A multilateral modelling of Youth Soccer Performance Index (YSPI)

International Conference on Innovative Technology, Engineering and Sciences 2018

工业技术;自然科学

Maliki, Ahmad Bisyri Husin Musawi^2 ; Abdullah, Mohamad Razali^1,2 ; Juahir, Hafizan^1 ; Abdullah, Farhana^2 ; Abdullah, Nurul Ain Shahirah^2 ; Musa, Rabiu Muazu^2,3 ; Mat-Rasid, Siti Musliha^1 ; Adnan, Aleesha^2 ; Kosni, Norlaila Azura^2 ; Muhamad, Wan Siti Amalina Wan^2 ; Nasir, Nur Afiqah Mohamad^2

East Coast Environmental Research Institute (ESERI), Universiti Sultan Zainal Abidin, Terengganu

21300, Malaysia^1

Faculty of Applied Social Sciences, Universiti Sultan Zainal Abidin, Terengganu

21300, Malaysia^2

Innovative Manufacturing, Mechatronics and Sports Lab (IMAMS), Faculty of Manufacturing Engineering, Universiti Malaysia Pahang, Pekan Campus, Pekan, Pahang

26600, Malaysia^3

关键词: Confirmatory factor analyses (CFA);    Dominant factor;    Exploratory Factor Analysis (EFA);    Group performance;    Index analysis;    Performance indices;    Prediction model;    Regression model;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/342/1/012057/pdf
DOI  :  10.1088/1757-899X/342/1/012057

来源: IOP

【 摘 要 】

This study aims to identify the most dominant factors that influencing performance of soccer player and to predict group performance for soccer players. A total of 184 of youth soccer players from Malaysia sport school and six soccer academy encompasses as respondence of the study. Exploratory factor analysis (EFA) and Confirmatory factor analysis (CFA) were computed to identify the most dominant factors whereas reducing the initial 26 parameters with recommended >0.5 of factor loading. Meanwhile, prediction of the soccer performance was predicted by regression model. CFA revealed that sit and reach, vertical jump, VO2max, age, weight, height, sitting height, calf circumference (cc), medial upper arm circumference (muac), maturation, bicep, triceps, subscapular, suprailiac, 5M, 10M, and 20M speed were the most dominant factors. Further index analysis forming Youth Soccer Performance Index (YSPI) resulting by categorizing three groups namely, high, moderate, and low. The regression model for this study was significant set as p 2is 0.8222 which explained that the model contributed a total of 82% prediction ability to predict the whole set of the variables. The significant parameters in contributing prediction of YSPI are discussed. As a conclusion, the precision of the prediction models by integrating a multilateral factor reflecting for predicting potential soccer player and hopefully can create a competitive soccer games.