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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Main Author:	Tan, Kok Siang
Format:	Thesis
Language:	English English
Published:	2006
Subjects:	Broad jump - Malaysia Athletes - Malaysia
Online Access:	http://psasir.upm.edu.my/id/eprint/205/1/549060_FPP_2006_6.pdf
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id	my-upm-ir.205
record_format	uketd_dc
spelling	my-upm-ir.2052013-05-27T06:46:32Z Development of a Talent Identification Model to Determine the Physical Attributes of Athletes for the Long Jump Event 2006-03 Tan, Kok Siang 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 Broad jump - Malaysia Athletes - Malaysia 2006-03 Thesis http://psasir.upm.edu.my/id/eprint/205/ http://psasir.upm.edu.my/id/eprint/205/1/549060_FPP_2006_6.pdf application/pdf en public masters Universiti Putra Malaysia Broad jump - Malaysia Athletes - Malaysia Faculty of Educational Studies English
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English English
topic	Broad jump - Malaysia Athletes - Malaysia
spellingShingle	Broad jump - Malaysia Athletes - Malaysia Tan, Kok Siang Development of a Talent Identification Model to Determine the Physical Attributes of Athletes for the Long Jump Event
description	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
format	Thesis
qualification_level	Master's degree
author	Tan, Kok Siang
author_facet	Tan, Kok Siang
author_sort	Tan, Kok Siang
title	Development of a Talent Identification Model to Determine the Physical Attributes of Athletes for the Long Jump Event
title_short	Development of a Talent Identification Model to Determine the Physical Attributes of Athletes for the Long Jump Event
title_full	Development of a Talent Identification Model to Determine the Physical Attributes of Athletes for the Long Jump Event
title_fullStr	Development of a Talent Identification Model to Determine the Physical Attributes of Athletes for the Long Jump Event
title_full_unstemmed	Development of a Talent Identification Model to Determine the Physical Attributes of Athletes for the Long Jump Event
title_sort	development of a talent identification model to determine the physical attributes of athletes for the long jump event
granting_institution	Universiti Putra Malaysia
granting_department	Faculty of Educational Studies
publishDate	2006
url	http://psasir.upm.edu.my/id/eprint/205/1/549060_FPP_2006_6.pdf
_version_	1747810173719674880

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

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