Age- and Gender-Specific Reference Values for Physical Performance in Tunisian Youth Basketball Players
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Physical performance is becoming increasingly critical in basketball, as it directly influences players' agility, power, and endurance. This study aimed to assess the progression of body composition and physical performance metrics across different ages and genders, establishing age- and gender-specific reference values for Tunisian basketball athletes. METHODS: A total of 469 Tunisian basketball players (239 boys and 230 girls) were assessed and grouped by age. Anthropometric measures-including standing and sitting height, body mass, leg length, body mass index, fat mass, fat-free mass, body fat percentage, wingspan, and leg muscle volume-were collected alongside physical performance metrics. Performance tests included countermovement and squat jumps, change-of-direction speed, maximal oxygen uptake, flexibility, the five-jump test, and 5 m, 10 m, and 20 m sprints with and without the ball. Normative data were generated based on age and gender categories. RESULTS: The findings revealed significant age-related improvements in both anthropometric and performance parameters. Boys consistently outperformed girls in physical and fitness-related measures, with gender differences becoming more pronounced with age. Stepwise regression analyses indicated that, for boys, body fat percentage, leg muscle volume, standing height, and wingspan were the best predictors of physical performance. For girls, body fat percentage, standing height, and sitting height were identified as key predictors. CONCLUSIONS: The newly established Tunisian reference values for physical performance in youth basketball provide valuable benchmarks that can support the development of explosive power and strength in players, aiding in talent identification and potentially enhancing individual and team performance outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".