Advancing athlete development: How Percentile Comparison Methods (PCMs) can identify youth developmental profiles.

Maturation Relative age effects Skill evaluation Sport performance Talent identification

Journal

Journal of science and medicine in sport
ISSN: 1878-1861
Titre abrégé: J Sci Med Sport
Pays: Australia
ID NLM: 9812598

Informations de publication

Date de publication:
21 Mar 2024
Historique:
received: 29 01 2024
revised: 07 03 2024
accepted: 18 03 2024
medline: 10 4 2024
pubmed: 10 4 2024
entrez: 9 4 2024
Statut: aheadofprint

Résumé

Inter-individual developmental differences confound the capability to accurately evaluate youth athletic performance, highlighting the need for considerate methodology and analytical approaches. The present study demonstrated how Percentile Comparison Methods (PCMs) were developed, tested, and applied to identify athlete developmental profiles in Australian youth swimming. Cross-sectional. Participants were N = 866 female 100-metre (m) Front-Crawl swimmers, aged 9-15 years, competing at 36 Australian regional-national level long course events. At respective events, swim performance time was collated alongside, age, date of birth, and anthropometric measures to identify age group, relative age, and maturity status. Quadratic relative age and maturity status with 100-m performance regression trendlines were generated. Then, individual swim performances at a given relative age or maturity status were converted into percentile rank distributions and compared with raw (unadjusted) annual age-group performance percentile ranks. At a cohort level, initial testing confirmed relative age and maturity-adjusted percentile rankings were associated with general rank improvements for relatively younger and later maturing swimmers compared to raw ranks (and vice versa). When assessing individual swimmer plots, where three percentile rank scores were compared and rank change threshold criteria applied, five Percentile Comparison Method profile types were identified, namely: 'Early Developing' (19 %); 'Later Developing' (18 %); 'Consistent' (15 %); 'Mixed' (38 %) and 'Counteracting' (10 %). Percentile Comparison Method plots helped identify developmentally (dis-)advantaged swimmers; specific factors leading to (dis-)advantage, and likely onward development trajectories. Overall and with practical considerations, Percentile Comparison Methods can improve the validity of youth athletic performance evaluation as well as inform athlete development programming.

Identifiants

pubmed: 38594115
pii: S1440-2440(24)00081-1
doi: 10.1016/j.jsams.2024.03.004
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier Ltd.

Déclaration de conflit d'intérêts

Declaration of interest statement None.

Auteurs

Shaun Abbott (S)

Discipline of Exercise & Sport Science, Faculty of Health Sciences, The University of Sydney, Australia. Electronic address: https://twitter.com/ShaunAbb0tt.

Clorinda Hogan (C)

Discipline of Exercise & Sport Science, Faculty of Health Sciences, The University of Sydney, Australia.

Giovanni Postiglione (G)

Discipline of Exercise & Sport Science, Faculty of Health Sciences, The University of Sydney, Australia.

Gary Barclay (G)

Swimming Australia Ltd, Australia.

Stephen Cobley (S)

Discipline of Exercise & Sport Science, Faculty of Health Sciences, The University of Sydney, Australia. Electronic address: stephen.cobley@sydney.edu.au.

Classifications MeSH