Birth month distribution and anthropometric measures of U-15 national elite soccer players
Bibliographic record
Abstract
The aim of this study was to analyze the birth month distribution and anthropometric measurements of U-15 elite soccer players. The sample consisted of 400 athletes (15.4 ± 0.4 years, 171.0 ± 10.6 cm and 63.0 ± 8.8 kg) participants of the 11th edition of the Brazil U-15 Soccer Cup, who had their birth month information and height and body mass measures obtained from data available on the organization’s website. Athletes were separated according to the categorization of chronological age into four-month periods: 1st quarter (1st QDT), athletes born between January and April; 2nd quarter (2nd QDT), those born between May and August, and 3rd quarter (3rd QDT), those born between September and December. The non-parametric chi-square test (X2) was used to analyze the possible differences between observed and expected birth date distributions in the four-month periods. The significance level was P<0.05. The results show that the number of players born in 1st QDT was higher when compared to 2nd QDT and 3rd QDT (P<0.05), and higher when compared to 2nd QDT with 3rd QDT (P<0.05). For variables height and body mass, it was observed that players born in 1st QDT presented values significantly higher than those born in 2nd QDT and 3rd QDT (P<0.05). In the same way, players born in 2nd QDT presented higher values than those born in 3rd QDT (P<0.05).It could be concluded that the relative age effect exerts an influence on the selection of Brazilian U-15 soccer players because it is associated with differences in the anthropometric characteristics of these young players.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".