The effect of sex, skill level and a defender on cutting kinematics in soccer players
Bibliographic record
Abstract
Cutting patterns may be influenced by task complexity and player attributes, ultimately affecting injury risks. This study examines the impact of skill level, sex, and defender conditions on joint kinematics during unanticipated cutting in soccer players. Kinematic data were captured using a three-dimensional motion capture system for 14 competitive and 14 recreational players performing unanticipated sidesteps (45 ± 10 degrees) under three conditions: no obstacle (NO), static-defender obstacle (SO) and dynamic-defender obstacle (DO). Principal component (PC) analysis and hierarchical linear models examined joint kinematics against sex, skill and defender conditions. For the first component of PC, skill effects revealed greater ankle dorsiflexion angles throughout cutting in competitive players (p = 0.01) than recreational players. DO trials showed lower hip flexion (p = 0.001) and ankle dorsiflexion angles (p = 0.01) than NO. SO trials showed greater hip adduction (p < 0.001) and knee abduction angles (p = 0.04), but lower ankle dorsiflexion angles (p < 0.001) than NO. For PC2, SO trials showed greater hip flexion excursions (p = 0.005) than NO. No sex effects were found. Clearance (participant’s distance to the defender) was examined using a three-way analysis of covariance. Greater distances were found in DO by 0.59 m than SO. Differences in cutting patterns highlight potential adaptations to varying defender pressures, providing insights for coaching and prevention programmes.
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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".