Mathematical models are used to describe and predict the effects of training on performance. The initial models are structured by impulse-type transfer functions, however, cellular adaptations induced by exercise may exhibit exponential kinetics for their growth and subsequent dissipation. Accumulation of exercise bouts counteracts dissipation and progressively induces structural and functional changes leading to performance improvement. This study examined the suitability of a model with exponential terms (Exp-Model) in elite short-track speed (ST) skaters. Training loads and performance evolution from fifteen athletes (10 males, 5 females) were previously collected over a 3-month training period. Here, we computed the relationship between training loads and performance with Exp-Model and compared with previous results obtained with a variable dose-response model (Imp-Model). Exp-Model showed a higher correlation between actual and modelled performances (R2 = 0.83 ± 0.08 and 0.76 ± 0.07 for Exp-Model and Imp-Model, respectively). Concerning model parameters, a higher (time constant for growth) value was found (p = 0.0047; d = 1.4; 95% CI [0.4;1.9]) in males compared to females with Exp-model, suggesting that females have a faster adaptative response to training loads. Thus, according to this study, Exp-model may better describe training adaptations in elite ST athletes than Imp-Model.
Keywords: Mathematical modelling; adaptation to training; olympic athletes; recovery; training load.