Visual Information in Basketball Jump-Shots: Differences between Youth and Adult Athletes
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Bibliographic record
Abstract
Basketball shooting is a complex skill that requires visual routines and trained players typically evidence a specific oculomotor pattern. This study aimed to examine visual patterns in male novice youth and professional adult players while performing a jump shot. The sample included 20 basketball players grouped as under-16 youth (n = 10) and professional adult (n = 10) players. Each participant completed 50 shots at two distances (long range: 6.80 m; middle range: 4.23 m). Eye tracking glasses were used to obtain quiet eye (QE), the number of fixations, total fixation duration, duration of first and last fixation. An independent t-test was used to assess differences between groups. Shooting accuracy given by % of efficacy indicated that under-16 players attained poorer scores at both distances: long (t = -4.75, p < 0.01) and middle (t = -2.80, p < 0.012) distance. The groups also differed in QE time (long: 600 ms vs. 551 ms; middle: 572 ms vs. 504 ms) and total duration of the fixations (long: 663 ms vs. 606 ms; middle: 663 ms vs. 564 ms) in both long and middle distance shots. Significant differences also occurred in the last fixation (long distance: t = -4.301, p < 0.01; middle distance: t = -3.656, p < 0.01) with professional adult players presenting the value of, on average, 454-458 ms, while youth shooters 363-372 ms. In summary, visual strategy differed between under-16 youth and professional adult basketball players. To support their long-term sport development, it is recommended that youth basketball players focus their attention with longer final fixation before releasing the ball to improve their shot.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it