Abstract
In this paper we look at the state of the MLB before and after the ban of the shift. The shift is a strategy in baseball where coaches will move infielders and outfielders outside of their normal zones in order to better cover a certain hitter. This strategy was very effective, and it was banned following the 2022 MLB season. To investigate further, we create a logistic regression model to predict hits and a linear regression model to predict ERA before and after the shift. The entirety of the data is focused on left handed hitters. After testing model effectiveness, we find that after the ban of the shift, ground balls that are pulled result in a hit about one and a half times as often as they do when the shift was allowed. Nearly all types of pulled balls in play see a major increase in probability of being a hit. Following this trend, ground balls that are not pulled have about half the probability of being a hit compared to before the ban. In the other model, we find that after the ban of the shift, strikeouts are more important than ever to maintaining a strong ERA. Interestingly, getting more ground balls after the shift also helps a pitcher’s ERA even more than it did prior. The results in this study can be used to shape pitcher strategy in the MLB now that the shift is no longer allowed.
Advisor
Long, Colby
Department
Mathematics
Recommended Citation
Westrick, Elijah, "How the Ban of the Shift Affected Pitchers in the MLB" (2024). Senior Independent Study Theses. Paper 11131.
https://openworks.wooster.edu/independentstudy/11131
Disciplines
Analysis | Applied Statistics | Data Science | Physical Sciences and Mathematics
Keywords
Modeling, MLB, Baseball, Shift Analysis, Predictive
Publication Date
2024
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2024 Elijah Westrick
