AUTHOR=Helsen Werner F. , Thomis Martine , Starkes Janet L. , Vrijens Sander , Ooms Gerrit , MacMaster Calum , Towlson Chris TITLE=Leveling the Playing Field: A New Proposed Method to Address Relative Age- and Maturity-Related Bias in Soccer JOURNAL=Frontiers in Sports and Active Living VOLUME=3 YEAR=2021 URL=https://www.frontiersin.org/journals/sports-and-active-living/articles/10.3389/fspor.2021.635379 DOI=10.3389/fspor.2021.635379 ISSN=2624-9367 ABSTRACT=

Despite various solutions proposed to solve the relative age effect (RAE), it is still a major problem confounding talent identification and selection processes. In the first phase, we sampled 302 under 7–21 academy soccer players from two Belgian professional soccer clubs to explore the potential of a new approach to solve the inequalities resulting from relative age- and maturity-related bias. This approach allocates players into four discrete quartile groups based on the midway point of their chronological and estimated developmental (ED) birth dates (calculated using the growth curves for stature of Belgian youth). With the use of chi square analyses, a RAE was found (p < 0.01) for the overall sample (Q1 = 41.4% vs. Q4 = 14.9%) that completely disappeared after reallocation (Q1 = 26.5%; Q2 = 21.9%; Q3 = 27.5%; Q4 = 24.2%). According to the new allocation method, the stature difference was reduced, on average, by 11.6 cm (from 24.0 ± 9.9 to 12.4 ± 3.4 cm, d = 1.57). Body mass difference between the two methods was 1.9 kg (20.1 ± 11.3–18.2 ± 13.1 kg, respectively, d = 0.15). The new method created a maximum chronological age difference of 1.9 vs. 0.8 years for the current method. With the use of this method, 47% of the players would be reallocated. Twenty-three percent would be moved up one age category, and 21% would be moved down. In the second phase, we also examined 80 UK academy soccer players to explore if reallocating players reduces the within-playing group variation of somatic and physical fitness characteristics. The percentage coefficient of variation (%CV) was reduced (0.2–10.1%) in 15 out of 20 metrics across U11–U16 age categories, with the U13 age category demonstrating the largest reductions (0.9–10.1%) in CV. The U12 and U13 age categories and associated reallocation groupings showed trivial to small (ES = 0.0–0.5) between-method differences and trivial to moderate (ES = 0.0–1.1) differences within the U14–U16 age categories. A reduction in RAE may lead to fewer dropouts and thus a larger player pool, which benefits, in turn, talent identification, selection, and development.