The Effect Of A Mixed Method Pre- And Halftime Cooling Strategy On Soccer Skill Performance
Bibliographic record
Abstract
Repeated sprinting ability and skill proficiency are key to success in team sports. Cooling lessens the thermal stress during repeated high intensity exercise, and as a result, better preserves repeated sprinting ability. It is unknown if cooling benefits skill performance. PURPOSE: To examine the effect of a mixed method cooling strategy on thermoregulatory responses and skill performance during simulated soccer in the heat. METHODS: Six male university soccer players completed 1 practice and 2 experimental sessions. In the experimental sessions, players completed 2 soccer halves. Each half consisted of a 36-min soccer specific cycling protocol (40 s at 3.3 Wkg-1 followed by 20 s at 1 Wkg-1 x 36 repeats) in the heat (30-32°C, 40-45% humidity). Skills testing made up the remainder of each half. Skill was assessed with a modified Loughborough Soccer Passing Test (LSPT) and a dribbling test. In one session cooling was applied for 25 min before the 1st half and for 15 min at halftime (COOL). Cooling involved ingestion of a sports drink slushy combined with wearing an ice vest. In the other session (CTL) players ingested sports drink. Core (TC) and tympanic temperature (TTY) were monitored throughout. RESULTS: TC at the start of the 1st half was lower in COOL than in CTL (37.0 ± 0.2 vs. 37.4 ± 0.1 °C; p=0.01). The increase in TC in the 1st half (1.3 ± 0.3 vs. 1.3 ± 0.5 °C), TC at the start of the 2nd half (37.4 ± 0.5 vs. 37.8 ± 0.3 °C), and the rise in TC in the 2nd half (0.9 ± 0.2 vs. 0.8 ± 0.5°C) were not different between COOL and CTL. TTY did not differ between COOL and CTL at any time. In COOL, the time needed to complete the LSPT in the 1st and 2nd half was 37.9 ± 1.1 s and 37.8 ± 0.4 s, respectively. Players amassed 8.1 ± 4.4 s and 5.4 ± 3.1 s of penalty time during these tests. Completion time and penalty time in CTL were 38.0 ± 1.2 s and 6.6 ± 2.3 (1st half) and 38.6 ± 1.7 s and 6.9 ± 4.0 s (2nd half). Time to complete the dribbling test in the 1st half equaled 7.0 ± 0.5 s and 6.9 ± 0.5 s in COOL and CTL. In the 2nd half these times equaled 7.1 ± 0.5 s and 7.2 ± 0.5 s. No between-condition differences were observed for any of the skill variables. CONCLUSION: The combination of ice slushy and ice vest cooling effectively reduced TC prior to the simulated soccer. Although thermal stress was slightly lower during the 1st and 2nd half due to cooling, this did not result in better skill performance.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".