Woods, Carl T.E., Raynor, Annette J., Bruce, Lyndell, and McDonald, Zane (2014) Technical skill testing predicts status in junior Australian Football. In: Proceedings of the Sixth Exercise & Sports Science Australia (ESSA) Conference and Sports Dietitians Australia (SDA) Update: research to practice. 165. p. 72. From: Sixth Exercise & Sports Science Australia (ESSA) Conference and Sports Dietitians Australia (SDA) Update: research to practice, 10-12 April 2014, Adelaide, SA, Australia.

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Abstract

Currently, it is unknown if technical skill testing is predictive of status in junior Australian Football (AF) despite technical ability being shown to influence success in the game (Sullivan, Bilsborough, Cianciosi et al., 2013). Thus, this study examined if a kicking test could predict and classify status in junior AF. Players were recruited from the 2013 under 18 (U18) West Australian Football League competition and classified into two groups; elite (state U18 representatives; n=25; 17.9 ± 0.5 y) and sub-elite (non-state U18 selection; n=25; 17.3 ± 0.6 y). Both groups completed the Australian Football Kicking (AFK) test, which was designed to assess kicking accuracy and ball speed on dominant and non-dominant sides. The design of the AFK test was initially modelled on the kicking test used within the Australian Football League (AFL) National Draft Combine but was psychometrically adapted for use within this study. A MANOVA modelled the main effect of 'status' (2 levels: elite, sub-elite) on the skill test parameters (kicking accuracy and ball speed on dominant and non-dominant sides), whilst logistic regression models were built using the same test parameters. Bootstrapped receiver operator curves (ROC) were produced to assess the discriminant ability of the predictive model; with an area under the curve (AUC) of 1 representing perfect discriminant power. Between group differences were noted across all test parameters, whilst the full model (combination of kicking accuracy and ball speed on both dominant and non-dominant sides) was the best predictor of status (wi = 0.25, AUC = 89.4%), successfully detecting 84% of the true positives (elite players) and 76% of the true negatives (sub-elite players). The AFK test can be used a means of predicting and thus classifying elite junior AF players, warranting its use as a means of sports specific talent identification in junior AF.

Item ID:	39720
Item Type:	Conference Item (Poster)
ISBN:	978-0-9873065-8-6
Related URLs:	Organisation
Date Deposited:	03 Nov 2015 04:41
FoR Codes:	01 MATHEMATICAL SCIENCES > 0104 Statistics > 010401 Applied Statistics @ 10% 11 MEDICAL AND HEALTH SCIENCES > 1106 Human Movement and Sports Science > 110603 Motor Control @ 20% 11 MEDICAL AND HEALTH SCIENCES > 1106 Human Movement and Sports Science > 110699 Human Movement and Sports Science not elsewhere classified @ 70%
SEO Codes:	92 HEALTH > 9299 Other Health > 929999 Health not elsewhere classified @ 100%
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