Date

12-22-2016

Document Type

Thesis

Abstract

Ever since Oakland Athletics’ general manager Billy Beane began applying analytical tools to compose a baseball team, professional sports teams have used advanced metrics to build competitive rosters. We use an exploratory data analysis strategy to find what statistics best predict team wins. Finding that the Player Efficiency Rating (PER) statistic best correlate with wins, we investigate the statistic to find its strengths and weaknesses. We look for ways to improve the statistic and adjust it to better evaluate player effectiveness. We also look for methods to best predict how the PER will change from one season to the next based on player age and experience in the league.

Department

Mathematics

Thesis Comittee

Ward Heilman (Thesis Mentor)

John Pike

Kevin Rion

Copyright and Permissions

Original document was submitted as an Honors Program requirement. Copyright is held by the author.

Included in

Mathematics Commons

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