AFL team performance and expenditure: Is it how much money your club

spends, or how they spend it, that matters?**

Initial version: December 14, 2013

This version: February 3, 2014

Jeff Borland*

Department of Economics

University of Melbourne

Ross Booth

Department of Economics

Monash University

Abstract

This study examines the relation between spending by Australian Football League (AFL)

clubs and their performances from 1994 to 2011. Differences in football spending between

AFL clubs are found to be related to the number of games that their teams win and whether

they make finals or win the premiership – but only in recent years. The case of the AFL is

shown to fit neatly into the international literature on the effects of spending on performance

of sporting teams: Similar to other competitions where the labour market is highly regulated,

we find that the role of clubs’ spending in explaining variation in teams’ performances is

relatively small. A potential criticism of salary cap mechanisms is addressed and rebutted by

showing that ‘undoing’ of the cap on player payments in the AFL via growing differences in

spending on other dimensions of football operations has been limited. Our study also

suggests that it is important to recognise that clubs’ performances depend on other influences

apart from how much they spend – such as how well they spend their money. Improving

competitive balance should therefore take account of equalising those other influences.

*Corresponding author: Jeff Borland; jib@unimelb.edu.au

**In constructing the data set on club spending we are grateful for assistance from Brad

Potter and Matt Pinnuck, Shane McCurry and Rob Macdonald. Some of the data we use in

the paper is proprietary to the Australian Football League. We are grateful to Dean Pagonis

for research assistance and to Rob Macdonald for helpful discussions. The opinions

expressed in the paper are those of the authors only.

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1.Introduction

Understanding what explains the performance of sporting teams and competitors is a major

topic of interest for sports economists. One line of research has examined the relation

between performance and the amount of money spent by teams (for example, Hall et al., 2002;

Szymanski, 2003; Jones, 2013). The idea that spending matters for team performance is

implicit in regulations that sporting leagues impose on clubs’ expenditure in order to promote

competitive balance – such as the salary cap and luxury tax.

This study examines the relation between spending by Australian Football League (AFL)

clubs and their performances from 1994 to 2011. The AFL is notable for having had a

relatively extensive set of labour market controls since the mid-1980s; including a salary cap

on player payments, a reverse-order draft for recruiting new players and regulations of player

mobility, and a limit on the size of each club’s playing list. Our study uses several alternative

measures of team performance – seasonal winning percentage, and whether a team makes the

finals or wins the premiership. We are also able to examine different measures of spending

by clubs – a measure of total football spending as well as the disaggregated categories of

spending on player salaries and on football operations.

Our study makes several contributions. First, it provides an additional data point to the cross-

country analysis of the effect of spending on performance of sporting teams. Previous studies

have, for example, used cross-country variation in the strength of relation between spending

and performance to make inferences on how labour market regulations affect the

determinants of performance of sporting clubs. However, these studies have been confined to

the US and Europe. Hence an observation from a sporting league in Australia can give extra

power for identifying the determinants of performance. Second, it contributes to debate on

the effectiveness of salary cap mechanisms. One criticism of using a salary cap to achieve

competitive balance is that it can be undone by differences between clubs in their spending

on football operations – such as the number and quality of coaches and medical staff hired, or

the quality of training activities and facilities (for example, Fort and Quirk, 1995). By

tracking the relation between clubs’ spending and performance in the AFL since the mid-

1990s, and by separately analysing the effects of total spending and spending only on football

operations, we are able to evaluate whether the AFL salary cap is being undone by clubs’

spending on football operations. This issue is currently of considerable relevance in the AFL

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where there has been substantial debate about the effect of an ‘arms race in spending’ on

competitive balance and the adequacy of existing equalisation policy (for example, Niall,

2012; Quayle, 2013; Baker, 2014).

In our study we do find evidence that spending by AFL clubs matters for their performance –

how many games they win, and whether they make the finals or are premiers. However, this

relation only becomes significant in the final years of our sample period, from 2009 to 2011.

As well, the proportion of the variation in performance between clubs that is explained by

differences in their spending is relatively small. This is in line with international studies

which find that differences in spending between clubs matter less for performance in leagues

where there is more extensive labour market regulation. Our findings suggest that regulations

such as salary caps can be relatively effective over extended periods in ensuring equalisation

of spending and hence competitive balance between clubs. They also inform the suggestion

in the title of our paper: that how clubs spend their money may be as important as how much

they spend for understanding their performance.

