Spanish football in need of financial therapy: cut expenses and inject capital.
Barajas, Angel ; Rodriguez, Placido
The European Union is concerned about the financial distress in
business. In response, the EU authorities are developing a policy
designed to give early warning signs of financial distress in businesses
that will help to prevent bankruptcy and that will come into effect in
the early stages of financial crisis. A quick response at that time may
be vital in order to offer a second chance to businesses.
UEFA, European football's governing body in turn, is worried
about the financial health of European football. Two main initiatives
have been promoted with that in mind. First, UEFA has developed the Club
Licensing Benchmarking Report. This report draws on the information
gathered from the UEFA Club Licensing system to provide a comparative
map of football in Europe covering financial, sporting and licensing
dimensions. To date four reports have been released: Financial years
2008, 2009, 2010 and 2011. The reports were elaborated by Perry (2009
and 2010) and Perry and Leach (2011 and 2012). Second, the Financial
Fair Play Regulations approved by the UEFA Executive Committee in May
2010 and in May 2012. These regulations have not just been generated
through an internal process in UEFA but are the result of discussions
with all stakeholders, and in particular with the clubs represented by
the European Club Association (ECA). The objectives of these
regulations, set out in article 2 (UEFA 2010) can be summarized as
follows: to protect the integrity of the UEFA competitions; to encourage
clubs to operate on the basis of their own revenues; to encourage
investment in infrastructures and youth football for the long-term
benefit of football; to ensure that clubs competing in European
competitions have paid their debts towards other clubs and employees.
Just in one sentence: to protect the long-term viability and
sustainability of European club football.
There is an unquestionable financial problem in European football.
Kuper and Szymanski (2009) underlined that forty English professional
clubs have been involved in insolvency proceedings during the period
1992-2008. Hamil and Walters (2010) asserted that, for English football
clubs, it is likely to be difficult to operate on a breakeven financial
basis due to their collective debt at that time. Mourao (2012) remarked
that most Portuguese football teams had increased their debt ratios
during the previous two decades.
The Spanish football industry has experienced serious financial
problems in the last decade. Ascari and Gagnepain (2006) asserted that
the Spanish football industry suffers a structural weakness but that, in
their opinion, the situation seems to be less severe than in other
European leagues. Bosca et al. (2008) refuted this conclusion of Ascari
and Gagnepain and stated, in line with Garcia and Rodriguez's
(2003) earlier conclusions, that the economic situation of Spanish
football clubs was one very fragile. Barajas and Rodriguez (2010)
pronounced the difficult financial situation of the Spanish football
industry. According to Syzmanski (2010), in Spain, only Real Madrid and
FC Barcelona have real financial strength, and the rest of the clubs
struggle to compete, and most clubs have significant debt exposure.
Paradoxically, the financial crisis of loss making in football had
coincided with a time of dramatic increases in revenue (Lago et al.,
2006). The origin of the problem is the imbalance between income and
expenditures and, as a consequence, the rising debt. A big portion of
that debt presents a short-term maturity. This implies that Spanish
clubs, in recent years, have not been able to pay their immediate debts
and have consequently gone under administration taking advantage of the
Concursal law 22/2003. This law is roughly analogous to Chapter 11
bankruptcy in the USA. It is worth noting that it was designed for other
industries. One of the principles of that law is to try to guarantee the
continuity of the business when it emerges from the administration
process. For that reason, the court of justice set the principle that
clubs could not be punished with relegation or other sporting punishment
because that would alter their business conditions and would make it
almost impossible for the club to survive.
The result is that, up until the end of 2011, 22 clubs were or had
been in administration (1): Las Palmas, Sporting de Gijon, Malaga,
Alaves, Celta de Vigo, Real Sociedad, Polideportivo Ejido, Albacete,
Recreativo de Huelva, Murcia, Xerez, Granada 74, Alicante, Zaragoza,
Levante, Cordoba, Rayo Vallecano, Betis, Mallorca, Racing de Santander,
Valladolid, and Hercules.
In this context, it is interesting to probe deeper into the
financial situation of Spanish football. At the same time, it is also
interesting to speculate what might be the necessary level of funding of
Spanish clubs in order for them to have a safe financial position
according to the Altman (2) criteria. So, our paper has two objectives:
first to analyze the finances of Spanish football clubs and, secondly,
to estimate the financial needs of clubs in order for them to achieve a
sound financial balance.
