AN ANALYSIS OF TEAM STATISTICS IN AUSTRALIAN RULES FOOTBALL. Andrew Patterson and Stephen R. Clarke 1. Abstract 1. INTRODUCTION

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1 AN ANALYSIS OF TEAM STATISTICS IN AUSTRALIAN RULES FOOTBALL Andrew Patterson and Stephen R. Clarke 1 Abstract Champion Data has collected Australian Rules Football player statistics since the beginning of the 1996 AFL season. As the data is collected from video replays, the statistics show more detail than those previously published, with the quality and effectiveness of possessions and disposals also being recorded. The statistics include short and long kicks, effective handballs, contested and uncontested marks, hard and loose ball gets, gathers, free kicks and clangers. The data have been analysed to determine the contribution of each factor to the game outcome. The ultimate aim of the investigation is to provide a scientific underpinning for a player rating system. 1. INTRODUCTION The game of Australian Rules Football has been around for over a century and is regarded as one of the most popular sports in the country. The 1997 AFL season involved 16 teams who competed against each other with each team playing a total of 22 matches during the home and away season. Although a finals series was conducted at the end of the season this paper only investigates data from the home and away matches. During the 1997 season, each match took place on one of 11 grounds across the country. Each ground has a centre square marked as well as a semicircle of radius 50 metres around the two goal lines at each end of the ground. Each team had a designated home ground on which they played between nine and 15 games for the season. A side could use 21 players for a match with 18 players being allowed on the ground at any time. Matches are played over four quarters with each quarter lasting about 30 minutes. At the end of each quarter the two teams exchange scoring ends. Australian Rules Football is high scoring compared to other team sports. The ball is moved around the ground by methods of kicking or punching, and with no offside rule the game is played at a fast pace. A goal is worth six points and a behind is worth one point. For the 1997 AFL season the average winning score was 16 goals 10 behinds, 106 points with the average losing score being 10 goals 8 behinds, 68 points. 1 School of Mathematical Sciences, Swinburne University of Technology, Hawthorn 3122.

2 Andrew Patterson and Stephen R. Clarke Champion Data has collected the data since the beginning of the 1996 AFL season. The statistics for each match are recorded using two people, one reading out the play and the other entering the relevant information into a laptop computer. In 1997 there were 36 designated statistics that were grouped into three categories - disposals, possessions and attack. For the first time these statistics measured the quality of possession and disposal. For example, kicks were rated as clangers, ineffective, and effective short and long kicks, according to team rules commonly used in clubs. Some of the definitions of these variables are given in Table 1. This paper looks at team totals for some of the more important variables, with a view to determining the importance of each variable to the outcome of the game. The competition statistics have been progressively broken down with respect to team, result and opposition. Fisk [1] performed a similar analysis using team data from the American National Basketball Association. Table 1 Definitions of main player performance statistics. Variable Code Category Definition Kick Long KKL Disposal A kick of more than 40 metres to a 50/50 contest or better for the team Kick Short KKS Disposal A kick of less than 40 metres that results in an uncontested possession for the team Kick Ineffective KKI Disposal A kick of less than 40 metres to a contest or a kick of more than 40 metres to a worse than 50/50 contest for the team Kick Clanger KKC Disposal A kick under little or no pressure that goes straight to an opponent Handball Effective HBE Disposal A handball to a team mate that hits the intended target to the team s advantage Handball Clanger HBC Disposal A handball under little or no pressure that goes straight to an opponent Handball Received HBR Possession When a player takes possession of the ball via a handball and a clean disposal follows Loose Get LBG Possession When a player picks up a disputed ball that has spilled onto the ground and a clean disposal follows Hard Get HBG Possession When a player picks up a disputed ball that has spilled onto the ground in a pressure situation and a clean disposal follows Mark Uncontested MKU Possession When a player takes a mark unopposed Mark Contested MKC Possession When a player marks under pressure or in a pack Inside-50 I50 Attack When a player takes or delivers the ball inside the 50 metre area in the team s attacking half Score SCR Attack The total number of points scored by the team 238

