Prediction of elite athletes' performance by analysis of peak-performance age and age-related performance progression - Gorzi, A.; Khantan, M.; Khademnoe, O.; Eston, R. (European Journal of Sport Science, 2022)
The aim of this study was to analyse age-related performance progression and peak-performance age (PPA) in elite track and field athletes and to use a model to predict peak performance. Best performances of world-class athletes from ages 14-15 y up to and including the last Olympic year (n=798), all-time top lists (n= 444), and world record-holders (n=43) were considered in all 22 disciplines for men and 21 disciplines for women. A discipline/sex-specified model was used by applying dynamic panel data methods to analyze the performance trends. Profile analysis showed that PPA of all-time top list throwers was higher than middle-distance runners (P<0.001), distance runners (P<0.05), and jumpers (P<0.05) in men and higher (P<0.05) than middle-distance runners in women. Olympic year top list athletes showed that PPA of women throwers was higher than sprinters (P<0.001) and middle-distance runners (P<0.05), and PPA of women distance runners was higher (P<0.05) than sprinters. In both all-time (P<0.05) and Olympic year (P<0.05) top lists, the PPA of men race walkers was higher than middle-distance runners. Performance over the preceding 1-2 years (in all disciplines), height (in Long Jump Men; Long Jump Women; Triple Jump Men) and weight (in Discus Throwing Men) indices, respectively, are important (P<0.05) for predicting future records with different coefficients in different disciplines. The models provide a useful tool for coaches to predict peak performance records and PPA of their athletes which may be of benefit with goal-setting and evaluation of performance progression at different ages in track and field athletics.