Effects of Combined Balance and Plyometric Training on Athletic Performance in Female Basketball Players
Bibliographic record
Abstract
Bouteraa, I, Negra, Y, Shephard, RJ, and Chelly, MS. Effects of combined balance and plyometric training on athletic performance in female basketball players. J Strength Cond Res 34(7): 1967-1973, 2020-The purpose of this study was to examine the effect of 8 weeks combined balance and plyometric training on the physical fitness of female adolescent basketball players. Twenty-six healthy regional-level players were randomly assigned to either an experimental group (E; n = 16, age = 16.4 ± 0.5) or a control group (C; n = 10, age = 16.5 ± 0.5). C maintained their normal basketball training schedule, whereas for 8 weeks E replaced a part of their standard regimen by biweekly combined training sessions. Testing before and after training included the squat jump (SJ), countermovement jump (CMJ), drop jump (DJ), 5-, 10-, and 20-m sprints, Stork balance test (SBT), Y-balance test (YBT) and modified Illinois change of direction test (MICODT). Results indicated no significant intergroup differences in SJ and CMJ height; however, E increased their DJ height (p < 0.05, Cohens'd = 0.11). No significant intergroup differences were found for sprint performance or SBT, but dynamic YBT tended to a significant group interaction (p = 0.087, d = 0.006). Post hoc analysis also showed a significant increase of MICODT for E (Δ 6.68%, p = 0.041, d = 0.084). In summary, the addition of 8 weeks of balance and plyometric training to regular in-season basketball training proved a safe and feasible intervention that enhanced DJ height, balance, and agility for female adolescent basketball players relative to the standard basketball training regimen.
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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 | 0.000 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".