Effect of Bosu Ball and Pilates Exercises on Core Stabilization among University Cricket Players: An Experimental Study
Bibliographic record
Abstract
Background: Cricket players must practice core stabilization to maintain their balance and stability. Cricket performance relies heavily on balance, making it crucial to design programs that assess, maintain, and enhance these skills. Despite the emphasis on core stability in cricket, limited research explores the comparative effectiveness of different exercise interventions, such as Bosu ball and Pilates workouts, on improving balance and core endurance among athletes. Exercise on unstable surfaces, such as the Bosu ball (both sides up), activates core muscles, while Pilates enhances posture, core strength, balance, and peripheral mobility. Therefore, this study aimed to evaluate the effects of Bosu ball and Pilates exercises on core stability among university cricket players. Methods: In this experimental study, 36 collegiate cricket players participated and were randomly allocated into two groups: Bosu ball and Pilates exercises. Participants' dynamic balance was assessed using the Y Balance Test, static balance using the Flamingo Balance Test, and core endurance using the McGill Core Endurance Test. Evaluations were conducted before and after a six-week intervention period for both groups. Results: Bosu ball exercises were found to be statistically significant (p < 0.01) and more effective than Pilates in improving core stabilization among university cricket players. Conclusion: Both interventions showed improvement in core stability and balance of university cricket players. However, Bosu ball exercises were slightly more effective in enhancing static and dynamic balance compared to Pilates.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".