Researcher ORCID Identifier
0000-0002-2635-0549
Graduation Year
2021
Date of Submission
4-2021
Document Type
Open Access Senior Thesis
Degree Name
Bachelor of Arts
Department
Economics
Reader 1
Angela Vossmeyer
Terms of Use & License Information
Rights Information
© 2021 Hank S Snowdon
Abstract
Utilizing thirteen years of Major League Baseball pitch-tracking and play-by-play data, this study investigates racial discrimination by umpires when making pitch calling decisions. Two models are formulated, one that predicts the probability of a strike erroneously being called a ball (batter favoritism) and one that predicts the probability of a ball erroneously being called a strike (pitcher favoritism). The probabilities are modeled as a function of whether or not the pitcher’s or batter’s race is the same as the umpire’s. With over 3 million pitch observations, multiple sub-sample and time trend analyses are conducted to examine with whom the discrimination lies and how it changes throughout the sample. The results suggest that umpires are significantly more likely to make calls that favor players of the same race, and that these effects have not diminished between 2008 and 2020. Furthermore, these biases seem mostly held by White umpires, who account for a wide majority of umpires in MLB.
Recommended Citation
Snowdon, Hank, "Would “Robot Umpires” Reduce Discrimination? Measuring Racial Bias in Major League Baseball Umpires" (2021). CMC Senior Theses. 2677.
https://scholarship.claremont.edu/cmc_theses/2677
