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Leon Corriea | MS-BANA | July 19, 2016 First Reader: Dr. Michael Magazine Second Reader: Dr. Edward Winkofsky An Analysis Of European Soccer Finances And Their Impact On On-field Success CAPSTONE PROJECT

An Analysis Of European Soccer Finances And Their Impact On On-field Success

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Leon Corriea | MS-BANA | July 19, 2016

First Reader: Dr. Michael Magazine

Second Reader: Dr. Edward Winkofsky

An Analysis Of European Soccer Finances And Their Impact On

On-field Success CAPSTONE PROJECT

Abstract

Analytics is revolutionizing every industry it touches. From banking to manufacturing to

healthcare, every industry has been made better, more successful with the use of

analytics. The sports industry has been the latest to embrace analytics. The use of

analytics in sports is often referred to as the “Moneyball revolution”, alluding to the

famous book and movie of the same name.

This report takes a closer look at the business of soccer and how analytics can be used to

improve financial decisions that impact performance on-field. It identifies all the essential

levers that are involved in the financial decision making process at the top European

soccer clubs and, through the use of analytics, assigns importance to each one of them. By

recognizing the most important factors, soccer clubs can prioritize their efforts in

improving those areas that have the maximum impact on on-field success.

PAGE 1

Table of Contents

Introduction .............................................................................................................................. 2

Revenue – All About The Money? ........................................................................................... 4

Transfers – Personnel Matters .................................................................................................. 5

Wages – An Offer You Can’t Refuse ........................................................................................ 8

Infrastructure – Home Advantage ......................................................................................... 10

The Future – Competing On Analytics .................................................................................. 13

Conclusion - Model Interpretation ........................................................................................ 18

Closing Thoughts – The Final Whistle .................................................................................. 19

Appendix .................................................................................................................................20

PAGE 2

Introduction

Leicester City – April 2015 – Bottom of the Premier League and facing immediate

relegation to the Championship (2nd tier of English soccer).

Leicester City – April 2016 – Premier League champions.

It has been a stunning rise for a team that bookmakers had at 5000/1 odds of winning the

league at the beginning of last season. “Football, bloody hell!” Sir Alex Ferguson had

exclaimed when Manchester United dramatically won the Champions League final in

1999 with two late goals scored in injury time. One can only imagine what his reaction

would have been after witnessing Leicester clinch the title last season. It’s safe to assume

it would have been even more intense!

Many people will see Leicester’s rise as a chance occurrence, a once in a lifetime underdog

story that might never be repeated. In statistical terms, this would be an outlier.

However, that would be oversimplifying things and robbing Leicester their due credit. It’s

true – modern sport is competitive and has made it extremely difficult for outsiders to

break the status quo set by traditional heavyweights. Just a glance at the historic trend in

the number of different teams making the top four (the positions that get you a ticket to

participate in the Champions League – Europe’s elite club competition) will give you an

idea how difficult it is to break the mold:

Fig. 1: Unique teams making the top four in previous five seasons1

PAGE 3

The number of different teams making the top four has steadily declined over the past

decades. This means that breaking the stronghold at the top is getting increasingly

harder. This just goes to highlight how much of a feat Leicester City achieved last season

in winning the league.

So how did they do it? It is true that a lot of it was down to the competition not being as

good as it has traditionally been. Chelsea, who won the league the previous season was

flirting with relegation for most of the season and eventually finished 10th, their lowest

finish since 1996, when they finished 11th. Manchester United, who is still struggling to

overcome the retirement of their longest serving manager in Sir Alex Ferguson, finished

5th and outside the Champions League places. Manchester City, who in recent year has

enjoyed a revival because of substantial investment from their Abu Dhabi based owners,

struggled to sustain a challenge and finished 4th. Arsenal, who was top of the league mid-

way through the season, suffered their typical end of the season collapse only to pip

Tottenham to 2nd place on the last day of the season.

Leicester also benefited from playing fewer number of games than its rivals because of not

being part of European cup competitions. They played a total of 43 games last season as

compared to an average of 56.7 games that their rivals played last season. A fewer number

of games meant more recovery time in between games. This resulted in the reduction of

the risk of injuries, with Leicester suffering the lowest number of injuries throughout the

season.2 This also meant that Leicester were able to maintain a remarkable consistency in

their team selection, having used the joint lowest number of players throughout the

season, ensuring that the team chemistry remained intact.3

However, even with all these factors in their favor, there was still a number of things

going against them. Firstly, Leicester was competing against teams with significantly

larger revenues. Secondly, Claudio Ranieri had to operate on a tight transfer budget. In

addition, Leicester has a significantly smaller stadium in comparison to its rivals which

limited its ability to generate revenue. All these factors meant that the club management

had to be smart about allocating its resources. And that’s exactly what they did. Some

intelligent player scouting and addition of talented staff with a strong focus on sports

analytics played its part.