An outline of the paper is as follows. Section 2 describes the main elements of labour market

regulation in the AFL. Section 3 describes the data we use in the study. Section 4 presents

descriptive statistics on spending by AFL clubs between 1994 and 2011. Section 5 presents

the results from analysis of the relation between clubs’ spending and their performances.

Section 6 provides concluding thoughts.

2. Labour market regulations in the AFL

The Australian Football League (AFL) is the premier Australian rules football competition.

It currently includes 16 clubs from the five major states in Australia, having evolved from the

Victorian Football League (VFL) competition in 1990. The structure of the competition

involves teams competing in a set of regular season (home-and-away) matches, after which a

finals (playoff) series involving the top-ranked clubs from the regular season determines the

winner of the league Premiership.

In the mid-1990s a variety of labour market controls were introduced into the VFL

competition as a response to a combination of problems that had arisen in the Australian

football competition in the early 1980s. These problems centred around the issue of

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competitive balance – and included financial instability of the VFL and its clubs, escalating

and unsustainable player salaries and transfer fees, declining match attendances, and several

challenges to the legality of the VFL’s labour market controls.

A salary cap on player payments for each club was introduced for the 1985 season and

remains in place today - At the end of our sample period in 2011 the cap was $?? per club. A

reverse-order player draft was introduced in 1986 with players chosen then being eligible to

play for clubs in the 1987 season. Initially the scope of the player draft was restricted, but

within a few years assignment of new players to clubs had come to occur almost exclusively

through that mechanism. The capacity of players to move between clubs and the timing of

moves is also highly regulated in the AFL. For example, in the period covered by our study

players who were contracted to a club could only move to another club with the agreement of

their current club, and that move could only occur between seasons; and the medium of

exchange for a trade was limited to other players or choices in the next season’s player draft.

The size of a club’s playing list, was set at a maximum level of 50 players in 1983, and has

subsequently been adjusted downwards to the current maximum of 40 players (plus the

‘emergency’ rookie list players). (For more details on labour market regulations in the AFL,

see Booth, 2006; Macdonald and Booth, 2007; and Borland et al., 2009).

3. Data

Data used in this study are on AFL clubs’ spending and their performances. From a variety

of sources (the AFL and AFL media releases) we have been able to construct measures of

football spending by AFL clubs from 1994 to 2011. We have a measure of total football

spending by each club; and we also have separate series for its components: player payments

and for football operations spending. Player payments are the salaries paid to a clubs’

playing list. Spending on football operations include items such as payments to coaching,

fitness and medical staff, player recruitment costs, and other team expenditure such as travel

costs, medical expenses and team maintenance. We exclude one club, Fitzroy, from the

analysis because we only had data on it for one year out of the period from 1994 to 1996 in

which it was in the AFL competition. We also exclude the Gold Coast club from our study as

it is only in our sample period for one year (2011). As well, missing data for prior years

mean we are only able to include Fremantle in our sample from 1997 onwards. The effect of

these exclusions on our sample is minor – We have data for 281 out of the potential 288

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observations. Data on clubs’ winning percentages in home-and-away matches, and whether

they make the finals and win the premiership, are taken or calculated from AFL (2012). To

have a definition of ‘making finals’ that consistent across time, we apply the rule from the

end of our sample period, and in each year define a team to have made the finals if it finished

the regular season in the top eight on the AFL ladder.

4. The amount of spending by AFL clubs

Trends in average spending

Figure 1 shows the average real spending by AFL clubs from 1994 to 2011 (expressed in

constant 2011 dollars). Total football spending increased from $5.9m to $17.2m over the

period, an average increase of about 6.5 per cent each year. Spending on football operations

increased at much the same rate, 6.7 per cent per annum, from $2.3m to $6.8m.

Differences in spending between clubs

Figure 2 shows the relative spending by the top four and bottom four spending clubs in each

year from 1994 to 2011. In recent years total football spending by the top four clubs has been

about 25 per cent higher than the bottom four clubs. Due to the salary cap restriction on

player payments, there is greater scope for football operations spending to vary between clubs.

