Abstract
Although relative age effects in sports have been studied worldwide, the underlying mechanisms are still under debate. This study adds to the existing knowledge by providing a further exploration of the association between relative age and the performance trajectories over four years in youth players of an individual skill/technique based sport: table tennis. Data of 1000 French male and female youth top 100 players across five ages (U14, U15, U16, U17 and U18) were collected from the ranking lists over a four-year period. A series of latent growth analysis was conducted per subsample and revealed three performance trajectories for male U14, U16 and U17 as well as for female U17 and U18 and four performance trajectories for male U15 and U18 and female U14, U15 and U16. Results of chi-square tests revealed that the players' birth quartiles were significantly associated with the performance trajectories only for male players U18 with a large effect size (p = 0.01; W = .48). All other male subsample only showed a trend for the male subsamples for those born in the fourth quartile. No relations or trends were found in the female subsamples. Future research in relative age effects should further explore individual characteristics and pathways while using a longitudinal approach in a prospective design and evaluate influencing constraints (and solutions) in a more comprehensive way.
Highlights
The relative age effect (RAE) is described as a situation of inhomogeneous distribution of the players’ birth dates within one age category
Within-year effects are described as deviated birth distributions per quartiles or semester and between-year effects as deviated birth distributions per year
An underrepresentation in quartile 4 (Q4) was present within the female U16 and male U14 subsamples, while male U16 showed an underrepresentation in quartile 3 (Q3) and male U18 an overrepresentation of Quartile 1 (Q1)
Summary
The relative age effect (RAE) is described as a situation of inhomogeneous distribution of the players’ birth dates within one age category. This means that the observed birth distribution differs from the expected one. Within-year effects are described as deviated birth distributions per quartiles or semester and between-year effects as deviated birth distributions per year (i.e. per birth cohort within an age-category) In most sports, both effects are displayed as overrepresentations of the relatively older players who are born more early after the cut-off date compared to the relatively young players [2,3,5,6,7,8].
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