Thus, in Anticipating Financial Distress we search the factors
determining the clubs' financial situation. The method that we will
use in this paper has been developed and first used by Altman (1968). It
allows us to simulate the values of the relevant variables (current and
total assets, equity, short- and long-term liabilities, player salaries,
revenues, and working capital) that are necessary for long-term survival
and growth. We also carry out our analysis considering the differences
between First Division (Liga BBVA) and Second Division (Liga Adelante).
Subsequently, in the third section, "Some Highlights," we will
present an overview about the clubs' financial situation.
The Altman models offer a classification of companies according to
the values of their Z-score. This classification is relevant for the
purpose of this study due to the fact that the Z-score is an indicator
of the different clubs' degree of (in-)solvency. Based on this we
have designed a programming model to estimate the values of the
different variables to be included in the model in order to reach a
sound financial situation. This is explained in the fourth section, and
the paper concludes in the fifth section with a summary of the results
obtained and our conclusions.
Anticipating Financial Distress
Several models seek to predict bankruptcy in companies with
reliability and it has been a common subject among many studies and
articles. Beaver (1966) created one of the first models. In his work, he
analyzed various financial ratios of companies, five years before the
bankruptcy occurred, and then compared them with the ratios of solvent
companies. So, using univariate analysis, he isolated a number of
factors that could differentiate between various samples of firms that
had gone bankrupt and others that had not.
However, economic failure in business is a very complex issue that
is a function of several factors. So, univariate analysis results are
insufficient in themselves to explain causality. Some years later,
Deakin (1972) used the variables of the Beaver (1966) model but, in this
case, applying multivariate discriminant models. He concluded that there
were definite potential relationships as many of the factors he chose
generally predicted bankruptcy. Those studies found that ratios
measuring profitability, liquidity, and solvency appeared the most
significant indicators.
Altman (1968), Altman et al. (1977), Dimitras et al. (1999),
Philosophov and Philosophov (2002) also employed financial ratios to
predict bankruptcy. The logistic regression has been commonly used to
try to explain or predict the financial failure of companies (Balcaen
and Ooghe, 2006; Dimitras et al. 1999), and this was also used by
Barajas and Rodriguez (2010) in respect to Spanish football. Artificial
neural network models, or genetic programming and self-organizing maps,
have been employed by Mora et al. (2007) and Alfaro-Cid et al. (2009).
All these models seek to examine and quantify the variables that predict
whether a company has the risk of falling into financial difficulty.
Altman (1968, 2000) and Altman et al. (1977) developed the Z-score
and Z Models[R], which employ multivariate analysis. Altman extended the
univariate analysis by introducing multiple Beaver's bankruptcy
predictors in his model. After introducing the multiple discriminant
analysis (MDA) to analyze a summary of accounting data on financial
ratios, he developed a linear function with a series of explanatory
variables, and the dependent variable appears in a qualitative form
(namely, bankrupt or non-bankrupt). This model is now commonly used and
has the advantage of simplicity. In that sense, Grice and Ingram (2001)
highlight that Altman's bankruptcy prediction has been persistently
used by researchers and practitioners. Even more, they emphasize that
"Altman's continues to be the one most cited and used."
Cantoni (2004) asserts that Altman's model is used nowadays by
banks and rating agencies. Charitou et al. (2004) sustain that the model
"has been commonly applied in finance and accounting research.
Furthermore, it has been used extensively by both academics and
practitioners as a standard of comparison for subsequent failure
studies" (p. 488). Anjum (2012) concludes that Altman's model
is one of the most effective MDA that has been researched for the past
40 years. Moreover, she remarks that "it can be safely said that
Altman's Z-score model can be applied to modern economy to predict
distress and bankruptcy" (p. 217). Pitrova (2011) maintains that
Altman's model ranks the group of healthy companies well and
detects the financial difficulties of companies one year prior to their
bankruptcies correctly.
However, there is evidence about the weaknesses of the model when
it is applied in countries other than the USA or specific industries.
See, for example, Bontz, Kennedy, and Sun (2007) who point out that
Altman's "poses a potential problem for practitioners in
Canada and researchers working with Canadian data" (p. 162). But
even with the possible shortcomings of the model, it can be a useful
tool in order to obtain an idea about what happens in Spanish football.
