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Journal of Quantitative Analysis in Sports

An official journal of the American Statistical Association

Editor-in-Chief: Glickman, PhD, Mark

4 Issues per year


SCImago Journal Rank (SJR) 2015: 0.288
Source Normalized Impact per Paper (SNIP) 2015: 0.358
Impact per Publication (IPP) 2015: 0.250

Online
ISSN
1559-0410
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An Exploratory Study of Minor League Baseball Statistics

Gabriel Chandler
  • Pomona College
/ Guy Stevens
  • Pomona College '13
Published Online: 2012-11-12 | DOI: https://doi.org/10.1515/1559-0410.1445

Abstract

We consider the problem of projecting future success of Minor League baseball players at each level of the farm system. Using tree based methods, in particular random forests, we consider which statistics are most correlated with Major League success, how Major League teams use these statistics differently in handling prospects, and how prior belief in a players ability, measured through draft position, is used throughout a players Minor League career. We show that roughly the 18th round prospect corresponds to being draft neutral for a team, whereas teams essentially make decisions based strictly on performance. We use for our data all position players drafted between 1999 and 2002.

Keywords: random forests; baseball; classification

About the article

Published Online: 2012-11-12


Citation Information: Journal of Quantitative Analysis in Sports, ISSN (Online) 1559-0410, DOI: https://doi.org/10.1515/1559-0410.1445. Export Citation

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