Tail modeling, track and field records, and Bolt's effect - Noubary, R. (Journal of Quantitative Analysis in Sports, 2010)
In recent years predictions of athletic records have acquired a special significance in the scientific community. This article presents a method for calculation of probabilities of future records through modeling the tail of the distribution for performance measures. It utilizes an estimation method based on ideas from classical extreme-value theory that avoids difficulties associated with the maximum likelihood estimation. To improve the predictions, whenever possible, it utilizes information such as the survival time of the latest record and the time interval between the last two records. The article also presents alternative prediction methods based on order statistics and the theory of records, and includes a method for prediction of ultimate records. Application of tail modeling to men's long jump produces reasonable results. For long jump the last two records 8.95 meters and 8.90 meters are significantly greater than the third best record, 8.35 meters, which indicates a medium or long tail model. Data for 100 and 200 meter runs exhibit a similar characteristic as the present records for these events, 9.58 seconds and 19.19 seconds respectively, are significantly lower than the previous records. Application to the men's 100 meter data for the period starting January 1, 1977, when IAAF required fully automatic timing, to September 1, 2009 shows that the probabilities of setting a new record such as 9.55 seconds or less or 9.5 seconds or less are respectively: