Assessing Player Performance in Australian Football Using Spatial Data
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ASSESSING PLAYER PERFORMANCE IN AUSTRALIAN FOOTBALL USING SPATIAL DATA Karl Jackson A thesis presented for the fulfillment of the requirements for the degree of Doctor of Philosophy at Swinburne University of Technology 2016 Abstract This thesis creates a new method for assessing player performance in Aus- tralian football, specifically for an application to the Australian Football League (AFL). Data have been captured by Champion Data as the official statistics provider to the AFL since 1999. More than 100 event types are recorded for each game, such as possessions, disposals, tackles and goals. Up to 50 variables are avail- able to describe the context, quality and location of such events. A full investigation of this information was performed to extract relevant traits of the data, and to improve on existing methods of analysis and available knowledge within the industry. Two outcomes of this exploratory analysis were a visual representation of data through the use of heatmaps, and a new measure for kicking ability called 'kick rating'. Heatmaps have been used by AFL clubs since 2008 as a way of communicating information to players and extracting information about team and player tactical traits. Kick ratings have been used by AFL clubs since 2011 as a development tool for their own players, and for scouting of opposition players. The data were also compiled into a player performance measure (`Eq- uity Ratings'), where the spatial locations of each event acted as a basis for evaluation. For each event, the rating system calculates the equity of the player's team before and after the event to measure the objective contribution that the event made to a team's position. i Players who consistently improve the position of their team are rewarded with a large positive rating. Worsening the position of the team results in a negative rating. In this manner, the quality of a player's involvements will be considered more important than previous rating systems which placed more emphasis on the quantity of a player's involvements in a game. Equity Ratings proved to be the most comprehensive measure of player performance that has been applied to AFL - showing decreased bias towards midfield players and a higher correlation to match results. A cross-season evaluation of player performance was then compiled to assess long-range per- formance. This combined measure has been adopted by the league as the ‘Official AFL Player Ratings', hosted on the official website of the league (afl.com.au) and through the League's official mobile and tablet apps. ii Acknowledgements I would first like to thank my primary supervisor Denny Meyer for the patience and guidance she showed throughout the completion of this thesis. What was initially planned as a three-year research project eventually stretched across nine years. Stephen Clarke should also be recognised as my original supervisor, whose retirement easily beat me to the finish line. Stephen's link in the early years with Champion Data is the only reason this project was possible through Swinburne, which should also be acknowledged. Most of the AFL team at Champion Data had strong contributions to this research through validity and `footy-smarts' testing of models, development of commercial products and collection of raw data. My parents, Barry and Diane Jackson, also showed great patience and persistence in encouraging completion, even to the point of asking \How is your thesis going?" consistently in the four years that elapsed when I had abandoned the research. Thank you. iii Declaration of Authorship This thesis is presented to fulfil the requirements of a Doctor of Philosophy at Swinburne University of Technology. I hereby declare that this thesis and the work presented in it is entirely my own. No other person's work has been used without due acknowledgement in this thesis. All references and verbatim extracts have been quoted, and all sources of information, including graphs and data sets, have been specifically acknowledged. Karl Jackson April 20, 2016 iv Contents Abstract i Acknowledgements iii List of Figures xi List of Tables xiv Executive Summary xvii Thesis Outline xxii 1 Introduction 1 1.1 Contribution to Knowledge . 