Detrending career statistics in professional baseball: Accounting for the steroids era and beyond

Details Detrending career statistics in professional baseball: Accounting for the steroids era and beyond Detrending career statistics in professional baseball: Accounting for the steroids era and beyond

2010-02-28

arxiv.org/abs/1003.0134v2

Eur. Phys. J. B 79, 67-78 (2011)

Physics

Physics and Society

24 pages, 7 figures, 11 Tables; Published under title: "Methods for detrending success metrics to account for inflationary and

Scientific paper

10.1140/epjb/e2010-10647-1

There is a long standing debate over how to objectively compare the career achievements of professional athletes from different historical eras. Developing an objective approach will be of particular importance over the next decade as Major League Baseball (MLB) players from the "steroids era" become eligible for Hall of Fame induction. Here we address this issue, as well as the general problem of comparing statistics from distinct eras, by detrending the seasonal statistics of professional baseball players. We detrend player statistics by normalizing achievements to seasonal averages, which accounts for changes in relative player ability resulting from both exogenous and endogenous factors, such as talent dilution from expansion, equipment and training improvements, as well as performance enhancing drugs (PED). In this paper we compare the probability density function (pdf) of detrended career statistics to the pdf of raw career statistics for five statistical categories -- hits (H), home runs (HR), runs batted in (RBI), wins (W) and strikeouts (K) -- over the 90-year period 1920-2009. We find that the functional form of these pdfs are stationary under detrending. This stationarity implies that the statistical regularity observed in the right-skewed distributions for longevity and success in professional baseball arises from both the wide range of intrinsic talent among athletes and the underlying nature of competition. Using this simple detrending technique, we examine the top 50 all-time careers for H, HR, RBI, W and K. We fit the pdfs for career success by the Gamma distribution in order to calculate objective benchmarks based on extreme statistics which can be used for the identification of extraordinary careers.

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