3 An analysis of team statistics in Australian Rules football 2. COMPETITION DATA In 1997 the average number of disposals per match for each team was 266. The competition averages for each of the six methods of disposal is given in Table 2. Kicking is the most common form of disposal with teams averaging twice as many kicks as handballs. Long kicks are performed on more than twice as many occasions as short kicks with clanger/ineffective kicks and handballs (junk disposals) counting for about 15% of all disposals. Table 2 Competition disposal statistics for the 1997 season. Variable 1997 Competition % Disposal Average Kick Long Kick Short Kick Ineffective Kick Clanger Handball Effective Handball Clanger Total In order for a player to effect a disposal, he must first gain possession of the ball. Since a possession nearly always results in a disposal, the totals of these two categories should always be about the same. The statistics show that football is evenly divided between gaining and retaining possession with about 50% of possessions being won in a contest situation and the other 50% coming from uncontested play. 3. TEAM DATA In 1997 Carlton averaged the most disposals per match and Melbourne averaged the fewest of the 16 teams in the competition. Table 3 lists the number of disposals each team averaged per match in 1997 as well as the breakdown of each method of disposal. Adelaide and North Melbourne averaged the most effective long kicks while Melbourne and Collingwood averaged the least. The Western Bulldogs had more effective short kicks than any other side and Richmond had the fewest. Carlton, Hawthorn and Essendon averaged a large number of effective handballs while North Melbourne was well below the competition average. The two South Australian sides, Adelaide and Port Adelaide averaged the fewest number of junk disposals for the season. The percentage breakdown of disposal methods shows the different styles of play used by each team. Adelaide and North Melbourne were long kicking teams that rarely handballed. Collingwood, West Coast and the Western Bulldogs all had high short kick to long kick ratios while Melbourne and Hawthorn were more likely to use handball as a form of disposal. 239

4 Andrew Patterson and Stephen R. Clarke Table 3 Breakdown of the average number of team disposals per match. Team Total KKL % KKS % HBE % Junk % Adelaide Brisbane Carlton Collingwood Essendon Fremantle Geelong Hawthorn Melbourne North Melbourne Port Adelaide Richmond St.Kilda Sydney West Coast Western Bulldogs Average COMPETITION DATA BY RESULT In 1997 the team that had the most number of disposals in the game won seventy-five percent of all matches. The difference in the average number of disposals between winning and losing teams as well as the percentage of teams that win given that they outnumber the opposition in a particular disposal method are shown in Table 4. Table 4 Differences between winning and losing team s disposal averages. Variable Winner Loser Difference % Win Kick Long Kick Short Kick Ineffective Kick Clanger Handball Effective Handball Clanger Total

5 An analysis of team statistics in Australian Rules football On average the winning side had 26 more disposals than the losing side. This included 10 more effective long kicks, 10 more effective short kicks and 7 more effective handballs. The winning side averaged 11% more effective long kicks, 23% more effective short kicks and 9% more effective handballs than the losing side. Effective long kicks were the best predictor of a match result with 83% of teams who had the majority of effective long kicks in a match winning. 5. TEAM DATA BY RESULT In 1997 the average side had an extra 10 more effective long kicks when they won compared to when they lost. Table 5 shows the difference and percentage difference comparisons of each team s win/loss averages. The percentage difference is calculated as the increase in percentage between the winning and losing averages. The values that are the most distant from the competition averages are of the most interest because it is these figures that can reflect a team s strength or weakness. Essendon and West Coast had the biggest differences between win/loss averages of any club for effective long kicks with Essendon averaging an additional 24 long kicks and West Coast an extra 22 when they won. Brisbane were up 57% on effective short kicks when they won whereas Western Bulldogs had about the same number of short kicks when they won as when they lost. West Coast averaged 17 more effective handballs when they won whereas teams such as Hawthorn, Melbourne and the Western Bulldogs all averaged more handballs when they lost than when they won. Team Table 5 Differences between team s winning and losing averages. KKL KKS HBE Diff %Diff Diff %Diff Diff %Diff Adelaide Brisbane Carlton Collingwood Essendon Fremantle Geelong Hawthorn Melbourne North Melbourne Port Adelaide Richmond St.Kilda Sydney West Coast Western Bulldogs Average

