The use of player physical and technical skill match activity profiles to predict position in the Australian Football League draft |
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| Authors: | Carl T Woods James P Veale Neil Collier Sam Robertson |
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| Institution: | 1. Discipline of Sport and Exercise Science, James Cook University, Townsville, Queensland, Australia;2. Australian Football League, Melbourne, Australia;3. Faculty of Sustainability, Leuphana University, Luneburg, Germany;4. Institute of Sport, Exercise &5. Active Living, Victoria University, Melbourne, Australia |
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| Abstract: | This study investigated the extent to which position in the Australian Football League (AFL) national draft is associated with individual game performance metrics. Physical/technical skill performance metrics were collated from all participants in the 2014 national under 18 (U18) championships (18 games) drafted into the AFL (n = 65; 17.8 ± 0.5 y); 232 observations. Players were subdivided into draft position (ranked 1–65) and then draft round (1–4). Here, earlier draft selection (i.e., closer to 1) reflects a more desirable player. Microtechnology and a commercial provider facilitated the quantification of individual game performance metrics (n = 16). Linear mixed models were fitted to data, modelling the extent to which draft position was associated with these metrics. Draft position in the first/second round was negatively associated with “contested possessions” and “contested marks”, respectively. Physical performance metrics were positively associated with draft position in these rounds. Correlations weakened for the third/fourth rounds. Contested possessions/marks were associated with an earlier draft selection. Physical performance metrics were associated with a later draft selection. Recruiters change the type of U18 player they draft as the selection pool reduces. juniors with contested skill appear prioritised. |
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| Keywords: | Talent selection predictive modelling notational analytics performance analysis recruiting |
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