The application of a multi-dimensional assessment approach to talent identification in Australian football.

This study investigated whether a multi-dimensional assessment could assist with talent identification in junior Australian football (AF). Participants were recruited from an elite under 18 (U18) AF competition and classified into two groups; talent identified (State U18 Academy representatives; n = 42; 17.6 ± 0.4 y) and non-talent identified (non-State U18 Academy representatives; n = 42; 17.4 ± 0.5 y). Both groups completed a multi-dimensional assessment, which consisted of physical (standing height, dynamic vertical jump height and 20 m multistage fitness test), technical (kicking and handballing tests) and perceptual-cognitive (video decision-making task) performance outcome tests. A multivariate analysis of variance tested the main effect of status on the test criterions, whilst a receiver operating characteristic curve assessed the discrimination provided from the full assessment. The talent identified players outperformed their non-talent identified peers in each test (P < 0.05). The receiver operating characteristic curve reflected near perfect discrimination (AUC = 95.4%), correctly classifying 95% and 86% of the talent identified and non-talent identified participants, respectively. When compared to single assessment approaches, this multi-dimensional assessment reflects a more comprehensive means of talent identification in AF. This study further highlights the importance of assessing multi-dimensional performance qualities when identifying talented team sports.

Discriminating talent-identified junior Australian football players using a video decision-making task.

This study examined if a video decision-making task could discriminate talent-identified junior Australian football players from their non-talent-identified counterparts. Participants were recruited from the 2013 under 18 (U18) West Australian Football League competition and classified into two groups: talent-identified (State U18 Academy representatives; n = 25; 17.8 ± 0.5 years) and non-talent-identified (non-State U18 Academy selection; n = 25; 17.3 ± 0.6 years). Participants completed a video decision-making task consisting of 26 clips sourced from the Australian Football League game-day footage, recording responses on a sheet provided. A score of "1" was given for correct and "0" for incorrect responses, with the participants total score used as the criterion value. One-way analysis of variance tested the main effect of "status" on the task criterion, whilst a bootstrapped receiver operating characteristic (ROC) curve assessed the discriminant ability of the task. An area under the curve (AUC) of 1 (100%) represented perfect discrimination. Between-group differences were evident (P < 0.05) and the ROC curve was maximised with a score of 15.5/26 (60%) (AUC = 89.0%), correctly classifying 92% and 76% of the talent-identified and non-talent-identified participants, respectively. Future research should investigate the mechanisms leading to the superior decision-making observed in the talent-identified group.

The use of skill tests to predict status in junior Australian football.

This study examined whether skill tests were predictive of status in junior Australian football. Players were recruited from the 2013 under 18 (U18) West Australian Football League competition and classified into two groups: elite (state U18 squad representative; n = 25; 17.9 ± 0.5 years) and subelite (nonstate U18 squad representative; n = 25; 17.3 ± 0.6 years). Both groups completed the Australian football kicking (AFK) and Australian football handballing (AFHB) tests, assessing kicking accuracy/ball speed and handballing accuracy on dominant and nondominant sides. A multivariate analysis of variance (MANOVA) modelled the main effect of "status", whilst logistic regression models were built for the predictive analysis using the same test parameters. Between-group differences were noted across all parameters, with the combination of kicking accuracy and ball speed on the dominant and nondominant sides being the best predictor of status for the AFK test (wi = 0.25, AUC = 89.4%) and the combination of accuracy on the dominant and nondominant sides being the best predictor of status for the AFHB test (wi = 0.80, AUC = 88.4%). The AFK and AFHB tests are predictive of status, suggesting that their use is warranted as a means of talent identification in junior Australian football.

Predicting playing status in junior Australian Football using physical and anthropometric parameters.

OBJECTIVES: To use physical and anthropometric parameters to predict playing status in junior Australian Football. DESIGN: Cross-sectional observational. METHODS: Participants were recruited from the under 18 competition within the West Australian Football League and classified into two groups; elite (state representative; n=50; 17.9 ± 0.5 y; 184.8 ± 6.9 cm; 80.6 ± 9.4 kg) and sub-elite (non-state representative; n=50; 17.8 ± 0.6 y; 179.8 ± 5.4 cm; 74.4 ± 7.9 kg). Both groups completed physical/anthropometric tests inclusive of a 5 m, 10 m and 20 m sprint, an agility test, stationary vertical jump, dynamic dominant and non-dominant foot vertical jump, 20 m multistage fitness test, standing height and body mass. A multivariate analysis of variance was used to test the main effect of 'status' on the physical/anthropometric parameters, whilst logistic regression models were used to predict playing status using the physical/anthropometric parameters. RESULTS: On average, the elite group were taller, heavier, had a greater stationary vertical jump, dynamic dominant and non-dominant foot vertical jump and higher maximal aerobic capacity as measured by the multistage fitness test (p<0.05). The combination of standing height, dynamic vertical jump non-dominant foot and the 20 m multistage fitness test were the strongest predictors of status (Akaike's Information Criterion=96.35). CONCLUSIONS: Despite mean differences in a number of parameters, the combination of standing height, dynamic vertical jump non-dominant foot and the multistage fitness test were the strongest predictors of status and thus important tests for initially identifying potential talent in junior Australian Football.