The Relative Age Effect on Youth Sports Injuries

Exploring the structure of relative age effects research using citation network analysis

Since the 1980s, research on relative age effects (RAEs) consistently shows that relatively older individuals are advantaged in sport and other contexts. With the recent proliferation of studies on RAEs, periodic knowledge synthesis becomes imperative. Our purpose was to conduct a cross-disciplinary citation network analysis of RAEs literature to enhance our knowledge of RAEs citation structures and the interconnectivity of RAEs studies. We analysed 484 RAEs articles found in Web of Science that were published before 2022. Descriptive results revealed a 12.6% annual growth rate for total RAEs articles published since 1980. The articles appeared in 151 journals, had 1,180 unique authors, and averaged 23.9 citations received. Three theoretical/review papers had the most substantial influence on the field. For the conceptual structure of the field, it was apparent that RAEs research focused mainly on sport performance, maturity, and competition. Regarding intellectual structure, three distinct clusters of articles were cited together, and 13 authorship clusters were detected with few between-cluster connections. The results describe a field with productivity but little interconnectivity among authors and papers. We offer insights into this trend and the role that influential authors/articles have in the field.

The Relative Age Effect at Different Age Periods in Soccer: A Meta-Analysis

In the selection of young athletes, earlier-born adolescents often leverage their temporary biological advantage over their later-born peers from the same cohort, giving rise to the phenomenon known as the Relative Age Effect (RAE). In this study, we delved into the complexities of the RAE in soccer by reviewing 563 independent research samples across 90 articles. Our analysis showed that age period and performance level are pivotal factors influencing the magnitude of the RAE. The adolescent age period emerged as a significant RAE determinant, showcasing the highest effect size magnitudes in our findings. Among athletes of different performance levels, adult European soccer players have been extensively studied, and they have exhibited the most pronounced RAE magnitudes. Intriguingly, our findings reveal another compelling trend: the frequency of players born early versus late in the eligible birth year escalated as player performance levels increased, particularly during adolescence. Coaches and players appear to capitalize unconsciously on this maturational advantage, though this strategy wanes post-adolescence. While there are currently no penalties for this team selection practice, our findings stress the need for coaches to comprehend the ramifications of selecting athletes with an age bias We offer insights into RAE complexities, highlight the synergy of age and performance in these transitory advantages, and advance arguments for more fairly selecting and developing youth athletes.

The relative age effect in the Gaelic Athletic Association (GAA): A mixed methods approach

In the Gaelic Athletic Association (GAA), Talent Academies (TAs) and senior teams cater for high performing players, however only two previous studies have quantified the relative age effect (RAE; i.e., a selection bias favouring those born near the beginning of the cut-off date) in these cohorts. Additionally, no studies to date have explored stakeholder understanding of the RAE using qualitative methods. This study aimed to: (a) quantify the RAE in TAs and senior teams, and (b) investigate stakeholder perspectives of the talent development environment, providing practical insight into the RAE. A mixed methods sequential explanatory study design was employed. Phase one involved a retrospective analysis of longitudinal data for the frequency and distribution of births using TA (n=12,445) and senior (n=8,752) players. Phase two comprised two focus groups of key stakeholders [coaches (n=4) and Talent Development Leaders (n=4)] at TA and senior level. Analysis revealed a significant difference between TA birth quarter (BQ) distributions compared with expected distributions across all age groups (P<0.001; BQ1=30.4% vs. BQ4=17.6%), while at senior level, there were no significant differences between observed and expected BQ distributions (χ² (df=3) =3.812, P=0.282). In phase two, inductive analysis revealed three higher order themes: (a) understanding of the RAE, (b) selection criteria, and (c) player characteristics. The GAA are encouraged to reflect on the practice of chronological age band grouping, investigate possible solutions to limit the effects of the RAE, and offer support programmes to educate key stakeholders on the potential impact of the RAE on talent development.

Risk of acute and overuse injuries in youth elite soccer players: Body size and growth matter

OBJECTIVES

This study investigated anthropometric measures and growth as risk factors for overuse and acute injuries in younger (U10-U12) and older (U13-U15) elite level soccer players.

DESIGN

Prospective cohort study.

METHODS

Height, weight, and sitting height were measured at the start and the end of the 2016-2017 competitive season and growth velocities were calculated. Throughout the season, injuries were registered continuously by the (para-)medical staff of the included clubs. We analyzed the injury risk using multilevel Poisson regression models, accounting for club and team clustering.

RESULTS

Of the included 314 players (11.7±1.7 years of age), 160 players sustained 133 overuse and 163 acute injuries (i.e. 106 injuries in 69 players of the younger group, 190 in 91 players of the older group). In the younger group, risk of overuse injuries was associated with an increase in leg length over the season (incidence rate ratio (IRR) 1.620 [95% CI 1.230-2.117]) and risk of acute injuries with relatively younger age (IRR 1.003 [95% CI 1.000-1.006]). In the older group, a higher leg length was associated with an increased risk of overuse injuries (IRR 1.055 [95% CI 1.011-1.108]), and a higher weight and a lower growth rate with an increased risk of acute injuries (IRR 1.043 [95% CI 1.021-1.067] and 0.903 [95% CI 0.831-0.981], respectively).

CONCLUSIONS

Injury risk factors differ by age group and type of injury. The age-specific anthropometric and growth-related risk factors should be monitored and these risk profiles should be considered to manage injury risk effectively.