Abstract
The influence of biological maturity status (BMS) on talent identification and development within elite youth soccer is critically debated. During adolescence, maturity-related performance differences within the same age group may cause greater chances of being selected for early maturing players. Therefore, coaches need to consider players' BMS. While standard methods for assessing BMS in adolescents are expensive and time-consuming imaging techniques (i.e., X-ray and MRI), there also exist more pragmatic procedures. This study aimed to evaluate commonly used methods to assess BMS within a highly selected sample of youth soccer players. A total of N = 63 elite male soccer players (U12 and U14) within the German Soccer Association's talent promotion program completed a test battery assessing BMS outcomes. Utilizing MRI diagnostics, players' skeletal age (SAMRI) was determined by radiologists and served as the reference method. Further commonly used methods included skeletal age measured by an ultrasound device (SAUS), the maturity offset (MOMIR), and the percentage of adult height (PAHKR). The relation of these alternative BMS outcomes to SAMRI was examined using different perspectives: performing bivariate correlation analyses (1), modeling BMS as a latent variable (BMSlat) based on the multiple alternative diagnostics (2), and investigating individual differences in agreement (3). (1) Correlations of SAMRI and the further BMS variables ranked from r = 0.80 to r = 0.84 for the total sample and were lower for U12 (0.56 ≤ r ≤ 0.66), and U14 (0.61 ≤ r ≤ 0.74) (2). The latent structural equation modeling (SEM) (R2 = 51%) revealed a significant influence on BMSlat for MOMIR (β = 0.51, p <0.05). The additional contribution of PAHKR (β = 0.27, p = 0.06) and SAUS (β = −0.03, p = 0.90) was rather small (3). The investigation of individual differences between the reference method and alternative diagnostics indicated a significant bias for MOMIR (p <0.01). The results support the use of economical and time-efficient methods for assessing BMS within elite youth soccer. Bivariate correlation analyses as well as the multivariate latent variable approach highlight the measures' usefulness. However, the observed individual level differences for some of the utilized procedures led to the recommendation for practitioners to use at least two alternative assessment methods in order to receive more reliable information about players' BMS within the talent promotion process.
Highlights
In the context of competitive sports, major sports organizations invest considerable financial resources and work in the promotion and development of youth players (Johnston et al, 2018), meaning a huge commitment for the organizations as well as for the players
The aim of the present study is to evaluate pragmatic diagnostics for assessing biological maturity in a representative sample of elite youth soccer players by comparing their applicability for the assessment of skeletal age, which is currently considered the gold standard method (Lloyd et al, 2014)
With respect to the total sample, correlation coefficients of skeletal age according to MRI (SAMRI) and the further biological maturity status (BMS) variables are ranked from r = 0.80 (SAMRI, skeletal age according to ultrasound (SAUS)) to r = 0.84 (SAMRI, MO from their PHV (MOMIR))
Summary
In the context of competitive sports, major sports organizations invest considerable financial resources and work in the promotion and development of youth players (Johnston et al, 2018), meaning a huge commitment for the organizations as well as for the players. Players born early in a given year (i.e., first birth quarter) generally have a physiological advantage in their development in contrast to their younger counterparts (i.e., those born in the fourth quarter) This leads to the well-known relative age effect (RAE), which occurs especially in soccer talent identification (Deprez et al, 2013). In the pubertal stages (i.e., 11–16 years; Deprez et al, 2015), in which rigorous and important selection processes take place, the difference in players’ BMS can reach up to 5 years (Malina et al, 2004) This leads to the phenomenon where coaches and talent scouts often prefer early maturing players due to a currently better performance level based on more developed physical attributes (Unnithan et al, 2012). Sports scientific research on talent has long shown that a player’s individual BMS should be taken into account within talent promotion, in selection processes (Romann and Javet, 2018)
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