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Testing the application of corrective adjustment procedures for removal of relative age effects in female youth swimming.

Shaun AbbottKylie MouldsJames SalterMichael RomannLucy EdwardsStephen Paul Cobley
Published in: Journal of sports sciences (2020)
The purpose of this study was (1) accurately estimate longitudinal relationships between decimal age (i.e., chronological and relative) and performance in Australian female 100 m (N = 765) and 200 m (N = 428) Breaststroke swimmers (10-18 years); and (2) determine whether corrective adjustment procedures could remove Relative Age Effects (RAEs) in an independent sample of age-matched 100 m (N = 2,491) and 200 m (N = 1,698) state/national level Breaststroke swimmers. In Part 1, growth curve modelling quantified longitudinal relationships between decimal age and swimming performance. In Part 2, relative age distributions (Quartile 1-4) for "All", "Top 25%" and "10%" of swimming times were examined based on raw and correctively adjusted swim times for age-groups. Based on raw swim times, finding identified RAE effect sizes increased in magnitude (small-medium) with selection level ("All"-"Top 25%") in 12-14 years age-groups for both events. However, when correctively adjusted swim performances were examined, RAEs were primarily absent across all age-groups and selection levels. Using longitudinal reference data, corrective adjustment procedures removed relative age advantages in female youth Breaststroke performance. Removing the influence of relative age-related differences is predicted to improve the accuracy of identifying genuinely skilled youth swimmers.
Keyphrases
  • physical activity
  • mental health
  • cross sectional
  • machine learning
  • quality improvement
  • artificial intelligence
  • big data