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Are football clubs like pieces of art or regular corporations? Empirical
evidence of the market valuation of football clubs in the big five
leagues
Luis Carlos Sancheza, Angel Barajasb,c and Patricio Sanchez-Fernandezc
a Department of Economics, University of Oviedo, Spain
b Deprt. of Finance, National Research University Higher School of Economics, Russia
c Department of Financial Economics, University of Vigo, Spain
This is an Original Manuscript of an article published by Taylor & Francis in “Managing Sport and Leisure”
on 31 May 2022, available at https://www.tandfonline.com/doi/full/10.1080/23750472.2022.2081251 and
https://doi.org/10.1080/23750472.2022.2081251
ABSTRACT
Purpose: The aim of this paper is to determine whether football clubs are valued
according to financial parameters, as in other profit-seeking investments, or
depending on the subjective preference of the buyers, in situations where buyers
seek emotional rewards or a status symbol.
Design: This work analyses a unique data set of the prices of actual transactions
of shares from clubs in the big European leagues from 2001 until 2019. A
theoretical model is presented introducing financial, sporting, and localisation
variables to study their influence in market value.
2
Findings: We have found that the valuation of football clubs in acquisitions is
influenced by financial parameters, as in other profit seeking investments, and
does not depend on the subjective preference of the buyers.
Practical implications: Our findings show the end of the alignment of interests
between new football owners and fans or current organisers of competitions, due
to the preferences of the new investor profit-seekers of an American model of
sport.
Research contributions: The ownership of football clubs in the big leagues has
changed dramatically in the last years. For the first time, to the best of our
knowledge, the present paper demonstrates the opportunity of analysing the
valuations of the football industry with actual data from the transactions.
Keywords: sport economics, football, valuation, firm ownership, sport management,
investment
3
Introduction
European football has gone from being a local sport to a global business. In recent years,
revenues from overseas TV rights have soared, international sponsors have emerged,
continental matches have multiplied, and foreign players have filled squads. Globalisation
has also extended to the ownership of football clubs. Gone are the days where clubs were
controlled by fans or local celebrities. Each year, more clubs fall under the control of
investors, most of them foreigners.
The profile of the owner is related to the objectives of football. Earlier efforts were
focussed on listed football clubs, at a time when various English clubs were listed on the
stock market. However, the ownership of football clubs has changed dramatically since
then, and there is a lack of research about the valuation of privately owned football clubs.
Nowadays, only a few clubs from the main leagues in Europe are listed, and their traded
capital only represents a small percentage. For this reason, their stock exchange price
cannot be considered representative of the market value of the European football clubs.
The motivation to acquire a football club has attracted vigorous debate. Some authors,
such as Leach and Szymansky (2015) and Huth (2019), have pointed out that investors
buy football clubs looking for an emotional reward without economic rationality, as is the
case when buying a piece of art. In this way, Kupers and Szymansky (2015) compared
buying a football club to buying a Picasso. If investors acquire a football club to obtain a
profit, they should estimate the value based on objective economic data. The objective of
this paper is to determine whether the prices paid by the buyers of European football clubs
show economic rationality or a subjective approach. In this way, we will study the value
of the acquisitions of clubs competing in the Big 5 leagues since 2001. Previous research
about the valuation of football clubs presents some limitations. Some of them are outdated
4
given that the strong changes in football ownership in current century, some are based on
journalist estimations instead real price transactions and others are reduced to the few
clubs currently listed. However, earlier studies about American sports clubs were based
on real prices, but they did not consider financial variables.
The present study is relevant because it is based on real price transactions and
information from financial statements. This facilitates studying the objectives of the new
clubs’ owners, and an analysis of the economic rationality of their investments in
European football clubs. This issue has not been previously studied. The results of this
paper are relevant because if new owners are investing in football clubs under economic
parameters and in order to maximise profit, a governance problem would arise. The first
conflict would appear between fans and local communities who had objectives different
from those of the clubs’ new owners. Another conflict would arise with the current
pyramid competition system, given that new investors would prefer a closed system as in
North America.
The rest of the paper is organised as follows. First, it introduces an analysis of the
differences between the valuation of (1) assets linked to emotional rewards as pieces of
art, and (2) financial investments in firms. Second, we review the previous literature about
football clubs' valuation. Next, data analysis is presented which describes the models and
the variables studied. The results obtained are discussed, and, finally, conclusions and
practical implications are presented.
Valuations based on emotional rewards vs financial returns
An old debate exists about the objectives of sports clubs. Some authors, such as El-Hodiri
and Quirk (1971), Fort and Quirk (1995), Vrooman (1995), and Feess and Stähler (2009),
5
have assumed that clubs’ owners aim to maximise capital invested, as in any other
industry. Other authors, such as Szymanski and Kuypers (1999), Morrow (1999), Gerrard
and Dobson (2000), Késenne (2006), Zimbalist (2003), and Ascari and Gagnepain (2006),
have assumed that clubs’ owners look for other non-monetary motivations, usually
emotional rewards that are linked to sporting success. Sanchez et al. (2017) revealed a
new possibility pointing out that the objective of the clubs would depend on the identity
of owners. In this way, some owners would buy a club to obtain profitability from their
investments while others would buy it to obtain emotional satisfaction.
Depending on the aim of buying football clubs’ shares, the valuation of the club
should be different. If the buyer expects financial profitability, the valuation of the equity
would depend on economic factors, as is the case with most investments. If the buyer
expects an emotional reward, the valuation would depend on their personal preferences
as in the case of the art market. Art buyers are examples of agents that do not follow the
behavior in the rational utility theorem, as Schoemaker (1982) and Machina (1987) have
explained.