For all that reasons, we are going to utilize it in the present paper.
The first model, Altman's Z-score, was the result of the
linear combination of five ratios as follows:
Z=0,012[X.sub.1]+0,014[X.sub.2]+0,033[X.sub.3]+0,006[X.sub.4]+0,999[X.sub.5]
Where: Working Capital/Total Assets
[X.sub.2] = Retained Earnings/Total Assets
[X.sub.3] = EBIT/Total Assets
[X.sub.4] = Market Value of Equity/Book Value of Total Liabilities
[X.sub.5] = Sales/Total Assets (3)
Z = Z-score
Altman found that for a Z-score value
* over 3, the business is free of bankruptcy risk;
* between 2.7 and 3, a monitoring process would be recommended;
* between 1.8 and 2.7 a detailed analysis of financial problems is
recommended;
* below 1.8, bankruptcy risk is high.
This initial model is applicable only to public companies due to
the fact that [X.sub.4] is estimated from market values. For that
reason, Altman considered how to modify the model in order to make it
suitable for analyzing private companies. The easiest way would have
been to replace the market values with book values. Instead, using that
proxy, he decided to estimate from scratch the model including the book
values in [X.sub.4].
This implies that all the coefficients have to change (not only in
the new [X.sub.4]). There would also be new values in order to set the
areas of safety and risk. Hence, the new model:
Z1 = 0.717[X.sub.1] + 0.847[X.sub.2] + 3.107[X.sub.3] +
0.420[X.sub.4] + 0.998[X.sub.5]
Where: [X.sub.4] = Book Value of Equity/Book Value of Total
Liabilities
Altman offered a third version of his model, one appropriate for
non-manufacturing companies. In this model, the [X.sub.5] ratio
(sales/total assets) is excluded. This was done in order to minimize the
potential effect related to the specific manufacturing industry because
this industry is highly sensitive to the criteria of the size of
business. So, the third version of the model:
Z2 = 6.56[X.sub.1] + 3.26[X.sub.2] + 6.72[X.sub.3] + 1.05[X.sub.4]
Where: [X.sub.4] = Book Value of Equity/Book Value of Total
Liabilities
[X.sub.5] is excluded.
This model is suitable to an industry where there are no listed
companies and where the size of the companies varies significantly. For
that reason, we believe that this model would constitute an appropriate
framework of analysis for the football industry. We are conscious that
the model would have a better predictability with the appropriate
coefficients. Nevertheless, we are not going to use it as a prediction
tool but as a classification instrument and as a starting point in order
to determine the necessary level of funding of clubs in order to have a
safe financial position.
European football is a peculiar industry where teams can be treated
as win maximizers--subject to a profit constraint--rather than profit
maximizers (Sloan, 1971; Kesenne, 1996 and 2000; Garcia-del-Barrio and
Szymanski, 2009). Various studies have addressed the financial crisis in
the Football industry, and have provided insights on the debate on the
financial regulations. For easing the financial burden of football
clubs, some papers have even proposed restructuring the sporting
competition (see for instance: Lago, Simmons, and Szymanski, 2006).
Moreover, the sporting contest in European football implies promotion
and relegation (4). Teams pursuing profit maximization are very likely
to be relegated (5), thereby reducing their future profit opportunities.
Thus, it is sensible to suppose that the promotion and relegation system
places additional pressure on the clubs to spend on players, reinforcing
the conclusion that their primary goal, in practice, is not to maximize
profits. Regarding Spanish professional football, Barajas and Rodriguez
(2010) assert that while clubs under serious financial distress
remaining in Liga BBVA6, they are capable of avoiding judicial
administration because creditors and public administration are not in
favor of asking for unpopular measures to shut down insolvent Spanish
football clubs.
Some Highlights about the Financial Situation of Professional
Football in Spain.
The macro financial situation in Spanish football has been analyzed
over the last decade by many scholars, including Garcia and Rodriguez
(2003), Barajas (2005), Ascari and Gagnepain (2006), Bosca et al.
(2008), Gay Saludas (2009a and 2009b) and Barajas and Rodriguez (2010).
Following these macro analyses, it is interesting to investigate more
deeply the micro financial analysis as contained in the financial
accounts of Spanish professional football clubs.
