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Understanding the relative contribution of technical and tactical performance to match outcome in Australian Football

Authors:	Christopher M Young Wei Luo Paul B Gastin Daniel B Dwyer

Institution:	1. Centre for Sport Research, Deakin University, Geelong, Australiac.young@deakin.edu.auhttps://orcid.org/0000-0001-6615-1950;3. School of Information Technology, Deakin University, Geelong, Australia;4. La Trobe Sport and Exercise Medicine Research Centre, La Trobe University, Melbourne, Australia;5. Centre for Sport Research, Deakin University, Geelong, Australia

Abstract:	ABSTRACT The aim of this study was to assess if tactical and technical performance indicators (PIs) could be used in combination to model match outcomes in Australian Football (AF). A database of 101 technical PIs and 14 tactical PIs from every match in the 2009–2016 Australian Football League (AFL) seasons was merged. Two outcome measures Win-loss and Score margin were used as dependent variables. The top 45 ranked technical and tactical PIs from a feature selection process were used to model match outcome using decision tree and Generalised Linear Models (GLMs). Of the top 45 selected features, this included seven tactical PIs. The Win-loss-based Decision tree model achieved a classification accuracy of 89.0% and GLM 93.2%. A Score margin-based GLM achieved a root mean squared error (RMSE) of 6.9 points. A combined approach to the classification of match outcomes provided no improvement in model accuracy compared with previous literature. However, this study has established the relative importance of technical and tactical measures of performance in relation to successful team performance in AF.

Keywords:	Decision Support Techniques tactical Analysis performance Analysis team Sport team Structure modelling data Mining

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