2025 MONEYBALL ACADEMY, ROOKIE REVIEW

AUTHOR

Jack Whitney-Epstein, University of Pennsylvania (Moneyball Academy)
Jackson Hubbard, University of Pennsylvania (Moneyball Academy)
Lila Dodson, University of Pennsylvania (Moneyball Academy)
William Deflorio, University of Pennsylvania (Moneyball Academy)
Zach Sissman, University of Pennsylvania (Moneyball Academy)

ABSTRACT

This project examines how Major League Baseball baserunners can optimize their lead distance from first base when attempting to steal second. Using factors including runner sprint speed, pitcher pickoff threat, catcher pop time, and lead distance, the researchers developed a statistical model to estimate the probabilities of a successful stolen base, caught stealing, or pickoff and translate those outcomes into expected runs. The model identifies an optimal lead for each individual situation rather than applying one standard distance to every runner and matchup.

Results suggest that MLB runners generally take leads that are too short and that optimizing lead distance—sometimes by roughly one additional shuffle—could add approximately 0.02 expected runs.