The effect of a modified nordic curl intervention on prevalence of hamstrings injuries in a professional football team
Bibliographic record
Abstract
There are many discussions about the occurrence of hamstring injury, especially in running dominant sports such as Canadian rules football. Many interventions exist to decrease the risk and/or occurrence of hamstring injury, with the Nordic Curl being among one of the most studied interventions. The Nordic Curl is commonly implemented as part of a preventative injury program, often alongside various other methods of injury prevention exercises. Limited research exists on the implementation of a “more difficult” variation of the conventional Nordic Curl, which involves keeping the concentric portion in the exercise, as opposed to only completing the eccentric portion. This modified Nordic Curl (mNC) exercise was completed in one professional football team over the duration of four competitive seasons, post practice in a progressive manner to an upper limit of 5 reps per practice. Hamstring injury data collected during the four years of implementing the mNC was compared to the prior four years of hamstring injury data in three categories: rate of hamstring injuries per 4 years; average calendar days lost due to injury; and a comparison of total hamstring injuries per timeframe of the season. Independent t-tests were calculated to analyze for differences between rate of hamstring injuries in the two time periods (intervention vs non-intervention), and average time lost due to hamstring injury between the two time periods. Four Mann Whitney U tests were conducted to examine temporal differences in number of injuries between the intervention and non-intervention periods using four separate timeframes within the competitive season. No significant differences were found with any analyses, but large effect sizes were observed for differences between the groups for rate of hamstring injuries and the number of injuries that occurred in the first 6 weeks of the season. The results suggest the mNC does not significantly affect hamstring injury rates, time lost due to injury or specific timeframes within the competitive season. Future research should seek to investigate the modified version of the Nordic curl’s electromyographical output, as well as further study using a larger sample size than the current study.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".