Investing in art provides low profitability with a high risk (Anderson, 1974;
Agnello & Pierce, 1996; Marinelli & Palomba, 2011; Worthington & Higgs, 2004). For
this reason, Baumol (1986) labelled the art market as a floating crap game. Candela et al.
(2004) maintain that art buyers face uncertainty in the accuracy of the pricing because the
quality is based on aesthetic judgements. These subjective judgements could move prices
depending on art fads among collectors (Buelens & Ginsburg, 1993) or art experts
(Becket & Rössel, 2013). In this way, returns in art markets will depend on future tastes
6
(Chanel et al., 1994), and art investors should thus expect to reap emotional benefits,
rather than high financial returns (Renneboog & Spaenjers, 2013).
In particular, the aesthetic benefit is part of the utility of owning an artwork (Frey
& Eichenb, 1995). Karpik (2010) designated the art market to be one of singular goods
because each is different, and is appreciated differently by each buyer. This could be
applied to football clubs because fans would be interested only in investing in their club,
but not in others.
In cases where the objective of the clubs’ owner would be to obtain economic
returns on their investment, the price paid would be based on financial data, as in most
industries. The most common valuation methods take into account the profitability of the
firms, such as the use of multiples like the price earnings ratio (PER), or the ability to
generate cash flows in the future—discounted cash-flow (DFC) (Kaplan & Ruback, 1995;
Demiakos et al. 2004; Penman & Sougiannis 1998).
Although a firm's valuation is usually linked to its ability to bring cash back to the
investors, cases of companies with a low or negative profitability, but a high valuation,
can be found beyond the football industry. In this way, investing in low-profit industries
is not a sign of not seeking profit, as was indicated by Leah and Szymanski (2015). What
is relevant is not the current profitability, but the potential to generate cash flows in the
future. This is the case of the technology industry where companies are usually considered
overvalued according to traditional earnings ratios (Barlett, 2016; Gompes et al. 2019).
This overvaluation does not mean a lack of financial rationality, unlike in the art
market. In this way, these valuations follow the utility theorem which requires higher
7
returns for greater perceived risk, as Manigart et al. (1997) and Pintado et al. (2007) have
pointed out. Schultz and Zaman (2001) found that individuals investing in Internet firms
really do not think that they are overvalued, although valuations can be considered
optimistic. Schwartz and Moon (2000) noticed that if sales growth rates are high,
valuations can appear abnormally high for the multipliers used. Similarly, Cuming and
McIntosh (2000) noticed that investors in private companies showed strong trust in their
own valuation capabilities. Specifically, the profit-oriented investors paid higher prices
than those with strategic motivations (Röhm et al., 2018). For all this, the valuation of
firms in overvalued industries is not estimated using earnings ratios or cash flow
discounts, but depends on other variables, such as book value (Aggarwal et al., 2009;
Collins et al., 1999) or revenues (Davila & Foster, 2005; Davis, 2002; Sievers et al.,
2013). Thus, the valuation of firms is not homogenous, and depends on the particularities
of the industry and the firms' stage in the business lifecycle.
Football Clubs' Valuation
Previous research on football clubs’ market value was focussed on listed clubs. In the
1980s, English clubs were pioneers in listing their shares on the stock market. Although
it would be thought that clubs could become profit-oriented, Leach and Szymansky
(2015) do not find any variation in the clubs' objectives. It is difficult to know the
motivations of each individual shareholder, but some facts point indicate that fans saw
the Initial Public Offering (IPO) of the clubs as an opportunity to become owners. Morrow
(2003) indicated that the illiquidity of club shares was a sign of the inexistence of real
financial investment, and the presence of fans in the capital of the club. Fans would not
8
be interested in selling their shares whatever happened, unlike financial investors,
because they were more interested in a long-term relationship with the club. Another sign
of the existence of a relation between the evolution of the price of the club shares and the
sporting performance was found by Benkraeiem et al. (2009), Berument et al. (2009), and
Bell et al. (2012). Moreover, Zuber et al. (2005), Gannon et al. (2006), and Tiscini and
Dello Strologo (2016) did not find that financial performance influenced share prices,
unlike in other industries.
Fans do not take into account financial information in their investment decision
making (Zuber et al., 2005), and for this reason, emotions can lead to changes in the share
prices (Demir & Rigoni, 2017). This leads them to consider that emotional benefits should
be used to explain the value of football clubs. This emotional motivation was confirmed
by a survey between actual and potential investors conducted by Huth (2019). Prigge and
Tegtmeir (2019) studied the market valuation and risk of listed football clubs, and
confirmed that they are overvalued according to CAPM. This is analogous to the art
market where buyers do not follow economic rationality.
The listing of football clubs allowed fans to become shareholders with only a few
shares. However, the ownership of European football clubs has changed dramatically.
Currently, only six clubs in the Big 5 leagues out of 98 clubs are listed in stock markets,
and the percentage of capital traded in those six clubs is low. In this way, the market value
of these traded shares cannot be considered as representative of the industry.
Sanchez et al. (2020a) described this transformation in detail with regard to the
ownership of Big 5 leagues. If local celebrities controlled English clubs, and fans bought
9
shares when clubs were listed in the eighties, most of the clubs in the Premier League
currently have foreign owners, and all of them have concentrated ownership. French
football clubs were controlled by fans through member associations in the past.
