Statistical Analysis of Defensive Production in Major League Baseball
Jun 1, 2006·
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1 min read
Christopher Teixeira
While many statistical measures have been devised to measure team and player performance in professional baseball, relatively little work has been done to study and improve measures of defensive performance. This project’s goals were to model defensive contribution to team performance and develop related measures of individual player defensive production. Factor analysis was employed to extract positional factors and combine them with pitching and offensive measures into a final logistic regression model to determine effects of defense on team performance.
Authors
Christopher Teixeira
(he/him)
Data Scientist
Christopher Teixeira is a Data Scientist with extensive experience applying statistics, applied probability,
and operations research to solve complex organizational challenges. Throughout his career, he has partnered with
diverse stakeholders to drive data-informed decision-making, helping organizations navigate the nuances of various
analytical techniques to find optimal solutions. Christopher has a proven track record of delivering code in multiple languages,
leading large-scale technical efforts, and responding to technical proposals and developing relationships with customers.
He holds an M.S. in Operations Research from George Mason University and a B.S. in Mathematics from Worcester Polytechnic Institute.