Open AccessThe Development of Athlete Performance Capabilities Index (APCI) Model for Male U12 Player Selection using Multivariate Analysis
Author(s) -
Mohamad Razali Abdullah,
Hafizan Juahir,
N. Mohamad Shukri,
N. A. Fuat,
N. A. Mohd Ros,
Fuziatul Norsyiha Ahmad Shukri,
NurfadhlinaAbdul Halim,
Siti Musliha Mat-Rasid,
Rabiu Muazu Musa,
Ahmad Bisyri Husin Musawi Maliki,
Norlaila Azura Kosni,
Mohd Syaiful Nizam Abu Hassan,
Mohd Khairi Zawi,
Vijayamurugan Eswaramoorthi
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.34.23589
Subject(s) - statistics , multivariate statistics , principal component analysis , linear discriminant analysis , multivariate analysis , index (typography) , anthropometry , mathematics , computer science , medicine , world wide web
This study develops an Athlete Performance Capabilities Index (APCI) model using multivariate analysis for selecting the best player of under twelve (U12). Measurement of anthropometrics and physical fitness were evaluated among 178 male players aged 12±0.52 years. Factor score derived by Principal Component Analysis were used to obtain a model for APCI and Discriminant Analysis (DA) were conducted to validate the correctness of group classification by APCI. Result was found two factors with eigenvalues greater than 1 were extracted which accounted for 62.00% of the variations present in the original variables. The two factors were used to obtain the factor score coefficients explained by 35.72% and 26.67% of the variations in athlete performance respectively. Factor 1 revealed high factor loading on fitness compared to Factor 2 as it was significantly related to anthropometrics. A model was obtained using standardized coefficient of factor 1. Three clusters of performance were shaped in view by categorizing APCI ≥ 75%, 25% ≤ APCI < 75% and APCI < 25% as high, moderate and low performance group respectively. Three discriminated variables out of thirteen variables were obtained using Forward and Backward stepwise mode of DA, which were weight, standing broad jump, and 40 meters’ speed. Such variables were established as essential indicator for selecting the best player among male U12.