Effect of Carbohydrate Ingestion on Basketball Performance in Competitive Players
Bibliographic record
Abstract
Research has shown that carbohydrate (CHO) intake improves performance in activities >45 minutes. Basketball requires intermittent high-intensity exercise bouts over the course of 20 minute halves or 12-minute quarters, suggesting that players may benefit from CHO intake during games. PURPOSE: The purpose of this investigation was to measure the affect of CHO ingestion on basketball performance. METHODS: Five male NCAA Division 1 basketball players (23.6±1.8yrs, 193±3.1cm, 87.2±3.8kg) completed two randomized game simulations. Each simulation consisted of game-like drills separated into quarters. The first and second quarter drills were repeated during the third and fourth quarters, respectively. Participants were allowed a five-minute break after the first and third quarters, with a 10-minute break after the second quarter for halftime. During the course of each game simulation, participants consumed 1000 ml of either a 6% CHO beverage or placebo (PLA). Participants consumed 250 ml after the first and third quarter breaks and 500 ml at halftime. A paired T-test was used to compare data between trials. Significance was set at p < 0.05. RESULTS: There were no differences between CHO and PLA trials in the first and second quarter drills. During the third quarter there was a trend (30.2±4.5 to 31.0±4.6s; p=0.08) for a faster full court combination drill in CHO. During the fourth quarter the key combination drill was completed faster in CHO (40.7±4.4 to 42.8±4.1s p=0.002). Additionally, there was a trend for faster completion of the lane slide drill in the CHO trial (36.5±2.2s to 38.1±2.1s; p=0.07). CONCLUSION: Although there were no differences in drill performance during the first two quarters, there is evidence that CHO intake led to faster completion of various third and fourth quarter drills. These data suggest that CHO intake during a basketball game may lead to performance improvements in the latter moments of a game.
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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) | 0.000 | 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 | 0.001 | 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".