Improving Major League Baseball Park Factor Estimates

Acharya Rohit A, Ahmed Alexander J, D'Amour Alexander N, Lu Haibo, Morris Carl N, Oglevee Bradley D, Peterson Andrew W and Swift Robert N
Additional contact information
Acharya Rohit A: Harvard University
Ahmed Alexander J: Harvard University
D'Amour Alexander N: Harvard University
Lu Haibo: Harvard University
Morris Carl N: Harvard University
Oglevee Bradley D: Harvard University
Peterson Andrew W: Harvard University
Swift Robert N: Harvard University

Journal of Quantitative Analysis in Sports, 2008, vol. 4, issue 2, 18

Abstract: The study of Park Factors (PF) is essential to the correct evaluation of player performance in Major League Baseball. We have identified two important problems with the commonly used formula which has been popularized by ESPN: it produces variable results due to unbalanced scheduling, and it has an inherent inflationary bias. To address these problems, we develop a new estimator for Park Factors using an ANOVA weighted fixed-effects model for run generation. Using simulated data, in addition to run data from 2000 through 2006, we show that this new estimator does not have the biases of the old estimator. From a strategic viewpoint, accurate PF values are needed to properly evaluate free agents and trade proposals, as well as to compare players for postseason awards. We develop a method to adjust statistics using Park Factors called a Neutral Park Adjustment (NPA), which takes into account the Park Factors of the entire schedule of a player, not simply their home park.

Keywords: park factor; baseball; hitter’s park; pitcher’s park; neutral park adjustment (search for similar items in EconPapers)
Date: 2008
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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DOI: 10.2202/1559-0410.1108

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