The "Fair" Triathlon: Equating Standard Deviations Using Bayesian Nonlinear Models

Curtis S. McKay, Fellingham Gilbert W and Reese C. Shane
Additional contact information
Curtis S. McKay: North Carolina State University
Fellingham Gilbert W: Brigham Young University
Reese C. Shane: Brigham Young University

Journal of Quantitative Analysis in Sports, 2006, vol. 2, issue 1, 21

Abstract: The Ironman triathlon was created in 1978 by combining events with the longest distances for races then contested in Hawaii in swimming, cycling, and running. The Half Ironman triathlon was formed using half the distances of each of the events in the Ironman. The Olympic distance triathlon was created by combining events with the longest distances for races sanctioned by the major federations for swimming, cycling, and running. The relative importance of each event in overall race outcome was not given consideration when determining the distances of each of the races in modern triathlons. Thus, there is a general belief among triathletes that the swimming portion of the standard-distance triathlons is underweighted. We present a nonlinear Bayesian model for triathlon finishing times that models time and standard deviation of time as a function of distance. We use this model to create "fair" triathlons by equating the standard deviations of the times taken to complete the swimming, cycling, and running events. Thus, in these "fair" triathlons, a one standard deviation improvement in any event has an equivalent impact on overall race time. We conclude that a ratio of roughly 1:4:17 for swim distance to run distance to bike distance generates appropriate distances for a "fair" triathlon. So, for example, the Olympic triathlon swim distance should be increased from 1.5 km to 2.5 km to more fairly value each discipline in the race.

Keywords: Three-parameter lognormal distribution; flexible tail thickness; growth models (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (1)

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DOI: 10.2202/1559-0410.1023

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