To develop a performance predictor model based on swimmers’ biomechanical profile, relate the partial contribution of the main predictors with the training program, and analyze the time effect, sex effect, and time × sex interaction.
91 swimmers (44 boys, 12.04 ± 0.81 y; 47 girls, 11.22 ± 0.98 y) evaluated during a 3-y period. The decimal age and anthropometric, kinematic, and efficiency features were collected 10 different times over 3 seasons (ie, longitudinal research). Hierarchical linear modeling was the procedure used to estimate the performance predictors.
Performance improved between season 1 early and season 3 late for both sexes (boys 26.9% [20.88;32.96], girls 16.1% [10.34;22.54]). Decimal age (estimate [EST] –2.05, P < .001), arm span (EST –0.59, P < .001), stroke length (EST 3.82; P = .002), and propelling efficiency (EST –0.17, P = .001) were entered in the final model.
Over 3 consecutive seasons young swimmers’ performance improved. Performance is a multifactorial phenomenon where anthropometrics, kinematics, and efficiency were the main determinants. The change of these factors over time was coupled with the training plans of this talent identification and development program.
Morais and Lopes are with the Dept of Sport Sciences, Polytechnic Inst of Bragança, Bragança, Portugal. Silva is with the Dept of Sport Sciences, Exercise and Health, University of Trás-os-Montes and Alto Douro, Vila Real, Portugal. Marinho is with the Dept of Sport Sciences, University of Beira Interior, Covilhã, Portugal. Barbosa is with the National Inst of Education, Nanyang Technological University, Singapore. All authors are also with the Research Ctr in Sports Sciences, Health and Human Development (CIDESD), Vila Real, Portugal.