Comparing and forecasting performances in different events of athletics using a probabilistic model Brian Godsey School of Medicine, University of Maryland, Baltimore, MD, USA
[email protected] Published in the Journal of Quantitative Analysis in Sports in June 2012 Abstract Though athletics statistics are abundant, it is a difficult task to quantitatively com- pare performances from different events of track, field, and road running in a meaningful way. There are several commonly-used methods, but each has its limitations. Some methods, for example, are valid only for running events, or are unable to compare men’s performances to women’s, while others are based largely on world records and are thus unsuitable for comparing world records to one other. The most versatile and widely-used statistic is a set of scoring tables compiled by the IAAF, which are updated and published every few years. Un- fortunately, these methods are not fully disclosed. In this paper, we propose a straight-forward, objective, model-based algorithm for assigning scores to ath- arXiv:1408.5924v1 [stat.AP] 25 Aug 2014 letic performances for the express purpose of comparing marks between different events. Specifically, the main score we propose is based on the expected number of athletes who perform better than a given mark within a calendar year. Comput- ing this naturally interpretable statistic requires only a list of the top performances in each event and is not overly dependent on a small number of marks, such as the world records. We found that this statistic could predict the quality of fu- ture performances better than the IAAF scoring tables, and is thus better suited for comparing performances from different events.