1 1.2 Catalyst for Research . 2 1.3 Australian Football . 5 1.3.1 History . 5 1.3.2 Rules and Terminology . 6 2 Literature Review 11 2.1 Maths in Australian Football . 12 2.2 Player Rating Systems . 13 2.2.1 Discrete Sports . 14 2.2.2 Continuous Sports . 15 2.2.3 AFL Player Rating Systems . 16 v 2.2.4 Champion Data Ranking Points . 18 2.2.5 Other Systems . 20 2.3 Expectation . 20 3 Data Overview 22 3.1 Collection Methods & Quality Assurance . 22 3.1.1 Capture Team . 23 3.1.2 Captured Statistics . 25 3.2 Data Structure . 27 3.2.1 Match Information . 27 3.2.2 Possession Chains . 28 3.2.3 Raw Statistics . 29 3.2.4 Enhanced Content . 29 3.3 Data Volume . 31 3.4 Accuracy . 32 3.4.1 Clearances . 33 3.4.2 Tackles . 34 3.4.3 Disposal Efficiency . 34 3.4.4 Possession Type . 35 3.5 Suggestions for Reviewed Quality Control . 35 3.5.1 Accuracy of Recorded Statistics . 35 3.5.2 Caller Bias . 36 3.6 Future Developments . 37 4 Exploratory Data Analysis 38 4.1 Heatmaps . 38 4.1.1 Density Estimation . 38 4.1.2 Implementation . 41 4.2 Spatial Data Traits . 46 4.2.1 Kicking Distance . 46 4.2.2 Next Scorer . 50 vi 4.2.3 Shot at Goal Accuracy . 51 4.3 Kicking Outcomes . 54 5 Field Equity 64 5.1 Calculation . 65 5.2 Discussion . 68 5.2.1 Example 1 - Hardball Get to Teammate's Mark . 69 5.2.2 Example 2 - Hardball Get to Opposition Mark . 69 6 Pilot Study - Equity Ratings 71 6.1 Points Allocation . 71 6.1.1 Special Cases . 72 6.2 Results . 73 6.3 Discussion . 74 6.4 Conclusion . 75 7 Field Equity - Part Two 77 7.1 Smoothed Equity . 77 7.2 Results & Discussion . 79 7.3 Conclusion & Future Developments . 82 8 Player Rating System - Points Allocation 84 8.1 Included Statistics . 84 8.2 Points Allocation . 85 8.2.1 Hitouts . 86 8.2.2 Possessions . 87 8.2.3 Disposals . 89 8.2.4 Run Equity . 92 8.2.5 Free Kicks . 94 8.2.6 Spoils . 94 8.2.7 Pressure . 95 vii 8.2.8 Errors . 96 8.3 Results . 96 8.3.1 Hitouts . 97 8.3.2 Run Equity . 97 8.3.3 Contested Possessions . 98 8.3.4 Disposals . 99 8.3.5 Pressure . 105 8.3.6 Summary . 106 8.4 Discussion and Future Developments . 108 9 Player Rating System 110 9.1 Distribution of Equity Rating Points . 110 9.1.1 Rank Order . 112 9.1.2 Match Result . 113 9.1.3 Player Position . 116 9.1.4 Player Experience . 117 9.2 Equity Rating Source . 118 9.2.1 Possession . 120 9.2.2 Disposal . 121 9.2.3 Hitout . 122 9.2.4 Defensive . 122 9.3 Assessment of Rating System . 123 9.3.1 Comparison of Systems - Match Points . 124 9.3.2 Comparison of Systems - Event Points . 125 9.3.3 Position Bias . 130 9.3.4 Brownlow Medal . 134 9.3.5 Coaches Association Votes . 139 9.3.6 Club Best & Fairest . 140 9.3.7 Correlation with Match Margin . 141 9.4 Conclusion . 143 viii 10 Industry Implementation 145 10.1 Included Games . 145 10.2 Weighting of Games . 148 10.3 Effect of Match Weights . 150 10.3.1 Changes to Overall Standings . 151 10.3.2 Penalty for Games Missed . 154 10.3.3 Rise Through Overall Standings . 156 10.4 Assessment of Overall Standings . 157 10.4.1 Celebrating Gary Ablett . 158 10.4.2 Player Case Studies - Positively Rated . 165 10.4.3 Player Case Studies - Negatively Rated . 170 10.4.4 Conclusion - Desirable Player Traits . 175 10.5 Limitations on Use . 175 10.5.1 Commercial Landscape . 176 10.5.2 Complexity of Calculation . 176 10.5.3 Available Resources . 177 10.5.4 Club Intellectual Property . 182 10.6 Conclusion . 182 11 Additional Uses 184 11.1 Value Above Replacement . 184 11.2 Defensive Rating . 186 11.2.1 Team Effect . 188 12 Discussion and Conclusion 191 12.1 Contributions . 191 12.2 Limitations . 192 12.3 Transferability . ..