Using cognitive general imagery to improve soccer strategies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Athletes use imagery for both cognitive and motivational functions (Paivio 1985) The cognitive function involves the rehearsal of skills (cognitive specific) and strategies of play (cognitive general). To date most of the imagery research has been concerned with skill rehearsal (cognitive specific), and there have been no controlled studies investigating the effects of cognitive general imagery on the learning and performance of game plans or strategies of play. The purpose of this study was to determine the effectiveness of a cognitive general imagery intervention on three distinct soccer strategies in a young elite female soccer team. Participants were 13 competitive female soccer players with a mean age of 12.54 years. Imagery scores were determined via the Sport Imagery Questionnaire (SIQ; Hall, Mack, Paivio, & Hausenblas, 1998) prior to, during, and after the intervention. A staggered multiple baseline design across behaviors was used to evaluate the effect of imagery on three distinct soccer strategies (defending a direct free kick, taking a direct free kick, and defending a corner kick) which were introduced at weeks 2, 4 and 6. Results indicated that cognitive general and cognitive specific imagery use as well as motivational general‐arousal imagery use significantly increased from baseline to post intervention. Based on the present study's findings, the execution of soccer strategies was not significantly enhanced with the implementation of a cognitive general intervention. Additional research should be conducted in order to reach clearer conclusions that will have implications for young athletes and their learning strategies.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it