ArticlePloS one2019
Comparing subjective and objective evaluations of player performance in Australian Rules football.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Implementation of a Decision Support System to Enhance Movement Proficiency Assessment in Sport.Journal of functional morphology and kinesiology · 2025Article
- Challenges and solutions to talent (de)selection and development in a youth soccer academy: the implementation of a multidisciplinary athlete profiling tool.Frontiers in psychology · 2025Article
- Coaching styles and sports motivation in athletes with and without Intellectual Impairments.PloS one · 2023Article
- Age at Nomination Among Soccer Players Nominated for Major International Individual Awards: A Better Proxy for the Age of Peak Individual Soccer Performance?Frontiers in psychology · 2021Article
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Authors and funding
3 authors.
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Abstract
Player evaluation plays a fundamental role in the decision-making processes of professional sporting organisations. In the Australian Football League, both subjective and objective evaluations of player match performance are commonplace. This study aimed to identify the extent to which performance indicators can explain subjective ratings of player performance. A secondary aim was to compare subjective and objective ratings of player performance. Inside Football Player Ratings (IFPR) and Australian Football League Player Ratings were collected as subjective and objective evaluations of player performance, respectively, for each player during all 1026 matches throughout the 2013-2017 Australian Football League seasons. Nine common player performance indicators, player role classification, player age and match outcomes were also collected. Standardised linear mixed model and recursive partitioning and regression tree models were undertaken across the whole dataset, as well as separately for each of the seven player roles. The mixed model analysis produced a model associating the performance indicators with IFPR at a root mean square error of 0.98. Random effects accounting for differences between seasons and players ranged by 0.09 and 1.73 IFPR each across the five seasons and 1052 players, respectively. The recursive partitioning and regression tree model explained IFPR exactly in 35.8% of instances, and to within 1.0 IFPR point in 81.0% of instances. When analysed separately by player role, exact explanation varied from 25.2% to 41.7%, and within 1.0 IFPR point from 70.3% to 88.6%. Overall, kicks and handballs were most associated with the IFPR. This study highlights that a select few features account for a majority of the variance when explaining subjective ratings of player performance, and that these vary by player role. Australian Football League organisations should utilise both subjective and objective assessments of performance to gain a better understanding of the differences associated with subjective performance assessment.
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