Training Quiet Eye Improves Accuracy in the Basketball Free Throw
Bibliographic record
Abstract
University basketball players (Team A) received quiet eye (QE) training over two seasons of league play, compared to two control teams (Team B and Team C), who competed at the top of the same league but did not receive similar training. QE was defined as the player’s final fixation on the hoop or backboard prior to the shooting action. In Season 1, Team A improved significantly, Pre to Post, in experimental accuracy, QE duration, and relative shot timing but did not transfer these improvements to league play during the season. At the conclusion of Season 2, Team A improved their free throw shooting accuracy by 22.62% to 76.66%, more than Team A (66.18%) or B (74.05%). The results highlight the importance of training a sustained duration of QE on a single location on the hoop prior to the execution of the shooting action. Theoretical and applied implications of training QE are discussed, and recommendations are made for future research and training.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".