Prediction of elite athletes’ performance by analysis of peak‐performance age and age‐related performance progression

Abstract

AbstractThe 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 to 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.