Hence, it is not surprising that the gap between the top four and bottom four clubs in football

operations spending has been higher – about 60 per cent. Interestingly, these spending gaps

have been relatively constant over the past decade – that is, there is no evidence of an

increasing difference in spending between the top four and bottom four clubs. The same

result is obtained using other measures of dispersion, such as the coefficient of variation. In

the 1990s, if anything, it appears that spending differences between the top and bottom

spending clubs actually declined.

Who are the high and low spending clubs?

There has been a relatively high degree of stability in the identity of the high and low

spending clubs. One perspective on this issue is available from Figure 3 which shows the

rank-order in total football spending for eight selected clubs. The persistence in identities of

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high and low spending is evident. For example, Collingwood, Sydney and West Coast are in

the top six spending clubs in every year between 1994 and 2011; whereas at the other end of

the spectrum, the Western Bulldogs, and over the last decade Melbourne and the North

Melbourne Kangaroos, were in the bottom six spending clubs in every year. An alternative

perspective is from Figure 4 which shows the year-to-year correlation in clubs’ rank-order in

total football spending. Especially over the past decade the correlation has been very high –

at 80 to 90 percent.

4. The effect of spending on team performance

Methodology

Our empirical method to examine the relation between spending by AFL clubs and their

teams’ performances is straightforward. We estimate a linear model for the relation between

a measure of team performance and a club’s spending relative to average spending:

it it itPERF = + RELSPEND + α β ε (1)

itPERF is a measure of the performance of club i in year t, and itRELSPEND is the ratio of

spending by club i in year t to average spending by clubs in that year.

We use three alternative measures of team performance – seasonal winning percentage in

home-and-away matches; whether a club made the finals in that year; and whether it won the

premiership in that year. The relation between clubs’ performances and their total football

spending and spending on football operations is tested. The relation is tested for the whole of

our sample period and within three sub-periods: 2006-11, 2000-05 and 1994-99, chosen to be

of equal length.

Spending and winning percentage

We begin by examining the relation between AFL teams’ seasonal winning percentages and

their clubs’ relative total football spending. The results are reported in Table 1. Beginning

with the whole period from 1994 to 2011 (column (1)) there is a significant relation between

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a club’s relative total spending and its winning percentage. However, by looking at the sub-

periods (columns (2) to (4)) it is evident that this effect is driven entirely by the period after

the mid-2000s. For 1994-99 and 2000-05 the relation between club spending and winning

percentage is not significant. It is only for 2006-11 that a significant relation exists. In that

period, by increasing its spending relative to the average by 10 percent, a club’s winning

percentage would have been higher by 6.8 percentage points. For example, this means that in

2011, increasing its expenditure by about $1.15m would be associated with a club winning

one more match.

The idea that the relation between club spending and performance has grown stronger over

time is reinforced by looking at graphs of average spending and performance of clubs for

each of the sub-periods. Figures 5a to 5c show this information using measures of total

football spending and average games won by each club. In 1994-99 and 2000-05 the

observations are relatively clustered and there is no clear relation between spending and

games won; but in 2000-11 a positive relation between spending and games won is apparent.

It is also possible to investigate in some more detail how the relation between team spending

and performance has changed across time by breaking up the final sub-period. Doing this

(columns (5) and (6)) shows that in fact the significant relation between team spending and

performance is only observed at the very end of the sample period – from 2009 to 2011.

The other aspect of our analysis of seasonal winning percentage is to examine its relation to

football operations spending. These results are reported in Table 2. The findings are

qualitatively the same as when total football spending is used. There is a significant relation

between clubs’ spending on football operations and their teams’ performance over the whole

sample period. However, this is again entirely due to there being a significant relation at the

end of the period. Taking into account that a given percent rise in spending on football

operations relative to the average is only about one-third the amount of money as the same

percent rise in total football spending, it seems that the effect of spending an extra dollar on

football operations is about the same as spending an extra dollar on player salary payments.

Spending and the finals

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Having found that clubs’ spending affects the percentage of games they win during the home-

and-away season, it follows that spending is also likely to affect whether a club makes the

finals and whether it wins the premiership. In Table 3 we report the findings from estimating

our basic model with these alternative dependent variables and clubs’ relative total football

spending as the explanatory variable.

