First Advisor

Kate Freier

Date of Award

Spring 6-14-2026

Document Type

Thesis

Degree Name

Bachelor of Science (B.S.) in Data Science and University Honors

Department

Mathematics and Statistics

Language

English

Subjects

fWAR, bWAR, baseball, wins above replacement, sabermetrics, WAR

Abstract

Pitching Wins Above Replacement (WAR) is an area of sabermetrics capable of being used to predict regular season success in Major League Baseball. Fangraphs WAR (fWAR) and Baseball Reference WAR (bWAR) were used to construct regression models to predict regular season winning percentage, to build logistic models to establish a relationship between pitching WAR and the probability to win an individual regular season game, and to overlay density plots to consider WAR accumulation by pitching role and observe the difference of impact between starter and relief pitchers. This research finds that while pitching fWAR and pitching bWAR are both statistically significant predictors of win percentage and individual game success, fWAR generally outperforms bWAR as an overall predictor in both models. Further research might seek to investigate how the relationship between pitching fWAR and pitching bWAR compares to offensive fWAR and offensive bWAR and whether fWAR continues to reign supreme in offensive contexts as well.

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