Sport psychological skills that discriminate between successful and less successful female university field hockey players : sports psychology
Bibliographic record
Abstract
Sport psychology plays an important and ever-increasing role in competitive sport. The objective of this study was to determine the sport psychological skills that discriminate significantly between successful and less successful female university field hockey players in order to emphasize the characteristics that need to be addressed in sport psychological skills training (SPST) sessions. The subjects consisted of 106 female university hockey players, categorized into a successful (players from the A division) and less successful group (players from the B division). The sport psychological skill (SPS) levels measured with the Psychological Skill Inventory (PSI) and the Ottawa Mental Skills Assessment Tool-3 (OMSAT-3) from the two groups were compared and reported. The results indicated that the successful group had better results in 66.7% of the variables that were measured in the study. Practical significance was found in four of the 18 psychological variables that included achievement motivation, goal-directedness, goal-setting and fear control. Furthermore, six variables discriminate significantly between the successful and less successful female hockey players, which included achievement motivation, stress reactions, fear control, self-confidence, mental rehearsal as well as imagery.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".