Abstract des Autors

The use of information technology within sport has significantly increased over recent years. These data and information have the potential to make a significant impact on sporting performance, and the nature of its related sciences too. For example, the retrospective analysis of sporting performance data affords the possibility to identify the impact of various technological advances and rule changes on world record performances in sports such as, javelin throwing (+95% over 76 years), pole vault (+86% in 94 years), and 1-h track cycling (+221% in 111 years; Haake, 2009). Similarly, such types of longitudinal data analysis may also be useful from an anti-doping perspective. In this regard, it has previously been shown that yearly world best performances increase with the emergence of new potent doping agents, such as anabolic steroids or EPO (Schumacher and Pottgiesser, 2009). Conversely, when new anti-doping tests are implemented, overall world best performances decrease as the effects of certain performance enhancing drugs become detectable, and are therefore avoided by athletes (Schumacher and Pottgiesser, 2009). These findings raise the possibility that performance monitoring can be useful for anti-doping efforts.
As the aim of any doping regime is to improve sporting performance, it has been suggested performance data, in the form of an Athlete Performance Module (APM), may be useful in strengthening the sensitivity and applicability of the current Athlete Biological Passport (ABP) in the fight against doping in sports (Schumacher and Pottgiesser, 2009). However, there is a general view that performance biometrics alone are not sufficient evidence to establish doping, and as such, cannot demonstrate the use of a prohibited substance in accordance with the World Anti-Doping Code (Article 2.2). Even though sudden increases in performance can be caused by reasons other than doping (e.g., improved training or nutritional strategies), such observations may nevertheless provide worthwhile information in order to trigger targeted anti-doping tests of specific athletes (Iljukov et al., 2018). In addition, whilst not sufficient to convict an athlete for doping, an atypical individual performance profile may also be useful as corroborative evidence in, for example, an ABP case. However, to date, the use of performance data for anti-doping purposes by National Anti-Doping Organizations (NADOs) and International Federations (IFs) remains low.