Longitudinal Changes of Functional Capacities Among Adolescent Female Basketball Players

Abstract

Background: The interpretation of young athletes' performance during pubertal years is important to support coaches' decisions, as performance may be erroneously interpreted due to the misalignment between chronological age (CA), biological age (BA) and sport age (SA). Aim: Using a Bayesian multilevel approach, the variation in longitudinal changes in performance was examined considering the influence of CA, BA (age at menarche), SA, body size, and exposure to training among female basketball players. Method: The study had a mixed-longitudinal design. Thirty eight female basketball players (aged 13.38 ± 1.25 years at baseline) were measured three times per season. CA, BA and SA were obtained. Anthropometric and functional measures: countermovement jump, Line drill (LD), Yo-Yo (Yo-Yo IR1). Based on the sum of the z-scores, an index of overall performance was estimated. The effects of training on longitudinal changes in performance were modeled. Results: A decrease in the rate of improvements was apparent at about 14 years of age. When aligned for BA, the slowing of the rate of improvements is apparent about 2 years after menarche for LD. For countermovement jump longitudinal changes, when performance was aligned for BA improvements became linear. For Yo-Yo IR1 and performance index, both indicators showed a linear trend of improvement when aligned for CA and BA, separately. Older players showed higher rates of improvement for Yo-Yo IR1 and performance index from pre-season to end-season. When considering performance changes aligned for BA it was apparent an improvement of performance as players became biologically mature. Conclusions and Implications: The alignment of CA with BA and SA provides important information for coaches. Human growth follows a genetically determined pattern, despite variation in both tempo and timing. When the effects of maturation reach their end, all the girls went through the same process. Hence, there is no need to artificially manipulate youth competitions in order to accelerate gains that sooner or later reach their peak and tend to flat their improvement curve.

Deliberate Practice, Functional Performance and Psychological Characteristics in Young Basketball Players: A Bayesian Multilevel Analysis

“…A standardized warm-up was taken by all athletes before testing. Details about the functional performance procedures and reliability estimates are available elsewhere [32,43,55].…”

Revisiting the Relative Age Effect From a Multidisciplinary Perspective in Youth Basketball: A Bayesian Analysis

“…To describe players functional capacities we used the vertical jump with countermovement (Bosco et al, 1983 ), a short-term maximal running protocol, the line drill test (Semenick, 1990 ; Carvalho et al, 2017 ) and intermittent endurance test, the yo-yo intermittent recovery level 1 test (yo-yo IR1) (Bangsbo, 1994 ). Details about the functional performance procedures and reliability estimates are available elsewhere (Carvalho et al, 2018 , 2019 ; Soares et al, 2020 ).…”

Modelling the dynamics of change in the technical skills of young basketball players: The INEX study

“…Moreover, repeated sprint ability was positively affected by chronological age, lower body explosive strength and interval endurance capacity. Additionally, Carvalho et al [ 17 ] examined longitudinal changes in functional performance between 12–16 years and reported a non-linear trend in countermovement jump and line drill tests, with the rate of improvement decreasing at approximately 14 years of age. The age of fourteen years typical aligns with the adolescent growth spurt.…”