In the following report, I have analyzed data about the most consistent soccer clubs in the

top 5 European leagues and provided an overview of their business operations. I have also

attempted to provide a framework for future strategies to optimize allocation of spending

in order to maximize on-field success.

PAGE 4

Revenue – All About The Money?

Perhaps the single most important goal for a soccer club outside of success on the field is

success off it. Now, traditional businesses define success according to how much profit

they generate. However, the primary goal of the business of soccer is not to make profits,

which is great because most of them don’t! So how do we define success off the field? The

answer is revenue maximization.

Like any other business, soccer clubs need money to keep themselves running.

Optimizing revenue streams is one the most important goals for any soccer club if it

wants to be successful on the field. But to optimize the revenue streams, first we need to

understand how soccer clubs make money. The revenue model of any soccer club can be

typically classified into three main segments: Matchday Revenue, Broadcasting Revenue

and Commercial Revenue.4

Fig. 2: Top ten European clubs by revenue (€m) - Deloitte Football Money League5

As you can see, commercial revenue is the biggest contributor to overall revenue for the

top clubs across Europe. However, some clubs are better at exploiting their commercial

opportunities than others. For example, Arsenal sits at the top of the pile when it comes

to matchday revenue, which is expected because they charge some of the highest ticket

prices in Europe.6

However, when it comes to commercial revenue, Arsenal is lagging behind their other

rivals by quite a margin. This indicates that there is certainly room to improve there.

PAGE 5

Transfers – Personnel Matters

After soccer games, the thing that gets fans most excited about their clubs is their transfer

activities. Every summer, clubs across Europe clamor to find the best players in the world

and sign them up on long term contracts. In recent times the transfer season has become

an entertainment spectacle in itself with clubs fighting over the best prospects and

looking for bargains. With no soccer action over most of the summer (save for an

international cup tournament every other year), fans need something to satisfy their

soccer appetite. That something is soccer transfers.

Every year soccer clubs spend massive amounts in transfer fees across Europe. Last

summer, the top 5 European leagues spent a whopping €2.93 billion in transfer fees.

Fig. 3: Total transfer spend of top 5 European Leagues7

PAGE 6

Looking at the net spend on transfers over 5 years and average points gained over that

same period, we can see that there isn’t a very strong correlation:

Fig. 4: 5 year net spend (€M) vs. average points in the same period.

Only 4 teams out of the 12 who had a net spend of €100M+ Euros over the 5 years had

average points of 85+ which is considered to be the threshold for winning the title in

many of the European leagues.8 One of them, Paris St-Germain spent a whopping €492M

in that period, which is a big price to pay for a winning a tournament that pays a paltry

€44.6M in prize money.

However, winning isn’t always about the return on investment. It’s about creating an

image of success that attracts more fans (paying customers) as well as the best players in

the world. It’s about developing a globally recognizable brand and in that regard, PSG is

doing a really solid job.

Another reason transfers are important is because they help boost revenues. Commercial

revenues usually skyrocket immediately after a club signs a star player as fans throng to

the club shops to purchase merchandise. Ticket sales also see a boost as fans are eager to

see their shiny new player in action. When Real Madrid paid a then world record fee of

€94M for Cristiano Ronaldo in 2009, they were almost immediately able to recoup their

investment from shirt sales with his name on it.9

However, year on year we see that clubs end up buying expensive players who end up

being complete flops.10 This has turned soccer transfers into an expensive gambling

business and has resulted in a transfer market that is extremely inefficient.

PAGE 7

As Liverpool legend Jamie Carragher says in his excellent autobiography ‘Carra’, “As I

know to my cost at Anfield, having money is no guarantee of success. The skill is spending it

on the right players.”

