3D-Multiple Object Tracking training task improves passing decision-making accuracy in soccer players
Why this work is in the frame
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Bibliographic record
Abstract
The ability to perform a context-free 3-dimensional multiple object tracking (3D-MOT) task has been highly related to athletic performance. In the present study, we assessed the transferability of a perceptual-cognitive 3D-MOT training from a laboratory setting to a soccer field, a sport in which the capacity to correctly read the dynamic visual scene is a prerequisite to performance. Throughout pre- and post-training sessions, we looked at three essential skills (passing, dribbling, shooting) that are used to gain the upper hand over the opponent. We recorded decision-making accuracy during small-sided games in university-level soccer players (n = 23) before and after a training protocol. Experimental (n = 9) and active control (n = 7) groups were respectively trained during 10 sessions of 3D-MOT or 3D soccer videos. A passive control group (n = 7) did not received any particular training or instructions. Decision-making accuracy in passing, but not in dribbling and shooting, between pre- and post-sessions was superior for the 3D-MOT trained group compared to control groups. This result was correlated with the players' subjective decision-making accuracy, rated after pre- and post-sessions through a visual analogue scale questionnaire. To our knowledge, this study represents the first evidence in which a non-contextual, perceptual-cognitive training exercise has a transfer effect onto the field in athletes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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