustering For Fitting Parameters Of A Markov Chain Model Of Multi-Game Playoff Series, Christopher M. Rump

Applied Statistics and Operations Research Faculty Publications

We propose a Markov chain model of a best-of-7 game playoff series that involves game-togame dependence on the current status of the series. To create a relatively parsimonious model, we seek to group transition probabilities of the Markov chain into clusters of similar game-winning frequency. To do so, we formulate a binary optimization problem to minimize several measures of cluster dissimilarity. We apply these techniques on Major League Baseball (MLB) data and test the goodness of fit to historical playoff outcomes. These state-dependent Markov models improve significantly on probability models based solely on home-away game dependence. It turns out that …