So how do clubs optimally use the money that is available to them apart from signing new

players? One way to do it is to make smart buys. As Simon Kuper and Stefan Szymanzki

opine in their book ‘Soccernomics’ – “Any inefficient market is an opportunity for

somebody. If most clubs are wasting most of their transfer money, then a club that spends

wisely is going to outperform.” Brian Clough did it in his time as the manager of

Nottingham Forest, Arsène Wenger did it in his first decade as Arsenal manager and even

Olympic Lyon were known to pick up unknown players and turn them into star

performers. Leicester City is probably the most well-known out of the recent set of clubs

that have taken to unearthing hidden gems from lesser known leagues. Signings such as

Jamie Vardy, Riyad Mahrez and N’Golo Kante, whose combined transfer fee was less than

€10M, were instrumental in them winning the league last season. Southampton is

another example of a club that has been punching above its weight in recent times thanks

to smart buys in the transfer market.

PAGE 8

Wages – An Offer You Can’t Refuse

An alternative to signing expensive stars for millions of euros is paying existing players

competitive wages. In contrast to transfers, which can be either hit or miss, with existing

players, you have the advantage of having seen them play for a certain duration. This

means that when you negotiate a contract with a star player that involves a substantial

raise in their salary, you have a fair idea of what you are paying for. Indeed, there is a

stronger correlation in the average number of points gained and the average weekly

wages per player in European soccer as shown below:

Fig. 5: Average annual salary (€M) vs average points.

Offering lucrative contracts can also be used as a tool to attract players by clubs that

traditionally may not be very attractive to players. One great example is the French club

Paris St-Germain (PSG). The club has been relatively successful in its brief history but was

lagging behind its European competitors until its takeover by the Qatar Sports

Investments group in 2011. Since then, the club has been on a spending spree, purchasing

the biggest names in Europe. However, PSG plays its soccer in the French Ligue 1 which is

the lowest ranked among the top 5 European leagues.11 Players want to win trophies but

they also want to play against the best players in the world and in the most competitive

leagues. So how did PSG manage to attract and retain their star players? They did that by

offering sky high wages.

PAGE 9

The table below shows the average wage per player paid by the top 10 European clubs last

year. PSG’s wages were even higher than the traditional heavy-weights Real Madrid and

Barcelona.

Fig. 6: Average annual salary per player (€M)

However, not every club has the backing of an extremely rich investor and can afford to

pay crazy amounts of money to its players. That’s where good investment strategies that

balance smart transfers with competitive wages come into play. In general, it is better to

raise the pay of your leading players than to risk losing them and having to go out and

purchase replacements.

PAGE 10

Infrastructure – Home Advantage

As mentioned earlier in the report, one of the three main sources of revenue for a soccer

club is matchday revenue. This includes revenue from ticket sales, food and hospitality.

This is generally money earned from fans of the soccer club who attend the matches on a

regular basis.

Having a large stadium is the first step in increasing matchday revenue. The figure below

shows the 5 year average revenue against the stadium capacity for the top European

clubs. We can see that almost all the clubs that recorded an average revenue of greater

than €100M over the past five years have a stadium capacity larger than 35,000. The only

exception is Southampton, which has a great youth academy and has an excellent record

at generating additional revenue from selling their best players at huge transfer fees.

Fig. 7: 5 year average revenue (€M) vs. stadium capacity

Of course, only having a large stadium is not enough. The facilities also need to be up-to-

date. This enables the clubs to charge a premium for good seats. Arsenal FC, who moved

to their brand new 60,000 capacity Emirates Stadium in 2006, charges some of the

highest ticket prices in Europe and still manages to sell out on a regular basis.12

This phenomenon is highlighted very clearly in France, who hosted the recently

concluded Euro 2016 international soccer tournament. A number of Ligue 1 stadiums

underwent renovations and new ones were constructed in order to host the matches in

PAGE 11

this tournament. As a result, the league has shown a steady increase in attendances over

the past three years as shown below:

Fig. 8: Average attendance figures across the top 5 leagues in Europe

However, they still lag substantially behind La Liga, Bundesliga and the Premier League

which indicates that there is room for improvement.

The importance of world class facilities is highlighted by the low attendances in Serie A.

The top clubs in Serie A play in some of the largest stadiums in Europe. Average stadium

capacity for the top clubs in second only to La Liga.

Fig. 9: Average stadium capacity by league

PAGE 12

However most of these stadiums are old and dilapidated.13 Hence fans decide to stay

away. Recently, there have been some signs of revival, with Juventus building their own

stadium and clubs like Roma and Milan unveiling plans for new stadiums in the near

future, Serie A seems to be on the right track.14

The more the number of games a team plays at home, the more matchday revenue it

generates. Typically, clubs only play a fixed number of games at home in the league.