In our case, we are going to take as main reference the variables
included, directly or indirectly, in Altman's models. We are going
to analyze Spanish First Division football clubs (Liga BBVA) and a
significant proportion of the Second Division A clubs (Liga Adelante).
The data base we will be working with is made up of the annual reports
of the clubs (balance sheet, income statement account) since 2007 until
2011. Table 1 shows the number of clubs in the sample. There is only one
set of club accounts for the First Division missing in 2008 and 2011.
Whilst a comprehensive set of accounts is not available for the Liga
Adelante clubs, nevertheless the sample available over the chosen period
is a representative one.
Before commencing the analysis, it is interesting to compare some
financial ratios in order to formulate an initial picture of the
evolution of the financial performance of Spanish football over the
chosen period of analysis. Table 2 illustrates how indebtedness (total
debt/total assets) has increased dramatically in the First Division and
how, on average, the clubs cannot cover their debts with their assets.
When the same ratio is applied for Second Division clubs the results are
even worse than for the First Division, although the ratio performance
was improving over the chosen period. A similar pattern emerges when
consideration is given to the ratio that measures the ability to cover
debt with revenue. It increases in the First Division and diminishes in
the Second Division. So, in summary, we can say that the financial
situation was deteriorating in Spanish football particularly among
Division One clubs. The effect of administration (Concursal Law) may
explain the improvement in the ratios of the Second Division (7).
Table 3 and Table 4 present the evolution of the main variables
included directly or indirectly in Altman's models for Liga BBVA
and Liga Adelante respectively. There are some features that should be
remarked upon. On average in 2011, the total assets (TA) of a First
Division clubs were 9.8 times the size of a Second Division club (8.8
times if the five season period is considered). Current assets (CA)
present a similar proportion (11.2 times in 2011 and 8.5 over the whole
period). The story repeats for current liabilities (CL), but in this
case what is relevant is that this variable is approximately twice the
CA. That means that on average the Working Capital (WC) is negative
(57.6MM [euro] in Liga BBVA and 6.5MM [euro] in Liga Adelante in 2011).
More relevant than the absolute negative figure is the fact that, on
average, the negative working capital for First Division clubs has
tripled since 2007.
When the working capital is negative, as a consequence,
Altman's [X.sub.1] ratio is negative as well. Table 5 illustrates
that almost 80% of clubs in Liga BBVA have negative working capital as
of the 30th June 2011. The situation is slightly better in Liga Adelante
(62.5%). Obviously, this means that a very significant number of clubs
are experiencing very serious financial problems because they cannot
cover their debt related payments in the short term.
With regards the equity (Eq) figure, the average equity in Liga
BBVA was 16.2MM [euro] at the end of the season 2010/11, but the figure
turns negative in Liga Adelante (12.6MM [euro]). This data should be
viewed alongside a consideration of the percentage of clubs with
negative Equity: 36.8% and 37.5% respectively. This implies that more
than a third of the clubs should issue shares or raise funds from their
members (socios).
Still, the panorama becomes darker when one examines the degree of
debt leverage. On average, the debt in Liga BBVA is 10.7 times the
equity in 2011. The good news is that this figure is lower than the
average of the period (11.4 times).
Examining the variables connected to the profit and loss account,
it becomes easy to understand how clubs have found themselves in such a
situation. The average revenue in Liga BBVA was 12.7 times the total
revenues (TR) in Liga Adelante over the whole period. However, of that
figure only 7.2 related to wages and salaries (W&S). One consequence
of this is that the value of the ratio W&S/TR is much worse in Liga
Adelante (on average 66.4% and 116.3% respectively). According to
Kesenne (2009) the first value is reasonable but the value for Liga
Adelante clubs is out of any financial rationality. With those figures
it would be expected that clubs in the Second Division would be making
significant financial losses. Indeed this is what happened: clubs in the
Second Division lost, on average, 4.5MM [euro] in the financial year
2011. But the situation is not much better on average in the First
Division with each club, on average, lost 2.5MM [euro] in that financial
year. Nevertheless, it is worth noting that only 52.6% of clubs in Liga
BBVA and 56.3% in Liga Adelante present financial losses (8). So some
clubs are clearly able to operate at a profit (9).
