The Critical Power Model as a Potential Tool for Anti-Doping

Peer reviewed: 
Yes, item is peer reviewed.
Scholarly level: 
Graduate student (PhD)
Final version published as: 

Puchowicz, M. J., Mizelman, E., Yogev, A., Koehle, M. S., Townsend, N. E., & Clarke, D. C. (2018). The Critical Power Model as a Potential Tool for Anti-doping. Frontiers in physiology9, 643. doi:10.3389/fphys.2018.00643

Date created: 
2018-06
Keywords: 
Critical power model
W' balance model
Performance models
Athletic performance
Doping in sports
Performance-enhancing substances
Biomarkers
Critical velocity
Abstract: 

Existing doping detection strategies rely on direct and indirect biochemical measurement methods focused on detecting banned substances, their metabolites, or biomarkers related to their use. However, the goal of doping is to improve performance, and yet evidence from performance data is not considered by these strategies. The emergence of portable sensors for measuring exercise intensities and of player tracking technologies may enable the widespread collection of performance data. How these data should be used for doping detection is an open question. Herein, we review the basis by which performance models could be used for doping detection, followed by critically reviewing the potential of the critical power (CP) model as a prototypical performance model that could be used in this regard. Performance models are mathematical representations of performance data specific to the athlete. Some models feature parameters with physiological interpretations, changes to which may provide clues regarding the specific doping method. The CP model is a simple model of the power-duration curve and features two physiologically interpretable parameters, CP and W0 . We argue that the CP model could be useful for doping detection mainly based on the predictable sensitivities of its parameters to ergogenic aids and other performance-enhancing interventions. However, our argument is counterbalanced by the existence of important limitations and unresolved questions that need to be addressed before the model is used for doping detection. We conclude by providing a simple worked example showing how it could be used and propose recommendations for its implementation.

Language: 
English
Document type: 
Article
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