However, clubs can increase the number of home games they play in a season by

progressing further in cup competitions and hoping for a home draw. For clubs playing in

the Champions League, progressing to the knockout phases guarantees at least one

additional home game because of the two-legged nature of the tournament. The further

they progress, more home games get added. More revenue means a bigger budget for

transfers and wages. Hence success on the field is tied to success off it.

PAGE 13

The Future – Competing On Analytics

The future of soccer, as with any sport lies in efficient use of analytics. European soccer is

going through somewhat of a ‘Moneyball’ revolution. Teams are increasingly using

advanced analytics for even marginal gains. Data capture companies such as Opta and

Prozone are making a fortune collecting data and selling their services to the clubs. The

clubs themselves are investing heavily in analytics. Arsenal acquired the sports analytics

company StatDNA in 2012 which helps the club in scouting and talent identification,

game preparation, post-match analysis and gaining tactical insights.15 The City Football

Group which owns Manchester City, New York City, Melbourne City and Yokohama

Marinos has signed a multi-year partnership with German software giant SAP to assist

them with their analytical needs.16 Leicester City, winners of the Premier League last

season, has an entire team of analysts dedicated to Sports Science, Performance Analysis

and Recruitment.

As Billy Beane, general manager of the Oakland A's and the star of ‘Moneyball’, said: "The

idea that I should trust my eyes more than the stats, I don't buy that because I've seen

magicians pull rabbits out of hats and I know that the rabbit's not in there." Data however,

are not meant to replace intuition. There is a reason soccer managers at the top clubs are

some of the highest paid employees. Their experience is something that can’t be

discounted. Analytics should be seen as a tool; something that can be used in conjunction

with intuition in order to make solid footballing decision.

This brings me to the original problem statement – how can we use analytics in order to

optimize the way all these elements work together in order to maximize on-field success?

There are a number of ways in which to approach this problem. I decided to look at it

from a modeling perspective, using correlations and linear regression in order to build a

model that best describes on-field success using off the field performance metrics.

The Data:

The data for this analysis were collected from a number of different sources and collated

together since it is not readily available in a centralized system on the internet. I decided

to focus on the top 5 European soccer leagues for this analysis (England, Spain, Germany,

France and Italy). Since the objective was to identify the successful clubs and observe

what they are doing right, I decided to focus only on the top 10 clubs in each league. The

top 10 clubs were identified on the basis of the average points gained over the past 5 years

in their respective leagues. Once these clubs were identified, I collected a number of data

points on each club such as their UEFA coefficient (a system used by the European soccer

governing body to rank clubs), current valuation (€M), 5 year average revenue (€M), 5

year net spend on transfers (€M), Average salary per player per year (€M), 5 year average

attendance at home games, stadium capacity and social media following. These metrics

PAGE 14

were essential in understanding how the club is performing off the field. For example, the

valuation and revenue are indicative of the overall financial health of the club, the net

spend indicates how well or poorly the club has performed in the transfer market, the

salary indicates how well the club is paying their players and the ROI they are getting in

terms of on-field performance and the attendances and social media following shows how

well the fans are engaged with the club.

The Model:

I started with loading the data in R and doing some exploratory data analysis (EDA). First

I plotted the correlation matrix:

Fig. 10: Correlation matrix for the variables

As you can see, the club value, revenue and average salary are highly correlated with

average points gained. A club’s ability to pay good wages is also dependent on the

revenue it generates as is visible from the high correlation with salary.

PAGE 15

Having a good fan following is also crucial to generating revenue as indicated by the high

correlation between social media following, average attendances and revenue.

Next, I checked for linearity between the dependent and independent variables by

plotting them using scatter plots. This is to ensure that a linear model is the best fit for

this data:

Fig. 11: Plots of Average Points vs Net Spend, Average Salary and Average Attendance

PAGE 16

The next step was to check that the dependent variable was normally distributed. This

was done by plotting a histogram of the dependent variable. As you can see, the data are

fairly normally distributed:

Fig. 12: Histogram of average points

Next, I split the data into two subsets – a training set and a testing set. I used stepwise

model selection in both directions to find the best model based on AIC. This suggested a

model that retained the UEFA coefficient, revenue and social media following as the

independent variables and left out the others. However, I was more interested in

understanding the impact of Net Spend, Salary and Attendance on the performance since

these are factors that the clubs have much more control over. Hence I selected a final

model that included Average points as the dependent variable and Net Spend, Average

Salary and Average Attendance as the independent variables. The model summary is

given below:

PAGE 17

Note that as per our earlier hypothesis, the salary plays a significant part in explaining the

on field performance. Hence we can conclude that if there’s one thing that the clubs have

to prioritize in order to improve on field performance, it would be to optimize the wage

bill.

