Effects of isolated or combined carbohydrate and caffeine supplementation between 2 daily training sessions on soccer performance
Bibliographic record
Abstract
This study aimed to investigate whether isolated or combined carbohydrate (CHO) and caffeine (CAF) supplementation have beneficial effects on performance during soccer-related tests performed after a previous training session. Eleven male, amateur soccer players completed 4 trials in a randomized, double-blind, and crossover design. In the morning, participants performed the Loughborough Intermittent Shuttle Test (LIST). Then, participants ingested (i) 1.2 g·kg(-1) body mass·h(-1) CHO in a 20% CHO solution immediately after and 1, 2, and 3 h after the LIST; (ii) CAF (6 mg·kg(-1) body mass) 3 h after the LIST; (iii) CHO combined with CAF (CHO+CAF); and (iv) placebo. All drinks were taste-matched and flavourless. After this 4-h recovery, participants performed a countermovement jump (CMJ) test, a Loughborough Soccer Passing Test (LSPT), and a repeated-sprint test. There were no main effects of supplementation for CMJ, LSPT total time, or best sprint and total sprint time from the repeated-sprint test (p>0.05). There were also no main effects of supplementation for heart rate, plasma lactate concentration, rating of perceived exertion (RPE), pleasure-displeasure, and perceived activation (p>0.05). However, there were significant time effects (p<0.05), with heart rate, plasma lactate concentration, RPE, and perceived activation increasing with time, and pleasure-displeasure decreasing with time. In conclusion, isolated and/or combined CHO and CAF supplementation is not able to improve soccer-related performance tests when performed after a previous training session.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".