| Literature DB >> 33345136 |
Adam L Kelly1, Daniel T Jackson1, Josh J Taylor2, Mark A Jeffreys1,2, Jennifer Turnnidge3.
Abstract
The relative age effect (RAE) is almost pervasive throughout youth sports, whereby relatively older athletes are consistently overrepresented compared to their relatively younger peers. Although researchers regularly cite the need for sports programs to incorporate strategies to moderate the RAE, organizational structures often continue to adopt a one-dimensional (bi)annual-age group approach. In an effort to combat this issue, England Squash implemented a "birthday-banding" strategy in its talent pathway, whereby young athletes move up to their next age group on their birthday, with the aim to remove particular selection time points and fixed chronological bandings. Thus, the purpose of this study was to examine the potential effects of the birthday-banding strategy on birth quarter (BQ) distributions throughout the England Squash talent pathway. Three mixed-gender groups were populated and analyzed: (a) ASPIRE athletes (n = 250), (b) Development and Potential athletes (n = 52), and (c) Senior team and Academy athletes (n = 26). Chi-square analysis and odds ratios were used to test BQ distributions against national norms and between quartiles, respectively. Results reveal no significant difference between BQ distributions within all three groups (P > 0.05). In contrast to most studies examining the RAE within athlete development settings, there appears to be no RAE throughout the England Squash talent pathway. These findings suggest that the birthday-banding strategy may be a useful tool to moderate RAE in youth sports.Entities:
Keywords: RAE; athlete development; bio-banding; expertise; skill acquisition; talent development; talent identification; youth sport
Year: 2020 PMID: 33345136 PMCID: PMC7739587 DOI: 10.3389/fspor.2020.573890
Source DB: PubMed Journal: Front Sports Act Living ISSN: 2624-9367
Figure 1The England Squash talent pathway.
Figure 2The distribution of BQs in athlete's respective cohort and expected distribution from national norms (Office for National Statistics, 2015).
Figure 3The distribution of BQs in male and female combined cohorts and expected distribution of national norms (Office for National Statistics, 2015).
The distributions of BQs with chi-square, Cramer's V, and OR analysis.
| ASPIRE | 57 | 65 | 70 | 58 | 250 | 2.292 | 0.514 | 0.07 | 1.00 |
| Development and potential | 7 | 14 | 15 | 16 | 52 | 3.822 | 0.281 | 0.19 | 0.45 |
| Senior team and academy | 5 | 3 | 11 | 7 | 26 | 5.290 | 0.152 | 0.32 | 0.73 |
| Male combined cohort | 41 | 56 | 54 | 51 | 202 | 3.061 | 0.382 | 0.09 | 0.82 |
| Female combined cohort | 27 | 27 | 42 | 30 | 126 | 4.857 | 0.183 | 0.14 | 0.91 |