The same pattern of a relation between performance and spending that strengthens over time

is apparent. In the initial sub-period from 1994-99 there is no significant relation between a

club’s total football spending and whether its team makes finals or wins the premiership. But

by the final sub-period , 2006-11, an increase in a club’s total football spending had a

significant effect on its team’s performance. For example, having total football spending that

was 10 percent higher relative to the average raised the probability of a club making the finals

by 23 percentage points and raised the probability of winning the premiership by 7.6

percentage points. In fact, the association between clubs’ spending and making the finals or

winning the premiership becomes statistically significant in the second sub-period from

2000-05. Hence differences in clubs’ spending have a significant effect on these measures

before there is found to be a significant effect on clubs’ winning percentages. Perhaps this is

because making the finals and winning the premiership are coarser measures of club

performance than seasonal winning percentage.

How much of differences in AFL teams’ performances are explained by differences in clubs’

spending ?

So far it has been found that differences in spending between AFL clubs – at least in recent

seasons - are a factor that can explain differences in their teams’ performances. The next

logical question to ask is how much of the overall differences in performance between AFL

teams can be explained in this way. The answer is a relatively small proportion.

As one ‘back-of-the-envelope’ perspective on this issue, consider the relation between clubs’

total football spending and their winning percentages. In 2011 the difference between the

highest and lowest spending clubs relative to average spending was about 25 percent. Using

the result on the effect of relative spending on winning percentage (Table 1, column (2)) this

translates into a difference in winning percentage of 17 percentage points. In that season the

actual difference in winning percentage between the top four and bottom four clubs was

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about 68 percentage points. Hence, in this way, differences in total football spending can be

interpreted to explain about one-quarter of the total gap in winning percentage between top

and bottom teams.

An alternative, and more rigorous and comprehensive, perspective on the explanatory power

of clubs’ spending is to use the R-squared measure from our regression models. Table 4

reports the R-squareds from regression models for the relation between the alternative

measures of football spending by clubs and their teams’ winning percentages. The main

impression is that this percentage explained by differences in football spending is relatively

minimal. Even in the period where differences in spending have their greatest impact on

clubs’ performance, 2006-11, those differences are only able to explain 5 to 9 per cent of the

variation in winning percentage between clubs.

That differences in spending between clubs explain a relatively small proportion of the

variation in winning percentage is a common finding in sporting leagues with a relatively

high degree of labour market regulation. To make this point Table 5 contrasts the findings

for the AFL with similar analyses for the NFL in the US and the Premier League in the UK

reported in Szymanski (2003). In both the AFL and the NFL, which have a high degree of

labour market regulation, the proportion of the variation in winning percentage between clubs

that is explained by differences in their spending is small – about 5 percent. By contrast, in

the Premier League, where there is much less labour market regulation, differences in clubs’

spending explain about one-third of variation in the percentage of games won.

In a way this conclusion on the limited role of differences in spending in explaining the

performance of AFL teams should not be surprising. In this study it has been found that the

identity of high and low spending clubs did not change much from 1994 to 2011. Yet we

also know that there has been a relatively high degree of ‘churning’ in teams’ performances

over that period. Figure 6 reports some information to support this point. It shows the

number of times that each AFL club made the finals in the six-year periods during 1994-2011.

There is shown to have been a relatively high degree of turnover in the identify of clubs

making finals – for example, in each six-year period at least have the clubs made the finals on

between two and four occasions. In each period there were also four different clubs that won

the Premiership. Comparing between the periods it does not seem that there was any trend to

less churning in the more recent periods. Putting together these pieces of information – that

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there has been consistency in the ordering of football spending by AFL clubs, but churning in

the ordering of finishing position - it follows that relative football spending by AFL clubs

cannot be the only factor explaining teams’ performances.

Which clubs get the most out of their money and which clubs get least?

Since differences in clubs’ spending can explain only a small proportion of the variation in

their teams’ performances, there must be other factors, such as management (for example,

quality of coaching, recruiting and medical staff) and luck (for example, injuries), that also

have a large effect. We refer to the influence of these other factors as the ‘effectiveness’ of

clubs’ spending, and we next derive a measure of this effectiveness.

Calculating the measure of the effectiveness of clubs’ spending is done in several steps. First,

a team’s predicted performance based on its spending by its club can be calculated. This

calculation is done using data on clubs’ spending and the estimated relation between that

spending and teams’ performances. To do this step we use seasonal winning percentage as

the performance measure and total football spending as the spending measure (Table 1,

columns (2) to (4)). Second, a team’s actual performance can be compared to its predicted

performance. Where a team’s actual winning percentage is above its predicted winning

percentage, this means that the club is doing better than would be predicted by its spending.

