Date of Submission

Spring 2017

Academic Programs and Concentrations

Mathematics

Project Advisor 1

Stefan Mendez-Diez

Abstract/Artist's Statement

Baseball is a very strategic and abstract game, but the baseball world is strangely obsessed with statistics. Modern mainstream statisticians often study offensive data, such as batting average or on-base percentage, in order to evaluate player performance. However, this project observes the game from the opposite perspective: the defensive side of the game. In hopes of analyzing the game from a more concrete perspective, countless mathemeticians - most famously, Bill James - have developed numerous statistical models based on real life data of Major League Baseball (MLB) players. Large numbers of metrics go into these models, but what this project attempts to quantify specifically how positioning of defensive players in baseball ultimately affects the success of those players. This consults the use of multivariate probability distributions and models that allow us to study how good players really are based on data.

Open Access Agreement

Open Access

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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