Longitudinal performance trajectories for youth female and male soccer players: 10m-sprint percentile curves adapted to biological age - Hernandez, J.; Widmer, C.; Cobley, S.; Born, D.-P.; Taube, W.; Romann, M. (Current Issues in Sport Science, 2025)
Introduction Longitudinal performance monitoring is essential in sport science for accurate talent identification and forecasting future performance. The present study applied linear mixed-effects models (LMM) to analyze the longitudinal performance development of youth soccer players, both female and male. In addition to percentile curves based on chronological age, a novel approach incorporating biological age, which accounts for maturation variability during puberty, is introduced. The incorporation of biological age, as compared to chronological age, is intended to enable a more equitable assessment of physical potential and to reduce selection bias. The goal was to create an evidence-based tool for coaches and researchers to establish realistic benchmarks, model predictions, a support athlete development.