The physiological parameters characterizing human capacities (the ability to move, reproduce or perform tasks) evolve with ageing: performance is limited at birth, increases to a maximum and then decreases back to zero at the day of death. Physical and intellectual skills follow such a pattern. Here, we investigate the development of sport and chess performances during the lifetime at two different scales: the individual athletes’ careers and the world record by age class in 25 Olympic sports events and in grandmaster chess players. For all data sets, a biphasic development of growth and decline is described by a simple model that accounts for 91.7% of the variance at the individual level and 98.5% of the variance at the species one. The age of performance peak is computed at 26.1 years old for the events studied (26.0 years old for track and field, 21.0 years old for swimming and 31.4 years old for chess). The two processes (growth and decline) are exponential and start at age zero. Both were previously demonstrated to happen in other human and non-human biological functions that evolve with age. They occur at the individual and species levels with a similar pattern, suggesting a scale invariance property.Electronic supplementary materialThe online version of this article (doi:10.1007/s11357-011-9274-9) contains supplementary material, which is available to authorised users.

Particular attention must be paid to illness prevention strategies during periods of intensive training, particularly in the winter months or in case of the recent medical episode.

WBC use during IT helped mitigate the signs of functional overreaching observed during ITCON, such as reduced sleep quantity, increased fatigue, and impaired exercise capacity. These results support the daily use of WBC by athletes seeking to avoid functional overreaching during key periods of competition preparation.

The aim of this study was to carry out a statistical analysis of the Banister model to verify how useful it is in monitoring the training programmes of elite swimmers. The accuracy, the ill-conditioning and the stability of this model were thus investigated. The training loads of nine elite swimmers, measured over one season, were related to performances with the Banister model. First, to assess accuracy, the 95% bootstrap confidence interval (95% CI) of parameter estimates and modelled performances were calculated. Second, to study ill-conditioning, the correlation matrix of parameter estimates was computed. Finally, to analyse stability, iterative computation was performed with the same data but minus one performance, chosen at random. Performances were related to training loads for all participants (R(2) = 0.79 +/- 0.13, P < 0.05) and the estimation procedure seemed to be stable. Nevertheless, the range of 95% CI values of the most useful parameters for monitoring training was wide: t(a) = 38 (17, 59), t(f) = 19 (6, 32), t(n) = 19 (7, 35), t(g) = 43 (25, 61). Furthermore, some parameters were highly correlated, making their interpretation worthless. We suggest possible ways to deal with these problems and review alternative methods to model the training-performance relationships.