Nowadays, more than 80% of them have concentrated ownership, and 30% a foreign
owner. If the Spanish football clubs that are companies – which excludes Real Madrid,
Barcelona, and Athletic Club de Bilbao – traded their shares in the stock exchange,
thousands of fans would buy the shares of their clubs. However, half of the Spanish clubs
are controlled by investors currently with concentrated ownership, and many of them are
foreigners. Although Italian clubs were historically associated with local businessmen,
now 20% of the clubs are currently owned by foreigners. Even in the German Bundesliga,
more than 20% of the clubs have a majority owner when all of them were member
associations a few years ago. This process of concentration in ownership is similar in
other industries where investors see an undervaluation of the firms, and they want to catch
all the potential profitability as Weir et al. (2005) and Renneboog et al. (2007) have
pointed out.
This concentration process has brought a new kind of investor into European
football, as institutional investors have withdrawn from listed English football clubs
(Wilson et al., 2013). Prigge and Tegtmeier (2020) distinguished between three kinds of
non-financial investors in football-clubs. These are: strategic investors investing in
football clubs to deepen their relationship with them, as in the case of German clubs as
described by Bühler (2006). Patron investors or sugar daddies are shareholders who
behave as non-profit seeking investors (Andreff, 2007). A third type would be fans
10
participating in ownership of football clubs in the way that Sanchez et al. (2020a) have
described. However, financial investors have not disappeared from football, and many
clubs have been bought by venture capitalist and investment funds. Table 1 shows the
percentage of clubs in 2017/18 with different types of ownership by each of the big
leagues.
INSERT TABLE 1 AROUND HERE
The majority shareholders obtain profits selling control of the clubs, as Fort (2006)
demonstrated in the case of baseball. For instance, the money invested by David Dean in
Arsenal’s shares was branded dead money by the former club chairman Peter Hill-Wood
as if it were akin to the purchase of a luxury car or a piece of art (Moore, 2006). However,
it was a very profitable investment when Dean sold the shares to a foreign investor with
a return of more than 2.56 times. The positive influence of the investment in European
football clubs in the stock prices of Chinese companies observed by Chen et al. (2019)
could point out that investors are looking for profitability instead of emotional benefits as
indicated by previous research.
Previous studies about the valuation of non-listed football clubs were based on
Forbes estimations. Scelles et al. (2013), discovered a relationship between Forbes
valuations and the clubs’ revenues, their sports performance, the domestic competition,
and the size of the population of clubs’ cities. In a subsequent study, Scelles et al. (2016)
noticed that operating income also influenced Forbes' valuations. However, important
differences have been detected between Forbes' estimations of clubs’ value and the price
of real clubs’ transactions as Fort (2006) and Humphrey and Mondello (2008) detected.
11
For this reason, the estimations and Forbes valuations should be treated with caution
because they could provide a better acknowledgement of the methodology of the
magazine but not about the actual clubs’ value.
For this reason, this paper will take into account the actual prices, instead of the
estimations from Forbes as previous works have done. Given that most of football clubs
have been unlisted, the only data about actual market value comes from sales transactions
of shares out of the stock market. On the other hand, Humphreys and Lee (2010) and
Humphreys and Mondello (2008) studied the characteristics of North American clubs
with influence in the real transaction prices, such as local market or facilities, but they did
not include financial data among the independent variables. The present paper not only
includes real transaction prices, but also analyses the influence of the club's financial
situation. This allows us to better explain the clubs’ valuation, and to identify the
motivations of the takeovers as we detailed previously.
Data Analysis
Sample
The present work focusses on the transactions of the shares of clubs from the Big5 leagues
from 2001 until 2019. Our sample is a unique hand-collected dataset that includes the 61
corporate transactions where the price was made public. The source of the data are the
different newspapers and press agencies that reported the transactions (see Annex 1).
Given accounting harmonisation thanks to European Union Regulation No 1606/2002,
12
we believe that there are not significant differences between clubs’ accounts at the level
of detail of the data used.
The English Premier League has been the most active market with 44.3% of the
operations, while only 8.2% of the trades were from Bundesliga clubs. The rest of the
transactions had their origin in Spanish La Liga (18%), French Ligue 1 (16.4%), and
Italian Serie A (13.1%). Most of the transactions (61.7%) were takeovers to obtain
majority control of the clubs. New shareholders joined the club by the issue of new shares
in 21.7% of the cases. During this period, the presence of foreign investors in Big5
leagues had increased as 70% of the buyers were foreigners while 70% of the sellers were
from the country of the club. It is worth remarking that in the case of the Bundesliga, all
transactions were among Germans, and there were no foreign investors.
The English Premier League featured more transactions including foreigners with
81% of the buyers being foreign. The rest of the competitions also presented an important
rise in foreign investors as in the case of the French Ligue 1 (78%), Italian Serie A (75%),
and Spanish La Liga (73%). Obviously, all of these new foreign owners did not have any
emotional link with the clubs. In the case of the rest of the investors, we cannot rule out
that many of them also had no link. The transactions of our sample are the cause of the
change in the landscape of the ownership of European football with more concentrated
ownership, and the emergence of foreigner owners, as explained by Sanchez et al.
(2020a). Table 2 presents all the transactions of a relevant number of shares in the Big5
leagues from 2000 until 2019.
INSERT TABLE 2 AROUND HERE
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Description of the models and variables
The study performs analysis using Ordinary Least Squared (OLS) regression on the
market value (MV) of the Big5 leagues clubs, based on the price in the transactions of big
packages of football clubs' shares since 2000. The price is expressed in Euros and adjusted
for inflation. The following models includes clubs’ financial characteristics and other
variables chosen according to previous literature. It is important to remark that to avoid
endogeneity, lagged values are used for the variables with financial information. The
same is applied to variables related to sporting performance. Given that residual errors of
the model do not follow a normal distribution; we use variables in logarithm values.
