The key role of context in team sports training: The value of played-form activities in practice designs for soccer
Bibliographic record
Abstract
Played-form activities in soccer are customized variants of the original game, configured to emphasize important informational and task constraints in the way players perform in practice. Parameters of play such as the shape and dimensions of the playing area, number of participants involved, and conditions of play are key properties that activities are designed from. These properties impact on the specific practice contexts in which players are challenged to perceive information, make decisions and perform actions, during competitive performance preparation and player development. There are countless possible configurations of played-form activities that can provide development or training opportunities for players to improve performance. Although there are no standard guidelines for designing such practice tasks, here we propose how a theoretical rationale like ecological dynamics can frame the configuration of activities, modelled on typical formats, specific task constraints and key developmental needs. In this article, these formats are depicted with reference to common coaching licence curriculum needs and scientific literature. This insight paper presents a continuum of played-form activities, exemplifying characteristics of different practice designs in soccer. This integration of knowledge provides a valid continuum of play practice designs, based on an extent of specific opportunities for actions in different phases of play. Our insights suggest how coaches and trainers in team sports could gain a deep understanding of how specific played-form activity configurations impact on skill adaptation in players, providing opportunities for coaches to function as learning facilitators.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".