Intensity demands and peak performance of elite soccer referees during match play
Bibliographic record
Abstract
Objectives This study examined the peak physical and physiological (heart rate) performance intensities andassociated decrements in elite soccer referees during match play. Design Longitudinal study. Methods Physical performancevariables and heart rate were analyzed during 457 matches across two seasons. Differences between halves, and the rate ofdecline in peak performance intensities across moving average durations of 1–10 minutes were assessed using linear mixed models and power-law analysis, respectively. Results Large significant differences were observed between halves for mean total distance, mean velocity, mean heart rate, and percentage of maximal heart rate (p ≤ 0.05; r = 0.51–0.64). Peak intensities (p ≤ 0.05; r = 0.15–0.17) and the rate of decline (p < 0.001; r = 0.17–0.37) were significantly higher in the 2 nd half compared to the 1 st half, for relative total distance, relative high-intensity running and mean velocity. The rate of decline was significantly greater in the 2 nd half than the 1 st half for relative distance covered by high-intensity acceleration (>2 m/s –2 /min), deceleration (<-2 m/s –2 /min), and relative mean heart rate (p < 0.001; r = 0.28–0.61). Elite soccer referees might have experienced transient fatigue during match play, as relative high-intensity running immediately following the most intense 5-minute period significantly declined by 61.2% ( p< 0.001; r = 0.94), and was 16.2% lower than the mean 5-minute period (p < 0.001; r = 0.34). Conclusions Increased physical and physiological demands during match play, with associated declines in the second half and transient signs of fatigue throughout the match, supports the inclusion of high-intensity interval and endurance training programs to prepare soccer referees for the intensity demands and peak performance outcomes of match play.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".