Concentric and eccentric isokinetic hamstring injury risk among 582 professional elite soccer players: a 10-years retrospective cohort study
Bibliographic record
Abstract
BACKGROUND/AIM: Different authors have tried to correlate the peak isokinetic torque values with the incidence of soccer match injuries. However, due to the wide variety of assessment testing protocols, such an inference becomes difficult. This study aimed to verify the capacity of an isokinetic test to establish injury risk reference values for hamstring strain injuries. METHODS: A retrospective cohort study based on isokinetic data and clinical records from the last 10 years was conducted in 582 Brazilian elite-professional soccer players, who were subjected to the same isokinetic test protocol, machine, and tester. A Multivariate Logistic Regression Analysis for Complex Data Sampling was used to generate injury risk statistical indexes. RESULTS: Multivariate regression analysis of both legs provided important data to identify the cut-off values of Concentric Peak Torque (181.82 Newton/*metres), Concentric Work (236.23 watts) and Concentric Power (130.11 joules). CONCLUSIONS: The injury risk indexes indicate that an increase of just one Newton unit in CPT (Concentric Peak Torque) and CJ (Concentric Power) above those cut-off values, can reduce the risk of future injuries by 2% and 2.7%, respectively.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".