Biology of Sport
eISSN: 2083-1862
ISSN: 0860-021X
Biology of Sport
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1/2012
vol. 29
 
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abstract:

Original paper
ANTHROPOMETRIC AND STRENGTH CHARACTERISTICS OF TENPIN BOWLERS WITH DIFFERENT PLAYING ABILITIES

R. Razman
,
J.P.G. Cheong
,
W.A.B. Wan Abas
,
N.A. Abu Osman

Biol. Sport 2012;29:33-38
Online publish date: 2014/08/22
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The primary purpose of this study was to investigate the strength and anthropometric characteristics

of elite and semi-elite tenpin bowlers as compared to non-bowlers, and to establish whether it was possible to

discriminate playing level through selected predictor variables. Elite and semi-elite bowlers were distinguished by

their bowling score average (BSave), with participants scoring 200 pin falls and above assigned to the elite group.

Eighteen elite bowlers (M=10, F=8; BSave 213.2±6.80), 12 semi-elite bowlers (M=7, F=5; BSave 181.3±9.36)

and 33 sedentary university students (M=14, F=19) were recruited. Anthropometric measurements were taken

and isometric arm strength was recorded. Between-group differences were identified through a two-way ANOVA,

while discriminant analysis was used to predict group membership. For anthropometric characteristics, the results

indicated that the elite bowlers were heavier, had longer lower leg and hand length and had a wider arm span

as compared to the non-bowlers. The elite group also had stronger forearm/wrist internal rotation compared to

non-bowlers. In addition, the male elite group were stronger than the non-bowling group for arm flexion. There

appeared to be a 54% success rate for predicting group membership from selected anthropometric and strength

discriminating variables, with forearm/wrist internal rotation strength being the best discriminating variable. It is

suggested that coaches should benefit by selecting larger built bowlers with long limbs. Furthermore, bowlers

could potentially gain by paying extra attention to increasing the strength levels of forearm/wrist internal rotators

and arm flexors during training. These findings also provide normative data for elite and semi-elite bowlers.
keywords:

bowling, prediction, discriminant analysis

 
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