Previous experience, aerobic capacity and body composition are the best predictors for Olympic distance triathlon performance: Predictors in amateur triathlon - Puccinelli, P. J.; Lima, G. H.; Pesquero, J. B.; de Lira, C. A.; Vancini, R. L.; Nikolaids, P. T.; Knechtle, B.; Andrade, M. S. (Physiology & Behavior, 2020)
Objective: Present study examines predictors of the overall race time and disciplines in the Olympic distance triathlon. Methods: Thirty-nine male and six female triathletes were evaluated for anthropometric, physiological, genetic, training, clinical and circadian characteristics. Body composition, maximum capacity for oxygen uptake (VO2max), maximum aerobic velocity (MAV), anaerobic threshold (AT), triathlon experience (TE) and XX genotype for a-actinin 3 affected total race time (p<0.05). Results: Total race time can be predicted by MAV (ß = -0.430, t = -3.225, p = 0.003), TE (ß = -0.378, t = -3.605, p = 0.001), and percentage of lean mass (%LM) (ß = -0.332, t = -2.503, p = 0.017). Swimming can be predicted by MAV (ß = -0.403, t = -3.239, p = 0.002), TE (ß = -0.339, t = -2.876, p = 0.007), and AT%VO2max (ß = 0.281, t = 2.278, p = 0.028). Cycling can be predicted by MAV (ß = -0.341, t = -2.333, p = 0.025), TE (ß = -0.363, t = -3.172, p = 0.003), and %LM (ß = -0.326, t = -2.265, p = 0.029). In running split, MAV (ß = -0.768, t = -6.222, p < 0.001) was the only parameter present in the best multiple linear regression model. Conclusion: The most important variables in multiple regression models for estimating performance were MAV, TE, AT and %LM.