Honors Projects

Kolin AtwoodFollow

Abstract

Traditional Wins Above Replacement (WAR) metrics have long served as a cornerstone of player evaluation in Major League Baseball, offering a context-neutral summary of offensive, defensive, and baserunning contributions. However, this neutrality often overlooks critical factors such as game situation, lineup strength, and advanced baserunning impact. This project proposes an enhanced model, WAR-PC (Wins Above Replacement – Plus Context), that integrates three key improvements: context-dependent batting value (RE24), clutch performance (Win Probability Added, WPA), and Statcast-based baserunning metrics. Using R, player logs, and modern baseball data sources, WAR-PC was calculated for eight players from the 2023 MLB season. The revised model better rewards players who perform in high-leverage situations, drive in runs when opportunities arise, and create value on the basepaths. Results show significant WAR increases for players like Brent Rooker and Corey Seager, whose real-world impact was greater than traditional WAR suggested. WAR-PC offers teams a valuable new tool for roster construction, highlighting players whose situational excellence can drive wins beyond raw statistics. This interdisciplinary project demonstrates how data science and athletics can intersect to produce more nuanced, actionable player evaluations, supporting smarter decision-making in both free agency and player development.

Department

Mathematics and Statistics

Major

Mathematics

First Advisor

Umar Islambekov

First Advisor Department

Mathematics and Statistics

Second Advisor

Earl McKinney

Second Advisor Department

Accounting and Management Information Systems

Publication Date

Spring 4-28-2025

Additional Files
Final HNRS Presentation.pptx (1007 kB)
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