After fitting the model, I used the testing set to test the validity of the model and got a

good fit. The MSE and MAE are in reasonable range:

Observing the plots, the residuals vs fitted do not seem to show any pattern and the Q-Q

plot suggests that they are normally distributed:

Fig. 13: Plots from the regression model

MSE MAE

Training Set 51.8 5.2

Test Set 66.4 6.8

PAGE 18

Conclusion - Model Interpretation

At the beginning of the report, we analyzed a number of off-the-field parameters that

affect the performance on-field. We looked at how revenue, transfer spending, salary and

infrastructure play a part in explaining a soccer club’s on-field success. We also

hypothesized, based on our preliminary analysis, that salary plays an important part in

explaining performance, since it’s almost always better to retain your existing players

than going out and purchasing replacements. After analyzing the output from the model,

it is clear that our hypothesis was accurate. With a p-value of 0.00341, the coefficient for

average salary is significant at α = 0.01. This means that the average salary is a very good

predictor of on-field success.

In conclusion, if a soccer club is interested in increasing its likelihood of success and has

to decide between recruiting new players, increasing salary or improving infrastructure,

according to the model, the decision makers should prioritize improving salaries as that

would provide the biggest uplift in performance.

PAGE 19

Closing Thoughts – The Final Whistle

It is clear to see that data and analytics, if used correctly can be a great tool for soccer

club management. Even with a simple correlation and linear regression, we were able to

uncover some good insights from the data we had at our disposal. This is just one of the

applications of analytics in the field of sports. A number of clubs have started investing

heavily in the field of analytics to eke out even the most marginal gains in performance.

Everything from player scouting, to strength and conditioning to injury prevention and

even nutrition is being touched by analytics. The day doesn’t seem too far away when a

soccer club wins a championship and it’s the analysts who take the plaudits instead of the

star players!

PAGE 20

Appendix

References:

1. http://fivethirtyeight.com/features/leicester-citys-stunning-rise-in-two-charts/

2. http://www.mirror.co.uk/sport/row-zed/injury-figures-every-premier-league-

7827967

3. http://www.skysports.com/soccer/news/15115/10186258/manchester-united-have-

used-33-players-in-the-premier-league

4. http://www.businessofsoccer.com/2014/02/18/how-do-soccer-clubs-make-money/

5. http://www2.deloitte.com/rs/en/pages/consumer-business/articles/deloitte-

soccer-money-league1.html#

6. http://www.bbc.com/sport/soccer/34531731

7. https://www.onesoccer.com/magazine/summer-transfer-window-2015-analysis/

8. http://www.soccer.co.uk/chelsea/what-will-it-take-to-win-the-

premiership/4617872/#gfMpdZkIBX8lMcH7.97

9. http://metro.co.uk/2010/04/15/cristiano-ronaldo-shirt-sales-have-already-paid-off-

80m-fee-to-manchester-united-real-madrid-claim-242129/

10. http://www.dailymail.co.uk/sport/soccer/article-3225400/Manchester-United-

wasted-money-expensive-flops-Premier-League-joins-throwing-cash-drain.html

11. http://www.uefa.com/memberassociations/uefarankings/country/

12. http://www.mirror.co.uk/sport/soccer/news/price-soccer-study-arsenal-again-

6634479

13. http://www.espnfc.us/italian-serie-a/story/2255044/serie-a-attendance-figures-

continue-to-decline-report-says

14. http://soccertripper.com/7-stadiums-which-could-rejuvenate-serie-a/

15. https://www.theguardian.com/soccer/2014/oct/17/arsenal-place-trust-arsene-

wenger-army-statdna-data-analysts

16. http://www.bbc.com/news/business-33277924

Data:

https://drive.google.com/open?id=1bb_AgsURV8k2Ryof4Pc0wFNRV0cUD4CElzvx

S_iBjZI

R Code:

https://drive.google.com/open?id=1mj__32hj2vjU4gdGxr5obVQJF8IN9zYglaWmi7

UYP3Q