According to the IAAF scoring tables, Usain Bolt’s 100m world record of 9.58 sec is worth 1374 points, whereas Kenenisa Bekele’s 10,000m world record of 26:17.59 yields only 1295 points. This demonstrates the immanent weakness and unfairness of the current scoring methodology. This paper studies the relationship between running distance and running speed, and proposes an alternative scoring method. First it presents the personal predictor model (PPM). This model uses two personal bests of an athlete for calibration, and then it allows predicting an athlete’s hypothetical personal bests for any other distance. The accuracy is well below 1% and it thereby greatly outperforms existing models. Second, it presents the normalised multi-event scoring model (NMSM). This model overcomes the manifest flaws of the current IAAF scoring tables; it demonstrates greater fairness, consistency and transparency. The impact of the new model is explained using empirical data. It substantiates the need for replacing the existing IAAF scoring tables. Finally, the two explained models (PPM and NMSM) are combined for composing personalised scoring tables. These tables convert an athlete’s performances for any distance into a single score, which allows for a ranking of the athlete’s performances across various distances.
|Number of pages||13|
|Journal||New Studies in Athletics|
|Publication status||Published - 2011|
- personal best