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On the evolution of athlete anthropometric measurements: racial integration, expansion, and steroids

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Abstract

We examine the temporal movements in three anthropometric measurements of a professional sport’s athlete population. Specifically, we examine unit root test results, traditional, nonlinear, and those that allow of possible structural breaks, for average player height, weight, and body mass index for the population of Major League Baseball athletes over the period 1901–2019. These anthropometric measures are likely associated with the athletes’ level of productivity. In the end, we find that the average values for the measures of players’ body mass index and weight are found to be nonstationary, while the average values of players’ height are stationary around a nonlinear trend. We further find that these series have been subject to a number of structural shocks. These shocks correspond to well-known events in Major League Baseball history, such as its ‘Deadball’ era, racial integration, periods of Major League Baseball expansion, innovations with respect to player management, the advent of free agency, and the so-called Steroid Era.

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Notes

  1. The BMI measure—the ratio of the weight in kilograms divided by the square of the height in meters—was first described by Quetelet (1832). The measure was known as the Quetelet Index until it was termed the Body Mass Index by Keys et al. (1972).

  2. Average life expectancy rose from roughly 30 years in the 1730s to roughly 50 years by 1900. See Floud et al. (2011).

  3. Gorry (2017) finds that an extra inch of height is associated with an increase in reported GPA by about 0.013 points. A foot of difference in height, therefore, is associated with an increase in GPA by approximately one-fifth of a standard deviation on average.

  4. Greater coordination, such as enhancing broader cooperation or promoting more regional integration in the health policies, may facilitate the transfer of information across countries thereby increasing policy effectiveness (Kasman and Kasman 2020)”.

  5. Bud Sielig, the MLB’s Commissioner, commissioned the report after the publication of Game of Shadows and a Congressional Hearing on Baseball’s use of steroids in 2005. See Lichtman (2009).

  6. All player data were taken from http://www.baseball-reference.com.

  7. We turn to estimating any possible shocks to these in the next two sections.

  8. The latter two augment the traditional ADF and LM test.

  9. For continuity, we refer to Perron and Yabu’s A2 approach as Model 1 and their A3 approach as Model 2.

  10. We thank an anonymous referee for the suggestion.

  11. While a long time series of anthropometric data is largely lacking, we were able or a subset of the data, 1914:2014, for United States average population height from the NCD Risk Factor Collaboration (https://www.ncdrisc.org/data-downloads-height.html).

  12. For the Bai and Perron (2003) approach, the detrended series estimates two breaks. The first of these breaks, however, has a very large 95% confidence interval—1938–1960—and the second has an interval from 1980–1983. The latter matches the earlier result, while former overlaps two of the earlier findings, i.e., 1958–1962 and 1944–1949. The two earlier estimated breaks, 1933–1937 and 1911–1920—are largely excluded as the detrended data begins nearly 15 years later.

  13. See Schmidt (2020), for a review of this literature.

  14. The obvious downturn in the average number of players in 1994 and 1995 was an outgrowth work stoppage that forced the cancellation of 948 games between the end of the 1994 and the start of the 1995 season.

  15. In 1922, for example, New York Giants paid the San Francisco Seals $75,000 for the contract of Jimmy O’Connell, who had been favorably compared to Babe Ruth

  16. See Gordon (2018) for a through discussion on these factors.

  17. Nightwatch—September 28th, 1988.

  18. In his book Juiced, Canseco writes that he believes that 85% of MLB players were using steroids during this period. See Canseco (2005).

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  1. Department of Economics, William & Mary, P.O. Box 8795, Williamsburg, VA, 23187-8795, USA

    Martin B. Schmidt

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Schmidt, M.B. On the evolution of athlete anthropometric measurements: racial integration, expansion, and steroids. Empir Econ 61, 3419–3443 (2021). https://doi.org/10.1007/s00181-020-02012-0

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