Executive functions, deliberate practice, and biological maturation are associated with soccer success
Bibliographic record
Abstract
The aim of this study was to analyze which variables were most important for the teams’ final rank. Executive function, deliberate practice, and biological maturation between a higher-ranked and a lower-ranked team in the championship were considered. The 51 players were divided into the top and bottom team. The players underwent stop-signal, design fluency, and verbal fluency tests. Deliberate practice was asked by questionnaire, and biological maturation was based on maturity offset. The statistical analyses were performed with discriminant analysis and a comparison between teams. The results showed a discriminatory power in biological maturation, deliberate practice, and design fluency test. The Stop-Signal results show statistically significant differences in favor of the top team (SSRT: p=0.006 / d=0.84 and MRT: p=0.016 / d=0.74). Moreover, players in the top team had more deliberate practice time (p<0.000 / d=1.41), as well more advanced maturation (p<0.000 / d=1.62) than the players in the bottom team. Therefore, executive function, deliberate practice, and biological maturation seems to be essential for collective soccer success and should be stimulated in training sessions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".