Ln MVit = β0 + β1 ln NPit-1 + β2 ln BVit-1 + β3 ln POPit + β4 STAit +
β5 ln LEAit-1 + β6 ln REVit-1 + + β7 ln GDPit-1 + Years Dummies + ɛit
(1)
Profitability can be one of the drivers for the market value of the firms, and it can
be measured in different ways, such as cash flow, operating income, or net profit. Given
the strong relationship among all these measures (Bowen et al. 1986; Dechow et al. 1988),
net profit (NP) has been chosen for its simplicity given the heterogeneity of the sample.
However, this is not the main financial variable in all cases that explains the value of a
club. In addition, investors are interested in the expected return, and for that reason,
historical financial performance may not be a good explanatory variable.
On the other hand, when a market is not mature, great growth is expected and
many firms may not obtain profits until the current moment. This is the case with
technological and dot-com companies, as was explained previously. These companies
14
had a strategy of winner-take-all-the-market, where one of the main variables used to
value them was the revenue because it is supposed that only the companies with clear
leadership in the market will survive. Sanchez et al. (2019) noticed the similarities
between European football and fast growth industries. First, since the 1990s, income from
TV rights has grown by 85.5%. Moreover, this increase is concentrated in a decreasing
number of clubs resulting in a possible endgame of winner-takes-all, like the dot-com
industry. For these reasons, revenues (REV) are included as a variable to study their
influence in market value following previous research in other industries (Davis 2002;
Davila and Foster 2005; Sievers et al., 2013).
If revenues are the most relevant variable in the valuation of a football club, we
considered the introduction of potential revenues to be necessary because new owners
would try to increase them. Some variables have been introduced as proxies of these
potential revenues. The population of local market has been included as a proxy of the
potential revenues from stadium. TV rights depend on deals by domestic leagues; for this
reason, a variable about the strength of the league in which the club plays has been
introduced. The capacity of commercial revenues depends on sporting success
(introduced as a variable), the visibility of domestic competition (also introduced as
variable), and local market (proxied by population). All of these are outlined below.
Book value of the equity (BV) is a firm’s net asset value found on its balance
sheet. This variable has also been used in research on the valuation of technology firms,
as was previously described (Aggarwal et al., 2009; Collins et al., 1999). The football
industry presents some similarities with technological and innovative industries with
15
strong growth and market transformation, such as globalisation, new competitions, and
innovation in streaming models. The influence of the capital structure in firms’ value has
been widely studied. Empirical studies have produced mixed results such as Fama and
French (1998), Davis et al. (2005), and Chen and Zao (2006). Myers (2001) pointed out
that the influence would not be universal depending of previous leverage, industry, and
economic cycle. In order to study their influence in football clubs, debt ratio
(LEVERAGE) has been introduced in the models studied. All financial data comes from
the financial statements made public by the clubs.
Regarding non-financial variables, Humphreys and Mondello (2008) found a
positive relationship between North American clubs' price in transmissions and the
population (POP) in the club area and the ownership of the stadium (STA). This last
variable is a dummy that takes the value 1 if the club owns the stadium and 0 otherwise.
Both variables were also used in most of the previous studies with Forbes estimations.
These authors found that the market value also varied depending on the competition. In
the present paper, all clubs analysed are from the same sport, but are taking part in
different domestic leagues. For this reason, a variable measuring the strength of each
competition is included (LEG). This variable is measured using the UEFA coefficient of
the league where each club plays. We introduce the economic situation of the country at
the time of the transactions with the variable of GDP per capita (GDP). The economic
situation at the national level is more relevant than that of the local level, given most of
the revenues come from national deals of TV rights and commercial arrangements, as
Sanchez et al. (2019) have shown.
16
The value of customers is the most important factor for a firm’s valuation in high
growth industries with negative earnings (Gupta et a. 2004), given the winner-takes-all
strategy in these industries. In this way, the number of customers or the size of the
revenues can hide other variables influencing the firm's value. Table 3 shows that this
could happen in our sample, given the correlation between market value and revenues.
For this reason, we introduce additional models with a relative measure, ratio market
value to sales (MVtoS), instead of the absolute value of the market value. The MVtoS
variable follows a normal distribution, and the errors of the models present also follow a
normal distribution.
The omission of the variable ‘revenues’ allows us to introduce variables relating
to sports performance due to the strong relationship between both variables (Arnold,
1991; Szymansky &Kuipers, 1999). Scelles et al. (2016) showed that Forbes’ estimations
of European football clubs’ value are positively related to their sports performance and
players’ value. We introduced similar variables, including recent national sporting
performance (NATSP), measured as the percentage of league points with respect to the
maximum possible, and historical national record (NATHIS), measured as the number of
league and cup titles. Given the relationship between players’ value, nationality, and
continental sporting performance as Table 3 shows, other models are presented. One
model includes recent UEFA competitions performance (UEFSP), based on a UEFA
coefficient used in establishing of seed clubs, and historical UEFA competitions record
(UEFHIS), based on historic coefficient of titles won used as bonus in sharing of money
prize by UEFA. Sporting performance is measured homogenously at national and
17
continental level. A measure combining both would need to introduce a subjective weight
between both performances. Moreover, there is a strong relationship between domestic
and continental success. Table 3 shows that the correlation between continental and
national performance is greater than 75%. For this reason, we decided not to use a
combination of both. Another model with players' value (PLAY) based on Transfermarket
data has also introduced to the study the influence of squad quality.
