Relative age, maturation, anthropometry and physical performance characteristics of players within an Elite Youth Football Academy. Issue 6 (December 2019)

• Record Type: Journal Article
• Authors: Patel, Rickesh; Nevill, Alan; Cloak, Ross; Smith, Tina; Wyon, Matthew
• Is Part Of: International journal of sports science & coaching. Volume 14:Issue 6(2019)
• Page Start: 714
• Page End: 725
• Publication Date: 2019-12
• Subjects: Association football -- peak height velocity -- soccer -- talent identification; Coaching (Athletics) -- Periodicals; Sports sciences -- Periodicals; Coaching (Athletics); Sports sciences; Periodicals; 796.077
• DOI: 10.1177/1747954119879348
• Languages: English
• ISSNs: 1747-9541

Abstract

A professional English football club with Category 1 academy status was investigated to determine the magnitude of relative age effects (RAE) within the club and explore between-quartile differences for somatic maturity, anthropometry and physical performances. Birth dates of 426 players from Under 9 to First Team were categorised into four birth quartiles (Q) and examined for relative age effects. Additionally, data on 382 players (Under 11 to First Team) were obtained for somatic maturity, anthropometry, countermovement jump, sprint (10 and 30 m), agility T-test and Yo-Yo Intermittent Recovery Level 1 or 2 performance to determine between-quartile differences. Odds ratios revealed Q1 players were 6.0 times more likely to be represented than Q4 players. Multilevel modelling demonstrated between birth quartile similarities for each variable across all age groups, though there was a tendency for Q4 players to outperform Q1 players between Under 11 and Under 18 groups. Strong relative age effects exist within this club as well as a tendency to select players demonstrating advanced growth and/or maturity, with some indication that higher categorised academies in England may be at risk of amplified selection biases. Talent identification strategies in elite youth football should actively seek to adopt novel approaches to reduce selection biases and avoid wasted potential.