Mathematical Models that Predict Athletic Performance in the Men's Throwing Events at the Olympic Games

Ian Heazlewood, Joseph Walsh

    Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedingspeer-review


    The prediction of future athletic performance is a recurring theme as sports scientists strive to understand the predicted limits of sports performance. Predictive models based on Olympic data for athletics have derived some accurate predictions of performance in the 2000, 2004, 2008 and 2012 Olympic Games. The aim of this research was to develop predictive models using performance data of the first three athletes competing in the finals of the men’s shot put, discus, hammer and javelin at the Summer Olympic Games from Berlin 1936 to London 2012. The approach utilised regression-curve estimation using IBM SPSS Statistics Version 22 statistical software and by evaluating fit to linear, logarithmic, inverse, quadratic, cubic, compound, power, sigmoidal, growth exponential and logistic functions. The mathematical models varied represented very good predictors of past, current future throws performance in the four field events based on R2 (0.850 - 0.972), p-values (<.001) and unstandardized residuals or error. The non-linear function of best fit for events was the cubic function, which indicated a decrease in performance in recent Olympics and predicted this performance decline would occur at the 2016 Olympic Games in Rio de Janeiro. The reasons for the current and predicted declines were more vigilance concerning drugs in sport and therefore dampening the enhanced performance effect of anabolic androgenic hormones, fewer athletes are undertaking the throwing events as a completive sport and changes in the source population providing the sample of potential throws athletes in Australia in terms of motor fitness abilities are getting smaller in terms of motor fitness abilities and thus fewer capable athletes exist to select from within source population. The good predictive models may be due to a longer time frame data set to develop substantive predictive models, a time frame able to detect phylogenetic trends in human athletic performance. The predictions may indicate a slightly modified Olympic motto from citius, altius, fortius to citius, altius and infirmius or “faster, higher and weaker?”
    Original languageEnglish
    Title of host publicationProceedings of the 12th Australasian Conference on Mathematics and Computers in Sport
    EditorsA Bedford, T Heazlewood
    Place of PublicationAustralia
    PublisherMathSport (ANZIAM)
    Number of pages6
    ISBN (Print)978-0-9925475-1-6
    Publication statusPublished - 2014
    EventAustralasian Conference on Mathematics and Computers in Sport 2014 12th - Darwin, Australia
    Duration: 25 Jun 201427 Jun 2014


    ConferenceAustralasian Conference on Mathematics and Computers in Sport 2014 12th


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