MVtoS
it
= β
0
+ β
1
NP
it-1
+ β
2
BV
it-1
+ β
3
POP
it
+ β
4
STA
it
+ β
5
LEA
it-1
+ β6 GDPit + β7 UEFSP it-1 + β8 UEFHIS it-1 + Years Dummies + ɛit
(2)
MVtoS
it
= β
0
+ β
1
NP
it-1
+ β
2
BV
it-1
+ β
3
POP
it
+ β
4
STA
it
+ β
5
LEA
it-1
+ β6 GDPit + β7 NATSP it-1 + β8 NATHIS it-1 + Years Dummies + ɛit
(3)
MVtoSit = β0 + β1 NP
it-1
+ β2 BV
it-1
+ β3 POP
it
+ β4 STA
it
+ β5 LEA
it-1
+ β6 GDP it + β7 PLAY it-1 + Years Dummies + ɛit
(4)
Although all the clubs included in the sample belong to the biggest leagues, they
are very different according to financial data and sporting performance, as can be seen in
Table 4.
INSERT TABLE 3 AROUND HERE
INSERT TABLE 4 AROUND HERE
18
Results
The results, presented in Table 5, show that two financial variables have a significant
influence on the market value: revenue and book values. All the models have an overall
statistical significance and a relevant coefficient of determination. The influence of
revenues in the market value also can be found in other winner-takes-all industries where
future success can be conditioned on size. This is the case with Internet industries where,
with many start-up companies competing, only the first ones will get a dominant position
in the market. A market-share as big as possible is determinant of survival in an industry
where only a few corporations will remain. Moreover, it has to be considered that in the
football industry only a few clubs have a global impact.
We have to remark that due to the fact that the number of acquisitions of clubs is
limited, the number of observations is low (only 60), and the model could be considered
overfitted mainly when the year dummies are included. In order to understand whether
we have this problem, we have run the regression using decade dummies instead of years,
thus increasing the degree of freedom, and the results remain similar (see model
‘Variables Reduced’ in the second column in the Annex 2).
INSERT TABLE 5 AROUND HERE
This situation is different in American sports competitions where the leagues
control the market, and the new members are decided by the existing ones in a system of
franchises. European football has an open system with competitions organised by leagues,
19
national federations, and UEFA. Participation in these competitions depends on previous
sporting performance. In practice, however, a reduced group of clubs has been
monopolising the competition in recent seasons. This is an effect of the increasing
difference of the financial capacity between the European clubs, as Sanchez et al. (2019)
have described. The relevance of revenues justified the use of the relative variable ‘market
value to sales’ in the other three models presented in Table 6.
The book value of equity represents a significant influence in all models. This
happens regardless of whether we use market value as an absolute measure or in relation
to revenues. The objective of equity in the balance sheet is to show the theoretical value
according to accounting standards. The strong relation between book and market value
shows that investors take financial statements as a relevant signal of market value as it
happens in other industries. This result shows economic rationality given that the
valuation of football clubs can be estimated by taking objective financial figures instead
of value being related to personal preferences.
On the other hand, earnings do not influence the market value of football clubs.
This may represent another signal that investors consider football to be an emerging
industry, where position in the market is more important than the current profitability or
knowing future earnings. In this way, poor profitability – and even losses – are not
significant for the financial evolution of the firm, if there is the expectation of future cash
flows. This is common to fast-changing industries, such as technology, where investors
prefer low profitability firms with the potential strength to control the market, rather than
companies with earnings. The Internet industry contains different examples of
20
investments in companies with losses that have lately consolidated their position in the
market, consequently providing big profitability. This is consistent with the studies of
Barlett (2016), Gompes et al. (2019), and Scwartz and Moon (2020) about growing non-
sport industries with poor profitability. This also shows the economic rationality of the
valuation of football clubs in the transactions studied, unlike with pieces of art that are
valued according to emotional motivations.
Results show a positive influence of the level of debt in the price paid in the
purchase of football clubs. A possible explanation for this relationship could be based on
the monitoring of clubs' management by debt-holders, as explained by Harris and Raviv
(1990). Given that in the case of an acquisition, there is an asymmetrical information
distributed between the buyers and the seller, the existence of debt-holders whose have
been previously monitoring the management reduces this asymmetry.
A control premium could be expected to be paid when the buyers are acquiring a
certain percentage of the shares, or when they take over the company. To check if this is
the case in the acquisitions of European football clubs, we have included two additional
models in the Annex 2. Model (3) in the Annex 2 includes the percentage bought, and
model (4) includes a dummy variable if the acquisition implies a takeover. The results of
both the variables are not significant.
INSERT TABLE 6 AROUND HERE
Regarding the non-financial variables, the league where a club participates
influences market value as an absolute variable and as relative to sales. In this way,
21
investors pay more for those clubs playing in the strongest leagues. The importance of
the domestic league indicates that buyers not only invest in a club, but also in participation
in a domestic league. The league's capacity for income generation helps the financial
viability of a club with regard to the sharing of TV revenues and the attraction of sponsors.
The GDP per capita of the year and country of the transactions also influences the price
paid for the investors in market value as an absolute variable and as relative to sales.
Investments in the football industry depend on the economic landscape, as with other
industries.
Previous research confirmed the influence of sports performance on clubs’ market
value. Our results show that their importance is reduced when financial data is considered,
unlike in previous studies. The previous season's sporting performance does not influence
the value of the clubs. In this way, short-term sporting performance and squad value do
not modify valuation in the football industry. On the other hand, international historic
sporting performance has some influence on clubs’ value. This performance has an
important role in building the club brand, the international reputation, and the evolution
of a broad fan base. These elements can be relevant for the business, and cannot be
achieved in the short term.