In other words, it is being relatively effective in using its money. By contrast, where a team’s

actual winning percentage is below its predicted winning percentage, the club is doing worse

than is predicted by its spending. It could be said to be relatively ineffective in using its

money.

Tables 6 and 7 report the findings from this analysis of relative effectiveness of clubs’

spending. Table 6 shows the three clubs whose actual seasonal winning percentage was

above and below their predicted levels by the largest margins. Table 7 provides a complete

picture by showing the rank-ordering of each club. A rank of ‘1’ means that the club was the

most effective in its spending, having the biggest positive difference between actual and

predicted performance; whereas a rank of ‘16’ means that the club was the least effective in

its spending, having the biggest negative difference between actual and predicted

performance. Both tables distinguish between the three six-year sub-periods from 1994 to

2011.

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What is striking about the findings is the extent of churning in the relative effectiveness of

spending by clubs. Looking at Table 6, for example, no club appears in the list of top three

clubs for more than one of the six year sub-periods; and two clubs (Western Bulldogs and

Essendon) shift between being in the lists of top three and bottom three clubs in successive

time periods (moving in opposite directions). This finding is reinforced by Table 7. There

are only two clubs that have been in the top half of clubs for the relative effectiveness of their

spending in all three sub-periods: Geelong and the Kangaroos. Equally, only one club has

been in the bottom half of clubs for relative effectiveness of spending in all three time periods

(Fremantle; although Melbourne and Collingwood feature in very low positions in two of the

time periods).

Why would there be so much churning in clubs’ effectiveness in spending? There are several

possible explanations. One explanation is that the effectiveness of clubs’ spending may be

constrained by institutions such as the reverse-order player draft. Clubs are all required to

spend relatively similar amounts on player salaries, yet their access to talent will vary

according to the reverse-order draft. Clubs that have done well in previous seasons will have

had lower draft choices, with higher draft choices going to clubs that have not done well.

Hence the reverse-order feature of the player draft causes variation over time in clubs’ access

to talent that may to some degree be reflected in variation in the effectiveness of clubs’

spending. This would be consistent with cycling in the relative effectiveness of spending on

player payments. But it cannot account for why the effectiveness of spending on football

operations would vary across time. Therefore there must also be other explanations. A

second explanation might be the influence of luck - such as incidence of injuries. To the

extent that injuries play an important part in determining teams’ performances, and that the

relative incidence of injuries at clubs varies across time, this could explain why the relative

effectiveness of football spending shows churning. A third explanation may be club

management. Clubs that are well-managed and coached are likely to do better than predicted

on the basis of how much they spend; and vice-versa for clubs that are not well-managed and

coached. However, if the quality of management and coaching are to explain the differences

in the relative effectiveness of spending, then given the observed churning in the relative

effectiveness of spending, it must be that there has been churning in the relative quality of

management and coaching.

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5. Conclusions and implications for policy

This study has examined the relation between spending by AFL clubs and their teams’

performances between 1994 and 2011. Total football expenditure by high spending AFL

clubs is about 25 percent higher than low spending clubs. With the salary cap governing

player payments in the AFL, this difference is mainly driven by spending on football

operations, which is about 60 percent greater at high than low spending clubs. This gap in

expenditure between high and low spending clubs is found to have translated into the number

of games that clubs win and whether they make finals or win the premiership – but only in

recent years.

One major implication from our study is to show that the case of the AFL fits neatly into the

international literature on the effects of spending on performance of sporting teams. The

AFL has a high degree of regulation of labour markets, and as with other sporting leagues

with that institutional set-up, we find that the role of clubs’ spending in explaining their

performances is relatively small. The second major implication is that it follows that the

regulations used by the AFL to equalise spending by clubs have indeed prevented differences

in spending becoming a major impediment to achieving competitive balance. Any ‘undoing’

of the salary cap on player payments via growing differences in spending on football

operations has been limited, and has only occurred in recent seasons.

Our study suggests that sporting leagues seeking to improve competitive balance are right to

worry about equalising spending by clubs. It also suggests, however, that it is important to

recognise that clubs’ performances depend on other influences – such as luck or how well

they spend their money. Hence, improving competitive balance may also be about equalising

those other influences.

