Body Fat Is a Predictor of Physical Fitness in Obese Adolescent Handball Athletes
Bibliographic record
Abstract
We examined the relationships between body fat (BF) and field measures of physical fitness in adolescent handball players. Twenty nine players (age: 16.6 ± 1.72 years; body mass: 79.8 ± 17.0 kg; height: 1.70 ± 0.12 m; body fat: 27.7 ± 8.67%) from Qatar handball first league performed a series of anthropometric and fitness tests related to their performance in sprinting (i.e., 15 m and 30 m sprint), jumping (i.e., countermovement and squat jumps), throwing (i.e., 3 kg medicine ball seated front throw) and running (i.e., agility T-Half and Yo-Yo intermittent recovery level 1 tests). Significant differences between obese and non-obese groups, classified based on age-stratified %BF norms, were found, with the largest difference being attributed to aerobic performance on the Yo-Yo test. Results indicated no significant relationships between anthropometric variables and sprinting or jumping abilities. %BF predicted a significant 8-15% portion in running performances of agility and aerobic capacity, while the latter were mainly explained by body height and mass. %BF was the only and strongest predictor of throwing performance, being an important determinant of performance in handball. Optimizing %BF should be considered as a training and nutrition goal in order to improve sport 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) | 0.000 | 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 | 0.000 | 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".