6 Andrew Patterson and Stephen R. Clarke 6. OPPONENT EFFECTS It is possible to see how the opposition performs against each team in order to get a better understanding of the characteristics of a particular side. Table 6 shows the difference between winning and losing opponents against each team for the 1997 season. Teams that beat Brisbane and Richmond averaged about 19 more effective long kicks than teams that lost to these two clubs. This can be compared with the average difference of 10. Teams that beat Essendon averaged 4 less effective long kicks than the teams that lost. Teams that defeated Brisbane, Melbourne, Sydney and West Coast all averaged a lot more effective short kicks than the teams that were beaten by these sides. Teams that beat North Melbourne averaged slightly less short kicks than the teams that lost. Teams that beat Collingwood, Melbourne and Richmond had a higher handball average than the teams that lost to them. Teams that beat North Melbourne and St.Kilda handballed a lot less than the sides who lost to them. Table 6 Differences between winning and losing opponent s averages against each team. Team KKL KKS HBE Diff %Diff Diff %Diff Diff %Diff Adelaide Brisbane Carlton Collingwood Essendon Fremantle Geelong Hawthorn Melbourne North Melbourne Port Adelaide Richmond St.Kilda Sydney West Coast Western Bulldogs Average

7 An analysis of team statistics in Australian Rules football 7. ZONE PROFICIENY Because the data records whenever the ball enters a team s attacking or defending 50-metre zone, it is possible to determine the proficiency of each team in certain areas of the ground. The ground has been divided into three zones with the proficiencies of each zone measured in the following way Midfield - Ratio of a team s inside-50 and the opposition s inside-50. Forward Line - Ratio of a team s score and a team s inside-50. Back Line Ratio of the opposition s inside-50 and the opposition s score. Table 7 - Ranking of Zone Proficiencies. Team % Position Midfield Forward Back Adelaide St.Kilda Geelong Sydney North Melbourne Collingwood West Coast Brisbane Western Bulldogs Carlton Essendon Fremantle Port Adelaide Hawthorn Richmond Melbourne Table 7 shows the zone proficiency rankings for all teams in each of the three zones. Although the AFL Ladder ranks teams on their number of wins, Clarke [2] has shown that percentage is a better indicator of overall team performance. The teams have been listed in their percentage order for the 1997 season. It is interesting to note that the correlation between percentage position and the midfield proficiency ranking is high. The only anomaly appears to be Fremantle who finished 12th on percentage order but had a high midfield ranking of 6. The forward and back line proficiency rankings are not highly correlated with finishing order. Essendon and Hawthorn who finished 11th and 14th on percentage order had the 3rd and 4th most proficient forward lines and Adelaide who had the highest percentage of any team was rated as 13th. The back line rankings were more highly correlated than the forward line rankings but still not significant. St.Kilda who finished 2nd on percentage, was rated as having the 10th best back line in the competition. 243

8 Andrew Patterson and Stephen R. Clarke 8. REGRESSION ANALYSIS OF TEAM DATA Table 8 Summary of regression analysis of score difference versus factor difference. Variable Coefficient p-value R-Sq. Kick Long % Kick Short % Kick Ineffective % Kick Clanger % Handball Effective % Handball Clanger % Table 8 gives the results of an individual regression analysis performed on each method of disposal with the score difference. Kick Long, Kick Short and Handball Effective were all found to be good predictors of score with their corresponding p-values being close to zero and the R 2 being reasonably high. Ineffective kicks, Kick Clangers and Handball Clangers were all found to be poor predictors of score with all of these variables having high p-values and a low R 2 value. The above coefficients do not change drastically if a multiple linear regression is performed. If all of the disposal methods are regressed together with the score difference an R 2 value of 66.0% is obtained. The kick long regression coefficient of 1.89 implies that a team would expect to be in front of their opposition by about 2 points for every extra long kick that they had in a match. If a side had 10 more long kicks than their opposition for the game then the estimate of their winning margin would be 10 x 1.89 = 18.9 points. The data suggests that long kicks are worth about one and a half times a short kick and that handballs are worth half a short kick as far as the score difference is concerned. 9. CONCLUSION There is a wealth of performance statistics that can be analysed in various ways to determine the bearing that these statistics have on the result of a match. Clearly different teams have different playing profiles and these become more evident when the data is broken down into more detail. Kicks are the most important predictor of match result with effective long kicking seemingly being the key to a team s success. If a handball were to be rated as one point, short kicks would be rated as about two points and long kicks three points. This result could form the basis of a player performance rating system in Australian Rules Football. REFERENCES [1] Fisk C.J., NBA regular season team statistics versus winning. A univariate/multivariate exploratory analysis. ASA 1996 Proceedings of the Section on Statistics in Sport, 1996, p [2] Clarke S.R., How fair is the AFL draw?, Mathematics and Computers in Sport, N de Mestre, Editor, Bond University: Gold Coast, 1998 (submitted) 244