Date of Graduation

5-2020

Document Type

Thesis

Degree Name

Bachelor of Science

Degree Level

Undergraduate

Department

Industrial Engineering

Advisor/Mentor

Pohl, Edward A.

Committee Member/Reader

Sullivan, Kelly M.

Committee Member/Second Reader

N/A

Committee Member/Third Reader

N/A

Committee Member/Fourth Reader

N/A

Abstract

Professional sports teams are important to their local economies, so successful franchises are significant contributors to their prosperity. This need for successful teams drives the owners and general managers to perform in-depth analyses on potential players to gain insight, so the best players can be chosen. Major League Baseball is one of the largest sports leagues in the world, so their analysis of players must be excellent to ensure they sign the best players and can compete at a high level.

Baseball is a complex sport with many different statistics evaluating nearly every part of a player’s game. Because of its complexity, professional baseball relies on statistics more than any of the other professional sports. General managers and scouts for teams analyze players using a variety of statistics, so ensuring current statistics that meet their needs are available is vital. Continuously updating and developing new statistics is extremely important to keep professional baseball near the top of the professional sports world. This analysis develops a new offensive statistic for use by MLB teams when they consider what players to sign during free agency. The approach used attempts to improve an existing statistic then combines the improved statistic with another statistic to gain a new perspective on player analysis.

Keywords

Baseball Analytics; MLB Player Performance Measures

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