Some information about the dispersion of the data related to each
variable could contribute towards a better understanding of the
financial situation. For this reason, we have included a box plot of the
total revenues, expenses on players (including wages and amortization),
net profit, equity and total debt for the financial year ending in June
2011. The charts are split into divisions in order to present the
differences between them (see Figure 1, Table 7 and Table 8). Regarding
the total revenues, the range in Liga BBVA goes from 445.5MM [euro]
earned by Real Madrid, followed by Barcelona (417.1MM [euro]), to the
minimum of 18.1MM [euro] earned by Almeria. This implies that the
revenue of Real Madrid is about 25 times greater than that of Almeria
and 5.3 times greater than the average of the Division. The dispersion
is much lower in Liga Adelante where the range goes from 15.4MM [euro]
to 2.9MM [euro]. Similar in wages and salaries, Real and Barcelona
change positions with a record of 240.6MM [euro] and 216.1MM [euro]
respectively. Almeria still expended the smallest amount in first
division (11.6MM [euro]). Looking at Liga Adelante figures, the maximum
expenditure rises to 23.5MM [euro]. This means that the club with higher
revenues and expenses on wages, namely Betis, expended (only in this
concept) nearly 8MM [euro] over its total revenues. The logical
consequence was that Betis had the highest losses in its division (36MM
[euro]).
[FIGURE 1 OMITTED]
Regarding net profit in Liga BBVA, there is a huge gap between Real
Madrid's 31.4MM [euro] profit and Malaga's losses (10) (43.9MM
[euro]). As previously mentioned, in Liga Adelante, Betis presented the
maximum losses. The standard deviation of the net profit is higher than
in first division.
Barcelona declared the minimum equity (-71.7MM[euro]) in 2011. This
figure is the result of two years of losses (70.6MM [euro] in 2010 and
>.3MM [euro] in 2011). Betis had a record of (-67.1MM [euro]). This
club entered under administration in January of 2011. There is a great
dispersion among the values in both divisions.
There are four clubs with outstanding levels of debt, namely, Real
Madrid, Barcelona, Atletico de Madrid, and Valencia. While Barcelona has
the highest level of short term debt (410.0MM [euro]), Real presents the
highest figures of long term debt (238.1MM [euro]) and total debt
(584.7MM [euro]). It is worth pointing out that, even when the club had
declared an average net profit of 30MM [euro] during the last 5 years,
its total debt increased by 107.4MM [euro]. This represents a geometric
average growth of 5.2%.
Nevertheless, as Real Madrid equity has been also increasing during
the study period, the ratio Total Debt to Equity has improved going from
3.39 (2007) to 2.39 (2011). However, still this figure is very high.
In general terms, dispersion is higher in first division than in
Liga Adelante, with outstanding values mostly related to Real Madrid and
Barcelona. The ability of those clubs to get revenues is far from the
average of Liga BBVA and it implies that most of their figures be
distant from the mean as well.
How Much Money Would Be Required by Spanish Professional Football
Clubs to Avoid the Financial Risk of Bankruptcy?
We have analyzed the financial situation of Spanish football, and
we have observed the worrying situation of its equity deficit and
indebtedness. We have then taken a step forward in our analysis. Working
with the sample described in Table 1, we have estimated the
Altman's Z, [Z.sub.1], and [Z.sub.2] scores, described in
Anticipating Financial Distress, for every club in our sample during the
study period in order to obtain a ranking of financial risk for clubs in
professional football. This ranking is based on [Z.sub.2]. It is the
most appropriate Altman's Z-score for football in Spain because no
Spanish club is listed (one of the features of companies in the Z model)
and football clubs are not manufacturing companies (a characteristic of
companies in [Z.sub.1]). The results are shown in Table 9 and Table 10.
These numbers are quite stark. Only one club in Liga BBVA would be in a
safe financial situation and the rest are at risk of going bankrupt. The
circumstances seems to be better in Liga Adelante where four clubs would
have a strong financial performance, and two other clubs would not be at
an immediate risk of bankruptcy. Maybe some comments should be added to
this regard. One of these clubs is Granada CF. We could ask ourselves
how a club under administration can present a safer financial position.
The answer is simple: as the club entered under administration early in
2011, the court of justice approved an agreement with the creditors
where they gave up 50% of their credits and offered a new payment
agreement over the course of the following five years (11). This implies
that suddenly the financial structure of the club appears to be much
healthier and the Z-scores improve automatically. However, this
immediate effect will easily disappear if there are no structural
changes in the management of the club. The case of Levante in Liga BBVA
is similar but with the peculiarity that Levante was promoted in 2011.
