Performance Profiling As An Intelligence-Led Approach To Anti-Doping In Sports
The current prevalence of doping in elite sport is unknown. Existing data from the World Anti-Doping Agency (WADA) suggests that the number of adverse analytical findings (AAF) was 1.43% in 2017 (4,596 AAFs from 322,050 samples1). Moreover, data from the recently formed Athletic Integrity Unit (AIU) place the number of antidoping rule violations (ADRV) at 65 ADRVs from 8,489 samples (<1%)2. However, these figures appear at odds to research studies using anonymous athlete selfreports that put the estimate much higher at between 14.0% and 57.1%,3 with between 3.1% and 26.0% of dopers reporting a lifetime prevalence.4
Therefore, there is clear discrepancy between the number of anti-doping rule violations (ADRV) and the estimated prevalence of doping. This is despite increases in both the financial resources being allocated to the fight against doping in sports, and number of samples analysed (7.1% increase in the overall number of samples analysed: 300,565 in 2016 to 322,050 in 20175).
Consequently, questions can be raised about the efficiency of current anti-doping policy and testing strategies, and whether other types of data are required. In turn, this targeted approach to anti-doping would enhance the ability of anti-doping authorities to make more informed decisions on assigning athletes to registered testing pools, and target-testing individuals, and ultimately allow a more efficient distribution of anti-doping testing resources.
One key piece of information available to anti-doping authorities is the performance of the athlete, which is currently seldom used in deciding testing strategy. As the primary reason for doping is improvement of athletic performance, it is reasonable to suggest that monitoring an individual's competition results on a longitudinal basis may reveal suspicious performance improvements. …
The aim of this case report is to demonstrate the potential for mathematical modelling of individual career trajectories (i.e. the relationship between age and performance) to identify characteristics of performance evolution, which are able to distinguish athletes who have previously been convicted of doping, from others who are presumed clean.
In this work, we acknowledge that monitoring athlete performance and identifying changes obviously does not prove doping, however extreme changes that are in excess of what is predicted based upon the population changes, may be sufficient to raise the level of suspicion of an athlete. …
Hopker J, Griffin J, Brookhouse J, Peters J, Schumacher YO, Iljukov S. Performance profiling as an intelligence-led approach to anti-doping in sports. Drug testing and analysis 2019. Error - Cookies Turned Off