Physical, physiological demands and movement profiles of professional men’s field hockey games
Bibliographic record
Abstract
The aim of this study was to investigate the physical demands, physiological demands, and movement profiles of different positions across four quarters in professional men’s field hockey games. Eighteen professional male field hockey players participated in the study, and data were collected in eleven official matches. Players wore global positioning system units and heart rate monitors to collect physical, physiological, and movement profile data. Defenders had significantly higher absolute total distance covered, player load, acceleration and deceleration count, and forward-backward initial movement analysis (IMA) count, but lower high speed running distance, compared with midfielders and forwards (p<.05). However, when using relative metrics (normalised by playing time), defenders had the lowest physical and physiological outputs, and forwards were the highest (p<.05). Total distance covered per minute, high-speed running distance per minute, player load per minute, acceleration and deceleration count per minute, and repeated high-intensity efforts per minute were all significantly higher in quarter 1 than in other three quarters (p<.05). The percentages of linear running and non-linear dynamic movement duration decreased quarter by quarter. Modified training impulse per minute reached its peak in quarter 2 (p<.05). It was concluded that defenders had the highest volume in terms of the game demands due to their high playing minutes; however, they had the lowest relative volume compared with other two positions. Forwards had the highest linear running intensity, while midfielders were required to perform more multi-directional, non-linear movements. Quarter 1 was the most active quarter and players became fatigued in quarter 2. IMA counts were not sensitive to fatigue compared to movement profile and modified training impulse variables.
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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 | 0.000 |
| 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".