Comparative Analysis between Effect of Shoulder Strength and Core Endurance on Bowling Speed in Pace Bowlers
Bibliographic record
Abstract
Background: Cricket has received considerable research attention due to popularity. Ability of bowlers to bowl with high-speed plays a major role in success. Earlier studies have suggested that shoulder and core play a crucial role in kinetic chain which results in improved bowling speed. Objective: The objective of this study was to study relative efficacies of shoulder strength and core endurance on bowling speed in pace bowlers. Methods: Forty male pace bowlers having age (20.10 ± 3.71) in years from Punjab participated in the study. Bowling speed was measured with Radar Gun. Shoulder strength measured with Biodex dynamometer. Core endurance was measured by McGill protocol. Statistical analysis of was carried out using SPSS version 23. Results: Bowling speed was recorded as mean ± SD 91.00 ± 10.10 km/h. Significant fair positive relationship found between bowling speed and external rotators at angular velocity of 90°/s and (r = 0.386) and shoulder flexors at 60°/s (r = 0.408), 90°/s (r = 0.383), and 120°/s (r =0.448). Trunk extension shows fair positive significant relationship (r =0.327) with bowling speed. Conclusion: The present study contributes toward pace bowlers’ training and focus on necessity of further research considering limitations of COVID-19 pandemic.
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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 | 0.000 |
| 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".