This fact entails an increase in revenues that, along with the strict
financial control due to the administration, contribute to improving
financial indicators. However, the cases of Numancia, Alcorcon, and
Huesca differ. The first one has been a yo-yo club for the past ten
years. Nevertheless, the board of directors knows full well that the
club cannot afford the level of expenses that other clubs in bigger
markets can to stay in the top division. Since 2008 the z-scores of
Numancia have been among the best (1.04; 5.19; 1.91; 2.45 from 2008 to
2011 respectively). Huesca and Alcorcon have traditionally played in
lower divisions. Huesca was promoted to Liga Adelante in 2008 and
Alcorcon was in 2010. In both cases, their management have been
characterized by financial rationality, their expenses being lower than
other clubs that have been in the division for a longer time.
It is worth stating that when a club goes under administration the
reduction of the credits has frequently reached up to 50% and sometimes
even more and there has been a delay up to five years on payments. So,
an improvement in the financial ratios in general and z-scores in
particular could be expected. However, this has not always been the
case. Table 11 presents the evolution of [Z.sub.2]-score of the clubs
that have entered under administration since 2007. Some clubs increase
their Z-score after the administration but others present worse values
after the process. Promotion and relegation can also affect these
values. So, the relationship between being under administration and the
financial situation measured by financial ratios or Z-score is not
clear. Moreover, this is due to the fact that, in Spanish football,
avoiding legal process of administration has been the common behaviour
whenever possible up to now.
The question then arises, what should the other clubs do in order
to achieve a [Z.sub.2]-score higher than 2.9, which is the value that
could be considered safe. So, according to the model described in
section 2, we have designed programming problem with the following
specifications:
Objective Function:
[Z.sub.2] = 6.56[X.sub.1] + 3.26[X.sub.2] + 6.72[X.sub.3] +
1.05[X.sub.4]
where the objective value is [Z.sub.2.sup.*] = 2,9.
Under the restrictions:
Net profit, EBIT, Long-term debt, current liabilities, and equity
[greater than or equal to] 0.
TR [greater than or equal to] [TR.sup.*]; where [TR.sup.*] are the
revenues of club i in 2011.
TA = Eq + LTL + CL
Where:
[X.sub.1]= WC/TA; where WC is function of CA and CL).
[X.sub.2] = (net profit - dividends)/TA, where dividends in
football has been null.
[X.sub.3] = EBIT/TA.
[X.sub.4] = Eq/(LTL+CL).
We have used the Excel Solver tool in order to obtain the values of
the different variables for each club at risk of bankruptcy according to
their [Z.sub.2]-score. The objective value for the [Z.sub.2]-score has
been settled at 2.9. After this process of analysis we draw the
following observations:
-- There have been three cases in which it was not possible to
reach a solution (achieving a 2.9 score). These clubs are Atletico de
Madrid, FC Barcelona, and Real Zaragoza. Nevertheless those clubs
obtained some values that provide a higher [Z.sub.2]-score than they had
before the process.
-- There are some cases in which there is a solution but still
their equity value is equal to zero (Xerez, UD Salamanca, and Recreativo
de Huelva). Obviously, the equity value needs to be higher.
-- In the case of Valencia FC and Rayo Vallecano, the solution
includes a high net margin (net profit/TR) that would be very difficult
or impossible to reach.
-- In the cases of Recreativo de Huelva, Malaga CF, and Racing de
Santander, the increase in revenues that they need to experience in
order to reach a safe financial situation does not appear feasible.
These facts mean that at least ten clubs would have serious
difficulties reaching a sound financial position. But if we consider the
average, the main figures are summarized in Table 12. This illustrates
that, on average, clubs in Liga BBVA would need to issue shares, or ask
their members to invest, 31.7MM [euro]. In the case of Liga Adelante the
figure is 12.6MM [euro]. In absolute terms, this should represent a
total investment of more than 630MM [euro] and 275MM [euro]
respectively. It would necessary represent a higher increase in revenue
in the Second Division than in the First Division. Conducting a
reduction of the current liabilities would be necessary. Partly, this
may be achieved by the conversion of some current liabilities into
long-term debt.
