The Effect of Fluid Ingestion During Soccer Training on Fluid Balance and Aerobic Test Performance
Bibliographic record
Abstract
Previous research in warm and cool environments demonstrated that soccer players do not voluntarily replace the sweat losses incurred during training sessions. Sweat losses of ~2% body mass have been shown to impair the performance of soccer-specific skills. PURPOSE: To examine the pre-training hydration status, sweat and sodium losses of female varsity soccer players (n=12, 18 - 20 years, 60.9 ± 1.7 kg, 1.79 ± 0.02 m), and evaluate their aerobic performance following three, 90 min training sessions. METHODS: The study employed a randomized, crossover design and all players completed, 1) no fluid (NF), 2) sweetened water (W), and 3) carbohydrate-electrolyte solution (CES) trials. Players drank 1 litre of the assigned fluid (blinded) during training in the W and CES trials in doses of 250 ml at -30 min and 0 before practice, and 30 and 60 min during practice. Pre-practice hydration status was estimated by measuring urine specific gravity (USG). Sweat rates were calculated from body mass changes and fluid intake. Sweat sodium concentration ([Na]) was analyzed in forehead sweat patch samples and used with sweat rate to estimate sodium loss. Aerobic performance was measured with a repeated, 20 m running test to fatigue (beep test) following all practices. RESULTS: Pre-practice USG was not different between NF (1.016 ± 0.003), W (1.021 ± 0.002), and CES (1.015 ± 0.003). Body mass loss was greatest in NF (2.4 ± 0.2%) compared to W and CES (0.3 ± 0.2, 0.1 ± 0.2%). Sweat rate during practice was significantly higher in NF (0.95 ± 0.09 l·hr-1) than in W and CES (0.69 ± 0.09, 0.65 ± 0.07 l·hr-1). Sweat [Na] was not different between NF (61.5 ± 3.6 mM), W (53.5 ± 3.1 mM), and CES (56.9 ± 5.2 mM), but net sodium loss was greater in NF (2040 ± 246 mg) than in W and CES (1271 ± 171, 867 ± 263 mg). Subjects were successfully blinded from the drinks and aerobic performance (beep test) was prolonged over NF by 7 levels in W, and further prolonged by 4 levels in CES. CONCLUSIONS: Female varsity soccer players incurred large sweat and sodium loses during a 90 min practice. Consuming 1 litre of fluid throughout practice prevented body mass losses and prolonged fatigue during an aerobic performance test. Consuming a CES was able to improve performance appreciably over water alone.
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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 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".