Jumping Side Volley in Soccer—A Biomechanical Preliminary Study on the Flying Kick and Its Coaching Know-How for Practitioners
Bibliographic record
Abstract
The jumping side volley has created breathtaking moments and cherished memories for soccer fans. Regrettably, scientific studies on the skill cannot be found in the literature. Relying on the talent of athletes to improvise on the fly can hardly be considered a viable learning method. This study targeted to fill this gap by quantifying the factors of the jumping side volley and to contribute to the development of a coaching method for it. Using 3D motion capture (12 cameras, 200 Hz) and full-body biomechanical modeling, our study aimed to identify elements that govern the entrainment of skill execution. Given the rarity of players who have acquired this skill and the low success rate of the kick (even in professional games), we were able to achieve and review 23 successful trials from five college-level subjects and quantify them for the study. The results unveiled the following key elements: (1) the control of trunk rotation during jumping, (2) the angle between thighs upon take-off, (3) the whip-like control of the kicking leg while airborne, (4) timing between ball motion and limb coordination, and (5) damping mechanism during falling. An accurate kick can normally be achieved through repetitive training. This underlines the need for athletes to master a safe landing technique that minimizes risk of injury during practice. Therefore, training should begin with learning a safe falling technique.
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How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".