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References

AFL (2012), AFL Record Season Guide 2012 (Melbourne). Baker, Grant (2014), ‘Pay to Win’, The Herald-Sun, January 28, pages 69,72. Booth, Ross (2006). The economic development of the Australian Football League. In W. Andreff and S. Szymanski (eds.) Handbook on the Economics of Sport (pp.552-64), Cheltenham, UK: Edward Elgar. Borland, Jeff, Chicu, Mark and Robert Macdonald (2009), ‘Do teams always lose to win?: Performance incentives and the player draft in the Australian Football League’, Journal of Sports Economics, 10, 451-84. Fort, Rodney and James Quirk (1995), ‘Cross-subsidization, incentives and outcomes in professional team sports leagues’, Journal of Economic Literature, 33, 1265-99. Hall, Stephen, Stefan Szymanski and Andrew Zimbalist (2002), ‘Testing causality between team performance and payroll: The cases of Major League Baseball and English soccer’, Journal of Sports Economics, 3, 149-68. Jones, Willis (2013), ‘Exploring the relationship between intercollegiate athletic expenditures and team on-field success among NCAA Division I institutions’, Journal of Sports Economics, 14, 584-605. Macdonald, Robert and Ross Booth (2007). ‘Around the grounds’: A comparative analysis of football in Australia. In B. Stewart (ed.) The Games Are Not the Same: The Political Economy of Football in Australia (pp.236-331), Carlton, Australia: Melbourne University Publishing. Niall, Jake (2012), ‘$7.8M jackpot’, The Age, December 5, pp.23-24. Quayle, Emma (2013), ‘AFL to consider luxury tax’, The Age, January 31, pp.15-16. Szymanski, Stefan (2003), ‘The economic design of sporting contests’, Journal of Economic Literature, 41, 1137-87.

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Figure 1: Average real spending by AFL clubs, 1994 to 2011 (expressed in 2011 dollars)

Figure 2: AFL, Ratio of spending by top 4 clubs to bottom 4 clubs, 1994 to 2011

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Figure 3: Rank-order of total football spending, Selected AFL clubs, 1994 to 2011

Figure 4: Correlation in rank-order of spending by AFL clubs, 1994 to 2011

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Table 1: Relation between seasonal winning percentage and relative total football

spending

Dependent variable: Seasonal winning percentage in home-and-away matches

(1) (2) (3) (4) (5) (6)

Whole period

Sub-periods

1994-2011 2006-11 2000-05 1994-99 2009-11 2006-08

Relative Total Football Spending

0.375** (0.109)

0.686** (0.225)

0.379 (0.209)

0.178 (0.144)

0.958** (0.331)

0.453 (0.309)

R-squared 0.040 0.089 0.033 0.016 0.153 0.044

Observations 284 96 96 92 48 48

Note: ** and * respectively denote significance at the 1% and 5% levels.

Table 2: Relation between seasonal winning percentage and relative football operations

spending

Dependent variable: Seasonal winning percentage in home and away matches

(1) (2) (3) (4) (5) (6)

Whole period

Sub-periods

1994-2011 2006-11 2000-05 1994-99 2009-11 2006-08

Relative Football Operations Spending

0.147** (0.054)

0.235* (0.106)

0.017 (0.108)

0.065 (0.073)

0.266 (0.165)

0.211 (0.140)

R-squared 0.025 0.049 0.025 0.008 0.053 0.047

Observations 284 96 96 92 48 48

Note: * and ** respectively denote significance at the 1% and 5% levels.

Table 3: Relation between making the finals and winning the premiership and relative

total football spending

(1) (2) (3) (4) (5) (6)

Dependent

variable

Make

finals

Win

premiership

2006-11 2000-05 1994-99 2006-11 2000-05 1994-99

Relative Total Football Spending

2.307** (0.550)

1.288* (0.562)

0.682 (0.466)

0.764** (0.279)

0.811** (0.266)

0.303 (0.231)

R-squared 0.157 0.052 0.023 0.073 0.089 0.018

Observations 96 96 92 96 96 92

Note: ** and * respectively denote significance at the 1% and 5% levels.