The remaining non-financial variables do not show any influence on the market
value of football clubs. The population in the influence area and the ownership of the
stadium do not seem to be considered in the acquisition of a football club. This result is
different from previous studies of the valuation of clubs in American sports. A reasonable
explanation could be that those studies do not consider financial variables omitting data
22
that the present paper shows as relevant. In this way, the size of the local market seems
not important for the buyers because the importance of the revenues from the stadium is
reducing with respect to income from TV or merchandise from international consumers,
as Sanchez et al. (2019) showed. Moreover, the stadium, despite to be an asset, seems
less important in the valuation of football clubs than historic sports performance.
Conclusions
As investors are profit-seekers, the valuation of firms in takeovers is given by the capacity
to turn profits from their investment. The objective of football club owners depends on
their personal traits because different owners can have different objectives. Traditionally,
club owners had strong ties with the clubs, and their investments were related to social
responsibility within the club area, or emotional reward. These motivations have
commonly been the reason for the poor financial results of the clubs. However, a new
kind of owner has emerged in the football industry without ties to the clubs, and in many
cases with investments in other sports, as in 14 of the 61 transactions of our sample. This
profile of investors may be identified as profit-seeking.
A way to grasp the motivations of this new kind of owner is to understand which
factors better explain the value of football clubs. If the assessment has a subjective
approach, as in the case of the art market, the valuation would not be related to the
financial value of the football clubs. The low profitability of the industry should not be
considered as a sign of no profit-seekers, because it is common to other industries with
high growth and rapid changes, such as in the case of technological firms. In this kind of
23
industry, the market valuations of firms are supported in financial variables, although not
the earnings, together with the intangible capital of the companies.
The results of the paper show the importance of the financial variables in the real
prices of transactions, as they occur in studies about firms’ value in non-sporting
industries. They also show the importance of the financial variables in the real prices of
transactions as it occurs in studies on firms’ value in non-sport industries (Collins et al.
1999; Davis, 2002; Sievers et al., 2013). We can conclude that economic rationality exists
in the valuation of football clubs in the cases of the acquisition of relatively big packets
of shares in the last two decades. There are financial variables, such as book value and
revenues, influencing the price paid by investors. In this way, the football industry is
similar to other fast-growth industries.
For this reason, we can establish some practical implications, given that we detect
that new owners are seeking an economic return, in a similar way to the case of American
sports, instead of emotional rewards. First, this can affect the relationship of the football
clubs with their stakeholders as fans or local communities. Giving that financial and
sporting performance are not related, as Sanchez et al. (2020b) found, profit-seeking
owners would clash with the interests of those stakeholders. Second, these new owners
would prefer the establishment of a competition with less variability of the revenues, in
order to obtain better profitability and reduced financial risks. This can create differences
with the current organisers of domestic leagues or UEFA. The ever-increasing power of
the new investors in football is a challenge to the current governance system. The ‘Big
Picture’ project, where not all the Premier League clubs had the same rights, or the failed
24
project of European Superleague, revealed these investors' interest in replicating the
American sports system
Third, football governing bodies and public administrations should watch the
change of ownership in football clubs. The presence of venture investors can lead to the
taking of elevated risks to obtain higher returns, as happens in other fast-changing
industries. This not only endangers the club they bought, but also the rest of the clubs.
For this reason, the acquisition of football clubs should be controlled in a similar way that
regulators control the takeovers of banks and financial institutions.
These results suggest the possibility of further studies about methods of valuation
for the clubs that are more accurate and transparent. This will be especially important to
protect small shareholders when control ones carry out equity transactions. Further
research could investigate the differences between the valuations of big and small
shareholders. One of the limitations of our work is that the sample only includes
observations in certain moments, but not their evolution over time. In this way, we could
not perform a panel data analysis which could provide better results. The repeat sales
method from Humphreys and Lee (2010) could not be used given that the period of our
sample is shorter, and the number of repeat sales is very low. Future research could
address these problems. Other limitation of the study is that there are few listed clubs. In
the future when more cases appear, the different behaviour between public and private
owned clubs would present an interest line of research.
25
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33
Table 1. Distribution of ownership in Big 5 leagues
Premier
League
La Liga
Bundesliga
Serie A
Ligue 1
Foreign Majority Owner
65%
20%
6%
20%
35%
Domestic Majority Owner
35%
30%
17%
80%
50%
Dispersed Capital
35%
61%
15%
Member Association
15%
17%
Source: Own elaboration.
