Geographical Variations in the Interaction of Relative Age Effects in Youth and Adult Elite Soccer
Bibliographic record
Abstract
Selection biases based on the use of cut-off dates and the timing of athletes' birthdates have been termed relative age effects. These effects have been shown to differentially affect individuals involved in sport. For example, young male soccer players born early in their age group are overrepresented in elite teams while studies in adult soccer indicated potential carry-over effects from talent development systems. This two-study approach focuses on the processes within multi-year age groups in youth and adult elite soccer and on the role of players' age position within the age band with regard to players' birth year and birth month. Study 1 tests for an interaction of two different types of relative age effects among data from participants in the last five Under-17 FIFA World Cups (2007-2015). Analyses revealed a significant global within-year effect and varying birthdate distributions were found between confederations. Even stronger effects were found for constituent year effects. For the total sample, a multi-way frequency analysis (MFA) revealed an interaction with a pattern of a stronger within-year effect for the younger year group. This study highlights the need to consider interactions between different types of age effects. The main aim of Study 2 was to test for carry-over effects from previously found constituent year effects among players participating in the 2014 soccer World Cup and, therefore, to test for long-term effects of age grouping structures used during earlier stages of talent development. A secondary purpose of this study was to replicate findings on the existence of within-year effects and to test whether effects vary between continental confederations. No significant interaction between constituent year and within-year effects was shown by the MFA among the World Cup sample and previous findings on varying within-year effects were replicated. Results indicate that long-term effects of age grouping structures in earlier high-level talent development structures exist.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".