2017•International Journal of Physical Education Sports and HealthRequires access

Impact of linear kinematic parameters on long jump performance: A three dimensional study

Bhanu Pratap, AS Sajwan, Pushpendra Purashwani

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Abstract

The present study intended to find out the relationship among the Linear Kinematic variables of take off in long jump and also find out which linear kinematic variable was most contributing factor in the enhancement of the long jump performance. The sample consisted of 5 (Five) Long Jumpers in the age group of 17-25 years’ with mean 21.47, The test item (parameters) selected for examined Linear kinematic was Center of Mass, horizontal velocity and vertical velocity the statistical technique regression analysis was used for the present study. The present finding towards, Linear Kinematic parameters are quite thought provoking and noteworthy. Linear kinematic (vertical velocity) only showed a statistically significant difference revealed that significant relationship of vertical velocity with the performance in Long Jump also provides further insight into Long Jump, although not all variables associated with real jumping performance. To conclude, it might be interpreted that the above regression equation was reliable as the value of R2 is .60.0. In other words, the one variable selected in this regression equation explains 60.0% of the total variability in the vertical velocity which was good. Since F- value for this regression model was significant & reliable. They found that jump performance was enhanced by a high approach speed, a high knee angle at touch-down and high (concentric and eccentric) muscle strength. Factors which did not have a great influence on jump distance were tendon compliance, muscle fibre contraction speed and some aspects of muscle architecture. We concluded that in the long jump, variables that are important to performance are interdependent and can only be identified by using appropriate statistical techniques. This has implications for a better understanding of the long jump event and it is likely that this finding can be generalized to other technical sports skills.

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What this paper is about

The present study intended to find out the relationship among the Linear Kinematic variables of take off in long jump and also find out which linear kinematic variable was most contributing factor in the enhancement of the long jump performance. The sample consisted of 5 (Five) Long Jumpers in the age group of 17-25 years’ with mean 21.47, The test item (parameters) selected for examined Linear kinematic was Center of Mass, horizontal velocity and vertical velocity the statistical technique regression analysis was used for the present study. The present finding towards, Linear Kinematic parameters are quite thought provoking and noteworthy. Linear kinematic (vertical velocity) only showed a statistically significant difference revealed that significant relationship of vertical velocity with the performance in Long Jump also provides further insight into Long Jump, although not all variables associated with real jumping performance. To conclude, it might be interpreted that the above regression equation was reliable as the value of R2 is .60.0. In other words, the one variable selected in this regression equation explains 60.0% of the total variability in the vertical velocity which was good. Since F- value for this regression model was significant & reliable. They found that jump performance was enhanced by a high approach speed, a high knee angle at touch-down and high (concentric and eccentric) muscle strength. Factors which did not have a great influence on jump distance were tendon compliance, muscle fibre contraction speed and some aspects of muscle architecture. We concluded that in the long jump, variables that are important to performance are interdependent and can only be identified by using appropriate statistical techniques. This has implications for a better understanding of the long jump event and it is likely that this finding can be generalized to other technical sports skills.

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Available abstract

The present study intended to find out the relationship among the Linear Kinematic variables of take off in long jump and also find out which linear kinematic variable was most contributing factor in the enhancement of the long jump performance. The sample consisted of 5 (Five) Long Jumpers in the age group of 17-25 years’ with mean 21.47, The test item (parameters) selected for examined Linear kinematic was Center of Mass, horizontal velocity and vertical velocity the statistical technique regression analysis was used for the present study. The present finding towards, Linear Kinematic parameters are quite thought provoking and noteworthy. Linear kinematic (vertical velocity) only showed a statistically significant difference revealed that significant relationship of vertical velocity with the performance in Long Jump also provides further insight into Long Jump, although not all variables associated with real jumping performance. To conclude, it might be interpreted that the above regression equation was reliable as the value of R2 is .60.0. In other words, the one variable selected in this regression equation explains 60.0% of the total variability in the vertical velocity which was good. Since F- value for this regression model was significant & reliable. They found that jump performance was enhanced by a high approach speed, a high knee angle at touch-down and high (concentric and eccentric) muscle strength. Factors which did not have a great influence on jump distance were tendon compliance, muscle fibre contraction speed and some aspects of muscle architecture. We concluded that in the long jump, variables that are important to performance are interdependent and can only be identified by using appropriate statistical techniques. This has implications for a better understanding of the long jump event and it is likely that this finding can be generalized to other technical sports skills.

Key concepts: Kinematics, Jump, Mathematics, Linear regression, Concentric, Muscle architecture, Regression analysis, Vertical jump

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