Date of Award

December 2014

Degree Type

Thesis

Degree Name

Master of Science

Department

Computer Science

First Advisor

Mukul Goyal

Committee Members

Ethan Munson, Hossein Hosseini

Keywords

Baseball, Markov

Abstract

In this work we confirm a Markov chain model of baseball for 2013 Major League Baseball batting data. We describe the transition matrices for individual player data and their use in generating single and nine-inning run distributions for a given lineup. The run distribution is used to calculate the expected number of runs produced by a lineup over nine innings. We discuss batting order optimization heuristics to avoid computation of distributions for the 9! = 362, 880 distinct lineups for 9 players. Finally, we describe an implementation of the algorithms and review their performance against actual game data.

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