An Exploratory Study of Minor League Baseball Statistics
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.
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Volume (Year): 8 (2012)
Issue (Month): 4 (November)
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Stephen J. Spurr & William Barber, 1994. "The Effect of Performance on a Worker's Career: Evidence from Minor League Baseball," ILR Review, Cornell University, ILR School, vol. 47(4), pages 692-708, July.
- Neil Longley & Glenn Wong, 2011. "The speed of human capital formation in the baseball industry: the information value of minor‐league performance in predicting major‐league performance," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 32(3), pages 193-204, April.
- Archer, Kellie J. & Kimes, Ryan V., 2008. "Empirical characterization of random forest variable importance measures," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2249-2260, January.
- Mills Brian M. & Salaga Steven, 2011. "Using Tree Ensembles to Analyze National Baseball Hall of Fame Voting Patterns: An Application to Discrimination in BBWAA Voting," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(4), pages 1-32, October.
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