Table 1. Transactions included in the sample
Club League Year Buyer
Nationality Buyer Seller
Nationality
Corporate
Operation1
Percentage
of capital
Transact. in
constant
Euros
(millions)
Bayern Munich Bundesliga 2009 National Audi National
Capital
Increase
9,1% 102.2
Bayern Munich Bundesliga 2014 National Allianz National
Capital
Increase
8,8% 114.3
Borussia Bundesliga 2014 National Evonik National
Capital
Increase
9,0% 28.1
HSV Bundesliga 2015 National
Klaus-
Michael
Kühne
National Capital
Increase 7,5% 19.5
HSV Bundesliga 2016 National
Klaus-
Michael
Kühne
National Capital
Increase 3,5% 9.6
Atlético de
Madrid
Liga 2015 Foreigner Wanda National
Capital
Increase
20,0% 46.8
Atlético de
Madrid
Liga 2017 Foreigner
Quantum
Pacific
National
Capital
Increase
15.0% 51.4
Atlético de
Madrid
Liga 2018 Foreigner Idan Ofer National Minority 18.0% 50.8
Celta de Vigo Liga 2006 National
Carlos
Mouriño
National Takeover 39.0% 6.1
Celta de Vigo Liga 2014 National
Carlos
Mouriño
National Takeover 24.0% 5.7
Espanyol
Liga
2015
Foreigner
Restar Group
National
Takeover
56.0%
18.7
Granada Liga 2016 Foreigner
Wuhan
Doublle
Foreigner Takeover 100.0% 38.5
Málaga FC Liga 2010 Foreigner
Abdullah Al-
Thani
National Takeover 100.0% 11.8
Sevilla Liga 2018 National
Sevillistas
Unidos 2020
National Minority 5.8% 10.15
Valencia CF
Liga
2014
Foreigner
Peter Lim
National
Takeover
70.4%
103.9
Valladolid Liga 2018 Foreigner
Ronaldo
Nazario
National Takeover 51.0% 30.5
1 Takeover is an operation where the buyer controls the most of the capital or increases it.
34
Girondins
Bourdeaux
Ligue 1 2018 Foreigner GACP National Takeover 100.0% 76.1
Lille
Ligue 1
2017
National
Gerard Lopez
National
Takeover
95.0%
82.3
Nice
Ligue 1
2016
Foreigner
Alex Zheng
National
Takeover
80.0%
11.4
Nice
Ligue 1
2019
Foreigner
Ineos
Foreigner
Takeover
100%
100
O. Lyonnais Ligue 1 2007 National IPO National
Capital
Increase
28.0% 104.7
O. Lyonnais Ligue 1 2016 Foreigner
IDG Capital
Partners
National
Capital
Increase
20.0% 104.0
O. Marseille Ligue 1 2016 Foreigner
Frank
McCourt
National Takeover 95.0% 46.8
PSG
Ligue 1
2006
Foreigner
Colony Funds
National
Takeover
100.0%
49.7
PSG
Ligue 1
2011
Foreigner
QSI
Foreigner
Takeover
70.0%
55.0
PSG
Ligue 1
2012
Foreigner
QSI
Foreigner
Takeover
30.0%
32.1
Arsenal Premier 2018 Foreigner
Stan
Kroenke’s
Foreigner Takeover 30.0% 634.5
Aston Villa
Premier
2006
Foreigner
Randy Lerner
National
Takeover
56.9%
75.9
Aston Villa
Premier
2016
Foreigner
Tony Xia
Foreigner
Takeover
100.0%
70.2
Birmingham
City
Premier 2009 Foreigner
Carson
Yeung
National Delisted 100.0% 104.0
Blackburn
Rovers
Premier 2010 Foreigner
Venky's
London Ltd
National Takeover 100.0% 30.1
Bolton
Wanderers
Premier 2003 National Eddie Davies National
Capital
Increase
64.8% 4.2
Chelsea
Premier
2003
Foreigner
Abramovich
National
Takeover
100.0%
262.9
Derby County Premier 2008 Foreigner
General
Sports and
Entertainment
(GSE)
National Takeover 100.0% 28.9
Fulham
Premier
2013
Foreigner
Shahid Khan
National
Takeover
100.0%
246.3
Liverpool
Premier
2007
Foreigner
Hicks
National
Takeover
100.0%
304.7
Liverpool
Premier
2010
Foreigner
NESV
Foreigner
Takeover
100.0%
392.5
Manchester
City
Premier 2007 Foreigner
Thaksin
Shinawatra
National Delisted 100.0% 142.8
Manchester
City
Premier 2008 Foreigner
Abu Dhabi
United Group
Foreigner Takeover 100.0% 336.6
Manchester
City
Premier 2015 Foreigner
China Media
Capital
Foreigner Minority 13.0% 312.3
Manchester
City
Premier 2019 Foreigner Silver Lake Foreigner
Capital
Increase
10.0% 454.0
Manchester
United
Premier 2005 Foreigner Glazer family National Delisted 100.0% 1459.8
Manchester
United
Premier 2012 Foreigner IPO Foreigner IPO 10.0% 189.7
Newcastle Utd
Premier
2007
National
Mike Ashley
National
Delisted
100.0%
229.3
Portsmouth Premier 2006 Foreigner
Alexandre
Gaydamak
Foreigner Takeover 50.0% 57.1
QPR
Premier
2011
Foreigner
Tune Group
National
Takeover
66.0%
44.3
Southampton Premier 2017 Foreigner
Lander Sports
Development
Foreigner Takeover 80.0% 245.5
Swansea City Premier 2016 Foreigner
Steve Kaplan
and Jason
Levien
National Takeover 60.0% 139.5
West
Bromwich
Premier 2016 Foreigner
Yunyi
Guokai
National Takeover 100.0% 184.1
West Ham
Premier
