Describing the tactical knowledge used by young competitive soccer players: A psychophenomenological analysis
Bibliographic record
Abstract
Purpose Decision-making is the process through which players choose the most appropriate action to perform in the play. Previous investigations did not clearly portray the specific decisional background of learning players considering the progressing state of their capabilities and game knowledge. The study aimed to describe significant information picked up in situ and how young soccer players applied it to make decisions in the play. Methods Three male soccer players aged 14 years were interviewed after 2 official district championship games in Portugal. Their games were filmed; the video sequences showing offensive actions were extracted and edited for visualization. Before questioning, each sequence was visualized for recalling the game actions. The explicitation interview technique was used to help the athletes describe in detail their recalled actions. In line with the recommendation in similar studies, a content analysis of the interviews was conducted to identify the decisional background and the links between elements of information picked up in situ and the decision itself. Results The players did not perform a detailed judgement for every decision and were influenced by direct constraints such as opponent pressure. In contrast, they occasionally assessed risks and opportunities emerging in the game depending on their colleagues’ actions and the pitch zone. At times, they relied on their imagination of what their teammates would do with the action outcome. Conclusions Key elements of the decisional background are common among learning players and can be used as a reference for further investigation or practical intervention in game teaching.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".