Speed of Thought and Speed of Feet: Examining Perceptual-Cognitive Expertise and Physical Performance in an English Football Academy
Bibliographic record
Abstract
Abstract The world’s greatest professional football players are able to execute effective tactical decisions as well as fulfil various physical demands. However, the degree to which both are associated with greater potential in a football academy is unknown. Therefore, the aim of this study was to investigate decision-making skill and physical performance as contributing factors to coach potential rankings in an English football academy. Ninety-eight outfield academy players (Foundation Development Phase [FDP] under-9 to under-11 n = 40; Youth Development Phase [YDP] under-12 to under-16 n = 58) participated in the study. They engaged in 45 film-based simulations at two occlusion phases (e.g., the visual display is cut-off at a precise time during an action), firstly “during” and secondly “post” execution, to examine decision-making skill. Participants also completed four fitness tests to examine physical performance. A classification of “higher-potentials” (top third) and “lower-potentials” (bottom third) were applied through coach rankings. Independent t-tests compared the decision-making and physical performance tests. Higher-potentials made significantly more accurate decisions within the “post” phase within the FDP (P < 0.05) and the “during” phase within the YDP (P < 0.05). Additionally, higher-potentials were significantly faster for the 0–30 m sprint in both the FDP and YDP (P < 0.05), with higher-potentials within the YDP also significantly faster in the 0–10 m sprint (P < 0.05) and jumped significantly higher in the countermovement jump (P < 0.05). These findings indicated that greater football potential may be associated with superior perceptual-cognitive expertise and quicker sprint ability in both academy age phases, with a greater discriminatory function within the older cohort.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.003 | 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".