2006
Foreigner
WH Holding
National
Takeover
100.0%
151.6
West Ham Premier 2010 National
David
Sullivan and
David Gold
Foreigner Takeover 50.0% 68.7
35
West Ham Premier 2010 National
David
Sullivan and
David Gold
Foreigner Minority 3.8% 4.6
West Ham Premier 2013 National
David
Sullivan and
David Gold
Foreigner Takeover 26.2% 31.3
AC Milan
Serie A
2017
Foreigner
Li Yonghong
National
Takeover
100.0%
761.3
AC Milan Serie A 2018 Foreigner
Elliott
Management,
Foreigner Takeover 100.0% 355.3
AS Roma Serie A 2011 Foreigner
Thomas Di
Benedetto
National Takeover 67.0% 77.4
Inter Milan Serie A 2013 Foreigner Erick Thohir National
Capital
Increase
70.0% 314.4
Inter Milan Serie A 2016 Foreigner
Suning
Holdings
Group
Foreigner Takeover 68.5% 280.8
Inter Milan
Serie A
2019
Foreigner
Lion Rock
Foreigner
Takeover
31.5%
150.0
Juventus
Serie A
2001
National
IPO
National
IPO
24.0%
142.1
Lazio Serie A 2004 National
Claudio
Lotito
National
Capital
Increase
27.0% 26.7
Source: Own elaboration from media (see summary in Annex 1)
36
Table 3. Variables correlation
Variables
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(14)
(15)
(1) MV
1.000
(2) MVtoSALES
0.798
1.000
(3) REV
0.856
0.612
1.000
(4) NP
0.342
0.262
0.442
1.000
(5) BV
0.841
0.565
0.811
0.300
1.000
(6) POP
0.061
-0.073
0.050
-0.026
0.321
1.000
(7) STA
-0.006
0.033
-0.054
0.202
0.101
0.118
1.000
(8) LEA
0.047
0.109
0.005
0.121
0.061
-0.079
0.302
1.000
(9) GDP
0.116
0.405
0.110
0.079
0.037
-0.092
-0.019
-0.145
1.000
(10) LEVERAGE
-0.259
-0.156
-0.499
-0.196
-0.348
-0.024
0.088
0.088
-0.103
1.000
(11) NATHIS
0.527
0.399
0.541
0.225
0.642
0.280
0.036
0.091
-0.066
-0.334
1.000
(12) NATSP
0.374
0.268
0.313
0.061
0.649
0.356
0.071
-0.121
-0.097
-0.281
0.481
1.000
(13) UEFHIS
0.406
0.215
0.471
0.287
0.631
0.293
0.242
0.284
-0.120
-0.300
0.694
0.494
1.000
(14) UEFSP
0.192
0.176
0.082
-0.251
0.438
0.351
0.028
-0.039
-0.113
-0.128
0.313
0.753
0.210
1.000
(15) PLAY
0.796
0.525
0.664
0.273
0.847
0.170
0.019
0.206
-0.077
-0.269
0.601
0.542
0.624
0.305
1.000
37
Table 4. Descriptive statistics
Variable
Meaning
Mean
Sd
Min
Max
MV*
Market Value
417.803
735.343
6.518
4540
MVtoS
Market Value to Sales
1.927
1.521
.091
7.953
NP *, †
Net Profit
376.22
201.294
55.85
1307.61
BV *, †
Book Value
194.616
32.518
72.085
277.108
REV *
Revenues
160.622
128.091
10.152
570.857
POP ‡
Market Size
5.082
4.161
.3
17.9
STA
Stadium
.525
.504
0
1
LEA
League
74.116
15.409
50.781
106.998
GDP ⁑
GDP per capita
29.871
4.631
22.21
54.85
LEVERAGE
Liabilities to Assets
.999
.705
.227
5.016
NATSP
Domestic Sport Performance
.52
.15
.265
.892
NATHIS
Historic Domestic Sport Performance
11.508
10.176
0
39
UEFSP
Continental Sport Performance
6.016
9.302
0
33
UEFHIS
Continental Historic Sport Performance
4.607
7.749
0
30
PLAY*
Squad Value
205.909
179.335
27.2
1010
* In millions of 2019 constant Euros.
† Scaling to avoid negative values.
‡ In millions of inhabitants.
⁑ In thousands of Euros.
Source: Own elaboration
Table 2. Output of the regressions explaining Market Value
(1)
VARIABLES
lnmv
lnREV
1.150***
(0.164)
lnNP
-0.479
(0.537)
lnBV
0.955**
(0.402)
lnPOP
-0.0353
(0.128)
sta
0.0498
(0.212)
lnLEA
1.348**
(0.539)
lnGDP
1.819***
(0.588)
LEVERAGE
0.279
(0.196)
Constant
-24.06***
(7.390)
Year dummies
Yes
Observations
61
R-squared
0.897
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
2
Table 3. Output of the regressions explaining Market-Value-to-Sales
(1)
(2)
(3)
VARIABLES
pricetosales
pricetosales
pricetosales
NP
-0.00333
0.00110
-0.00363
(0.00446)
(0.00456)
(0.00437)
BV
0.00498***
0.00524***
0.00448***
(0.000870)
(0.000760)
(0.00115)
POP
-0.0167
-0.0147
-0.0140
(0.0342)
(0.0331)
(0.0332)
STA
-0.109
-0.0430
-0.114
(0.271)
(0.254)
(0.274)
LEA
0.0315***
0.0321***
0.0283***
(0.0105)
(0.00939)
(0.0100)
GDP
0.126***
0.122***
0.129***
(0.0255)
(0.0237)
(0.0269)
LEVERAGE
0.459**
0.485**
0.394*
(0.217)
(0.200)
(0.215)
NATHIS
0.0140
(0.0160)
NATSP
0.0518
(1.143)
UEFHIS
0.0371**
(0.0166)
UEFSP
-0.0209
(0.0163)
PLAY
0.00110
(0.00136)
Constant
-4.899**
-5.636***
-4.247***
(1.801)
(1.571)
(1.545)
Year dummies
Yes
Yes
Yes
Observations
61
61
61
R-squared
0.840
0.863
0.839
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
3
