Coaching Shared Mental Models in Soccer: A Longitudinal Case Study
Bibliographic record
Abstract
This study was aimed at capturing the components comprising shared mental models (SMM) and the training methods used to address SMM in one athletic program context. To meet this aim, two soccer coaches from the same collegiate program were interviewed and observed extensively during practices and games throughout the 2009–2010 season. In addition, documents (e.g., players’ positioning on free kicks sheet) from the soccer program were reviewed. The data were analyzed inductively through a thematic analysis to develop models that operationalize SMM through its components, and training. Game intelligence and game philosophy were the two main operational themes defining SMM. Moreover, four themes emerged for SMM training: (a) the setting, (b) compensatory communication, (c) reinforcement, and (d) instruction. SMM was embedded within a more comprehensive conceptual framework of team chemistry, including emotional, social, and cognitive dimensions. Implications of these conceptual frameworks are considered for sport psychologists and coaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 teacher head, 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".