An Experimental Model on Multiple Regression Analysis in CMJ and SJ Jump Tests on 10-14 Years Old Players of Tirana Football Club

Aida Bendo,Ferdinand Mara

doi:10.13189/saj.2020.080518

Abstract

In vertical jump performance, the goal of the task is simply to jump as high as possible. In many sports, the height at which an athlete can jump is often of critical importance, as well as the maximal force applied during the vertical jump. In the absence of resistance to air and other external forces, the projection of the center of gravity COG of the whole body is completely determined by the vertical velocity at the moment of takeoff and the acceleration due to gravity. However, this quality does not fully describe the full jump and height achieved. This study aims to use the multiple regression method in both CMJ and SJ vertical jump tests, to understand whether vertical jump performance for Hmax and Fmax respectively parameters, can be predicted based on anthropometric variables such as: age, height, and body mass, as well as biomechanical variables such as: vmax, F.tot.rel, EFI and efficiency. Multiple regression method allows to determine the overall fit of the model and the relative contribution of each of predictor to the total variance explained. The equations of regression for this team emerged these parameters as the best predictor of the main variables for each test: for Hmax in CMJ test: vmax and body mass; and for Fmax in SJ test: body mass and Pmax/kg.

Highlights

Locomotion and neuromuscular function are important factors in understanding and assessing motor performance
In the first countermovement jump (CMJ) test, the multiple regression method is used to understand if the performance of vertical jump test to measure the maximum height (Hmax) can be predicted based on anthropometric variables such as age, body height, body mass and in the biomechanics variables as maximum velocity (Vmax), the total relative strength (F.tot.rel), Esslinger Fitness Index (EFI) and efficiency of movement
At CMJ test should be known the percentage of variation of test performance on the dependent variable (Hmax) that can be explained by anthropometric and biomechanics parameters as a whole, and the "relative contribution" of each of the independent variables in explaining variance

Summary

Introduction

Locomotion and neuromuscular function are important factors in understanding and assessing motor performance. A study has found that the ability to generate lower body power is a key component for success in many sport activities [7]. Applied to the vertical jump, general strength training exercises are those that are aimed at increasing the maximal strength of the muscles involved in jumping [4]. Various types of strength-training modalities have been utilized in order to improve lower body power as can be measured by vertical jump [7]. Some studies have shown that both the individual plyometric and weight training programs increased vertical jump performance, but the combination program showed the greatest improvement of vertical jump performance, [2; 5; 10]

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