Investigation of Positional Differences in Fitness of Male University Ice Hockey Players and the Frequency, Time Spent and Heart Rate of Movement Patterns during Competition
Bibliographic record
Abstract
Background: Men’s university ice hockey has received little scientific attention over the past 30 years, a time in which the traits of the players and the demands of the game have evolved. Objectives: This study compared the physiological characteristics of university ice hockey players and examined the frequency and duration of the different movement patterns and heart rate (HR) responses during competition. Methods: Twenty male ice hockey players from the same team ( age ± SD = 22±2 years) underwent a fitness evaluation and were filmed and HR monitored during regular season games. Results: Forwards and defense had similar fitness and only differed on % fatigue index and peak heart during on-ice sprinting (P<0.05). Defense stood, glided and skated backwards more than forwards and forwards skated at a moderate intensity and glided forward more than defense (P<0.05). All players spent the majority of game time gliding forward (60% of the time) followed by skating forward at a moderate intensity (17%) and standing with little movement (9%). Average HR during the game reached 96 and 92 % and peak HR was 100 and 96 % of maximum in forwards and defense, respectively. Conclusions: Male university hockey players present with a high level of physical fitness in a variety of categories with few differences between forwards and defense. Movement patterns during games suggest that players are performing low to moderate intensity on-ice activities the majority of the time. Paradoxically, HR continues to climb to near maximum during on ice shifts.
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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 | 0.000 | 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 | 0.001 |
| 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".