Modeling World Record Predictions in Track Events
Journal Title: IOSR Journal of Sports and Physical Education (IOSR-JSPE) - Year 2018, Vol 5, Issue 6
Abstract
We consider here the estimation of best possible running track events. A logistic type curve is applied with a least squares estimator and applying the gradient descent method. The facts seem to indicate a non-uniqueness of the best estimator and a rather slow convergence. The initial data must be reasonably accurate to obtain convergence, and convergence can require thousands of iterations. Since these are not production codes lengthy iterations are not significant, but there can be multiple convergence values depending on initial values. The implication is that unlike other literature which offers up best times, we demonstrate there can be substantial variance is best estimates. Predicting world records involves combining human mechanics, training, psychology, diet, and coaching. Our focus, mathematical models, groups these as four parameter models.
Authors and Affiliations
G. Donald Allen
Keywords
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- EP ID EP430896
- DOI 10.9790/6737-05060622.
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