Interseason variability of a functional movement test, the 9+ screening battery, in professional male football players
Bibliographic record
Abstract
BACKGROUND: The Nine Plus screening battery test (9+) is a functional movement test intended to identify limitations in fundamental movement patterns predisposing athletes to injury. However, the interseason variability is unknown. AIM: To examine the variability of the 9+ test between 2 consecutive seasons in professional male football players. METHODS: Asymptomatic Qatar Star League players (n=220) completed the 9+ at the beginning of the 2013 and 2014 seasons. Time-loss injuries in training and matches were obtained from the Aspetar Injury and Illness Surveillance Program. No intervention was initiated between test occasions. RESULTS: A significant increase in the mean total score of 1.6 points (95% CI 1.0 to 2.2, p<0.001) was found from season 1 (22.2±4.1 (SD)) to season 2 (23.8±3.3). The variability was large, as shown by an intraclass correlation coefficient (ICC) of 0.24 (95% CI 0.11 to 0.36) and a minimal detectable change (MDC) of 8.7 points. Of the 220 players, 136 (61.8%) suffered a time-loss injury between the 2 tests. There was an improvement in mean total scores in the injured (+2.0±0.4 (SE), p<0.001) group but not in the uninjured group (+0.9±0.5, p=0.089). The variability from season 1 to season 2 was large both in the injured (ICC 0.25, 0.09 to 0.40, MDC 8.3) and uninjured (ICC 0.24, 0.02 to 0.43, MDC 9.1) groups. CONCLUSIONS: The 9+ demonstrated substantial intraindividual variability in the total score between 2 consecutive seasons, irrespective of injury. A change above 8 points is necessary to represent a real change in the 9+ test between seasons.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".