Abstract
The prediction of future athletic performance is a recurring theme in sports science. Predictive mathematical models can provide new standards which athletes can aspire, assist with talent identification, develop realistic qualifying standards for international competitions and serve to motivate athletes to achieve new objectively set goals. The aim of this research was to develop predictive models based on past Olympic performances for swimming and athletics based on regression curve estimation. Data was averaging the top six performances in the finals of each swimming and athletic event. Nonlinear equations based on data up to 1996 accurately predicted 2000, 2004 and 2008 Olympic performances. The best fit mathematical functions for men and women freestyle swim were 50m (inverse), 100m (men-compound, women-cubic), 200m (sigmoidal), 400m (cubic), 800m (women-sigmoidal) and 1500m (men-cubic) and R2 from .543-.997 (p<.01). The best fits for men and women athletic events were I00m (men-inverse, women-cubic), 400m (sigmoidal), long jump (men-cubic, women-inverse) and high jump (compound and logistic) and R2 from .659-.947 (p<.05). Predicted values for these preceding events at the 2012 Olympics for most swimming events are logical and attainable, whereas performances in the athletic events of women's 400m and men's high jump appear to be overestimated.
Original language | English |
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Title of host publication | Proceedings of the 3rd International Conference on Mathematics in Sport |
Editors | D Percy, J Reade, P Scarf |
Place of Publication | England |
Publisher | Institute of Mathematics and Its Applications |
Pages | 71-77 |
Number of pages | 7 |
Publication status | Published - 2011 |
Event | International Conference on Mathematics in Sport (2011 3rd) - England, United Kingdom Duration: 22 Jun 2011 → 24 Jun 2011 Conference number: 2011 (3rd) |
Conference
Conference | International Conference on Mathematics in Sport (2011 3rd) |
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Country/Territory | United Kingdom |
Period | 22/06/11 → 24/06/11 |