Association Between Variations in Training Load, Sleep, and the Well-Being of Professional Hockey Players
Bibliographic record
Abstract
PURPOSE: To evaluate whether sleep quantity and quality of professional hockey players is affected by external training load (TL), their perception of well-being, and contextual factors associated with match participation. METHODS: Fifty male athletes were monitored daily during the 28 weeks of the regular season using well-being and sleep surveys. On-ice external TL was monitored using portable inertial measurement units during practices and matches. Linear mixed-effects models were applied to evaluate whether well-being perception (ie, pain, nutrition, stress, and rest) and external TL may affect sleep quality and quantity. RESULTS: High levels of well-being positively affected sleep duration and quality (P < .001), whereas high-intensity TL had a detrimental impact on sleep duration (P = .007). Moreover, away and evening matches had a detrimental effect on sleep quantity and quality (P < .001). Finally, a high match on-ice load per minute had a negative association with sleep quality (P = .04). CONCLUSIONS: Findings indicate that well-being and high-intensity trainings can impair sleep duration and quality. In addition, high-intensity match load, away matches, and evening matches can impair postmatch sleep. Therefore, monitoring well-being in conjunction with TL is essential to understand sleep disturbances in athletes. Practitioners should also implement sleep hygiene strategies that facilitate longer time in bed after high-intensity, away, and evening matches to help athletes recover.
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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".