P a g e | 17

Figure 5a: Average total football spending and average games won per season by AFL

clubs, 1994 to 1999

Figure 5b: Average total football spending and average games won per season by AFL

clubs, 2000 to 2005

AdelaideBrisbane

Carlton

CollingwoodEssendon

Fremantle

Geelong

Hawthorn

Kangaroos

Melbourne

RichmondSt.Kilda Sydney

Western Bulldogs

West Coast

0

2

4

6

8

10

12

14

16

18

20

0 1 2 3 4 5 6 7 8 9 10

Av

era

ge

Ga

me

s W

on

Pe

r S

ea

son

, 1

99

4-9

9

Average Total Football Spending, 1994-99 ($million; 2011 dollars)

Adelaide

Brisbane

Carlton

Collingwood

Essendon

Fremantle

Geelong

Hawthorn

KangaroosMelbourne

Port Adelaide

9St.Kilda

Sydney

Western Bulldogs

West Coast

0

2

4

6

8

10

12

14

16

18

20

8 9 10 11 12 13 14 15 16 17 18

Av

era

ge

Ga

me

s W

on

Pe

r S

ea

son

, 2

00

0-0

5

Average Total Football Spending, 2000-05 ($million, 2011 dollars)

P a g e | 18

Figure 6: Average total football spending and average games won per season by AFL

clubs, 2006 to 2011

Table 4: Proportion of inter-club variation in games won per season explained by club

spending, 1994 to 2011

Proportion of

variation in total

games won

explained by:

1994-2011 2006-11 2000-05 1994-99

Total Football Spending

0.040 0.089 0.033 0.016

Football Operations Spending

0.025 0.049 0.025 0.008

Adelaide

BrisbaneCarlton

Collingwood

Essendon

Fremantle

Geelong

Hawthorn

Kangaroos

Melbourne

Port AdelaideRichmond

St.Kilda

SydneyWestern Bulldogs

West Coast

0

2

4

6

8

10

12

14

16

18

20

10 11 12 13 14 15 16 17 18 19 20

Av

era

ge

Ga

me

s W

on

Pe

r S

ea

son

, 2

00

6-1

1

Average Total Football Spending 2006-11 ($million, 2011 dollars)

P a g e | 19

Table 5: Relation between expenditure and performance, International comparison

League α β WPCσ WPC*σ RWσ R-

squared Period Obs

AFL 0.12 0.38 0.180 0.106 0.096 0.04 1994-2011

285

NFL (US) 0.19 0.31 0.19 0.13 0.13 0.05 1989-2000

350

Premier League (UK)

0.33 0.19 0.11 0.08 0.34 0.34 1974-99

339

Note: α and β are as defined in equation (1). WPCσand WPC*σ

are respectively the SD of

winning percentage and the ideal SD for each competition. RWσis the SD of total spending in

each competition.

Sources: AFL – Calculations by authors; NFL and Premier League are from Table 1 in

Szymanski (2003).

Figure 6: Number of times AFL clubs made finals, 1994-2011

0

1

2

3

4

5

6

0 1 2 3 4 5 6

Nu

mb

er

of

AFL

clu

bs

Number of times made finals

1994-99

2000-05

2006-11

P a g e | 20

Table 6: Clubs’ actual relative to predicted winning percentage, 1994 to 2011

2006-11 2000-05 1994-99

Top 3 clubs Geelong Port Adelaide Kangaroos

St.Kilda Brisbane Carlton

Western Bulldogs Essendon West Coast

Bottom 3 clubs Brisbane Carlton Collingwood

Melbourne Collingwood Fremantle

Essendon Western Bulldogs Melbourne

Table 7: Clubs’ actual relative to predicted winning percentage, Rank-order of

performance, 1994 to 2011

2006-11 2000-05 1994-99

Adelaide 7 5 13

Brisbane 16 2 9

Carlton 10 16 2

Collingwood 5 15 16

Essendon 14 3 4

Fremantle 12 11 15

Geelong 1 7 6

Hawthorn 4 10 12

Kangaroos 6 4 1

Melbourne 15 6 14

Port Adelaide 9 1 10

Richmond 13 13 7

St.Kilda 2 12 8

Sydney 8 8 11

Western Bulldogs 3 14 15

West Coast 11 9 3

Note: 1 = Best performance relative to spending; 16 = Lowest performance relative to spending.