Development of a Talent Identification Model to Determine the Physical Attributes of Athletes for the Long Jump Event

The purpose of this study is to analyze and determine the physical attributes for use in a Malaysian talent identification model for the athletic long jump event.This is a predictive study that explores the relationship between the physical attributes and how these attributes can be used to predict...

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Bibliographic Details
Main Author: Tan, Kok Siang
Format: Thesis
Language:English
English
Published: 2006
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/205/1/549060_FPP_2006_6.pdf
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Summary:The purpose of this study is to analyze and determine the physical attributes for use in a Malaysian talent identification model for the athletic long jump event.This is a predictive study that explores the relationship between the physical attributes and how these attributes can be used to predict long jump performance (LJUMP).By use of multiple regression analysis,the dependent variable, LJUMP,is predicted from the derived regression equation. The study populations are junior long jumpers consisting of 29 girls with mean age 14.06 years and 20 boys with mean age 14.60 years. Data were collected on their performance in LJUMP,and the physical attributes of anthropometry comprising height (HT),weight (WT),stage of growth and development (GTH), age (AGE), as well as their performance in the 30m Run (RUN), Sit-ups (SITUPS), Sargent Jump (SARG) Standing Long Jump (SLJ) and Sit and Reach (S&R).The predictive equation for the girls is LJUMP = 356.517 + 42.809(z-score SLJ) + 30.081(z-score SARG). SLJ influences LJUMP more than SARG.The model explains 71.6% (R squared) of the variance in LJUMP.Collinearity was of concern and it was treated using z-scores in place of raw scores.The predictive equation for the boys is LJUMP = 104.164 + 4.388(SARG) + 2.965(S&R). SARJ influences LJUMP more than S&R.The model explains 83.8% (R squared) of the variance in LJUMP.The data and statistical results presented support the idea that a practical and effective talent selection model can be formulated for the athletic long jump event. The model has immediate practical application and the theoretical framework and statistical procedures involved can be employed to construct talent selection models for other athletic or sports events