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Multifactorial Benchmarking of Longitudinal Player Performance in the Australian Football League.


ABSTRACT: This study aimed to develop a model to objectively benchmark professional Australian Rules football (AF) player performance based on age, experience, positional role and both draft type and round in the Australian Football League (AFL). The secondary aims were to identify the stage of peak performance and specific breakpoints in AF player performance longitudinally. AFL Player Ratings data were obtained for all players (n = 1052) from the 1034 matches played during the 2013-2017 seasons, along with data pertaining to the abovementioned player characteristics. Two separate linear mixed models revealed that all factors influenced player performance, with age and experience the strongest in each model, respectively. Post hoc Tukey tests indicated that performance was affected by age at each level up until the age of 21 (effect ranging from 0.98 to 3.70 rating points), and by experience at the levels 1-20 and 21-40 matches in comparison to all higher levels of experience (effect ranging from 1.01 to 3.77 rating points). Two segmented models indicated that a point of marginal gains exists within longitudinal performance progression between the age levels 22 and 23, and the experience levels 41-60 and 61-80 matches. Professional sporting organisations may apply the methods provided here to support decisions regarding player recruitment and development.

SUBMITTER: McIntosh S 

PROVIDER: S-EPMC6554430 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Multifactorial Benchmarking of Longitudinal Player Performance in the Australian Football League.

McIntosh Sam S   Kovalchik Stephanie S   Robertson Sam S  

Frontiers in psychology 20190531


This study aimed to develop a model to objectively benchmark professional Australian Rules football (AF) player performance based on age, experience, positional role and both draft type and round in the Australian Football League (AFL). The secondary aims were to identify the stage of peak performance and specific breakpoints in AF player performance longitudinally. AFL Player Ratings data were obtained for all players (<i>n</i> = 1052) from the 1034 matches played during the 2013-2017 seasons,  ...[more]

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