Affiliation:
1. Department of Physical Education, Aligarh Muslim University, Aligarh, Uttar Pradesh, India
2. Department of Physical Therapy, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
3. Department of Rehabilitation Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.
Abstract
In volleyball, a strong correlation exists between the proper application of kinematics factors and the serve results. Therefore, this study compared the kinematics parameters of the volleyball jump serve among different functional classes and established an appropriate multilinear regression model of performance. This correlational observational study involved thirty male collegiate volleyball players categorized into under twenty-three (U-23) men, under twenty-one (U-21) junior men, and under nineteen (U-19) youth boys. Data acquisition entailed the utilization of synchronized cameras to capture the volleyball serves meticulously, while subsequent data analysis was conducted through the implementation of silicon coach–pro 8 motion analysis software. Analysis of variance and multiple linear regressions were performed to analyze data, with a predetermined significance level of P < .05. Jump serve analysis showed significant mean differences in selected major kinematic variables among all 3 classes (U-23 men, U-21 junior men, and U-19 youth boys). U-23 men Model-3, which includes 3 independent variables (approach velocity [AV], shoulder extension angles during the cocking phase, and center of gravity [CG] height), predicted velocity with an R-square of 1.00, indicating that the selected independent variable caused 100% variation in ball velocity (BV), whereas models 1 and 2 showed 99% variation in BV, respectively. The U-21 Junior men Model-2, which includes 2 independent variables (height of CG and shoulder extension angles during the cocking phase), predicted velocity with an R-square of 9.80, indicating that the selected independent variable caused a 98% variation in BV. In contrast, model 1 showed a 94% variation in BV, respectively. U-19 youth boys Model-1, which includes one independent variable (AV), predicted velocity with an R-square of 0.89, indicating that the selected independent variable caused 89% variation in BV. The jump serve exhibits similar biomechanical characteristics across different classes. However, the major independent variables of the jump serve: U-23 men were AV, shoulder extension angles at cocking phase (SEACP), the height of CG, U-21 junior men were SEACP and height of CG, and U-19 youth boys were SEACP and height of CG AV showed significant with the dependent variable (BV).
Publisher
Ovid Technologies (Wolters Kluwer Health)
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