Summary and Conclusions
The financial situation of Spanish professional football has become
weaker year after year. The phenomenon is worse in Liga BBVA than in
Liga Adelante, where in the case of the latter the effect of
administration could explain the improvement in indebted ness ratio (as
clubs shed some debt through the protection of the administration
process). It is worth noting that, as Barajas and Mareque (2012)
demonstrate, more than 70% of clubs present qualified auditing report,
adverse opinion report or disclaimers to their financial statements.
This means that we could argue that the financial situation is even
worse than it is presented in their accounts.
Regarding the working capital, the panorama is extremely worrying.
Almost 80% of the clubs in Liga BBVA, and 62.5% in Liga Adelante, cannot
cover their current liabilities with their current assets. This implies
that the probability of struggling with problems to pay on time will be
high.
Clubs have a dynamic of losing money. The excess of expenditure on
players explains clearly the reason for that phenomenon. So, for
example, Liga Adelante clubs expend on average more than 110% of their
total revenues in wages and salaries. Slightly better is the situation
in Liga BBVA (66.4%). The consequence is that more than half of clubs in
both tiers present losses. Finally, this implies that almost 40% of the
clubs in both divisions present negative equity. So, more than a third
of clubs should seek funds from their shareholders or members. In this
sense, if clubs do not change the tendency and get some funds from their
shareholders, they are going to have difficulties fulfilling the
requirements of the Financial Fair Play. In fact, three clubs could not
get the license to compete in UCL or Europe Cup in season 2013-2014.
Barcelona and Real Madrid would not have problems if they do not
overspend in players. Both clubs together gather more that the 50% of
the total revenues (Barajas, 2010).
Altman's models can be useful to identify clubs that could
suffer financial difficulties in the future. According to the model,
only one club in Liga BBVA and four in Liga Adelante could be said to be
in a sound financial position at the financial year 2011 (see Table 9
and Table 10). Nevertheless, being under administration is an
independent legal process. So, some clubs try to avoid that process
while they can (12). For that reason, not all the clubs that should be
theoretically under administration have actually entered the legal
process.
We have employed a programming problem in order to identify the
theoretical financial needs of clubs. The average results illustrated in
Table 12 suggest that Spanish football should pass through a process of
issuing shares or asking members to provide funds, for more than 900MM
[euro] in total. This process needs to be accompanied by an increase in
revenues and reduction in wages and salaries, particularly in Liga
Adelante. Moreover, it is necessary that there be a cutback of current
liabilities. Part of the latter process could be achieved by converting
such current liabilities into long-term liabilities.
Even when Altman's models appear to be useful as a means of
identifying future financial distress, we would like to include other
ratios in the model in future researches.
Angel Barajas is associate professor of financial management in the
Department of Accountancy and Finance and Director of the MBA in Sport
of the University of Vigo.
Placido Rodriguez is the current president of the International
Association of Sports Economists and the lead editor of The Econometrics
of Sport (Edward Elgar Publishing, 2013).
Acknowledgement: We thank Pedro Garcia del Barrio, Sean Hamil,
Stephen Morrow, Paulo Mourao, and Pablo Rodriguez for their useful
comments and remarks during preparations and discussions of the paper.
We also thank the two referees for their anonymous work to improve the
quality of this paper.
References
Alfaro-Cid, E., Mora, A. M., Merelo, J. J., Esparcia-Alcazar, A.
I., & Sharman, K. (2009). Finding relevant variables in a financial
distress prediction problem using genetic programming and
self-organizing maps. Natural Computing in Computational Finance, 2,
31-50.
Altman, E. I. (1968). Financial ratios, discriminant analysis and
the prediction of corporate bankruptcy. Journal of Finance, 23, 589-609.
Altman, E. I. (2000). Predicting financial distress of companies:
Revisiting the Z-score and Zeta[R] models, Working Paper Stern
University.
Altman, E. I., Haldeman, R. G., & Narayanan, P. (1977). ZETATM
analysis: A new model to identify bankruptcy risk of corporations.
Journal of Banking and Finance, 1, 29-54.
Anjun, S. (2012). Business bankruptcy prediction models: a
significant study of the Altman's Zscore model. Asian Journal of
Management Research, 3, 212-219.
Ascari, G., & Gagnepain, P. (2006). Spanish football. Journal
of Sports Economics, 7, 76-89.
Balcaen, S., & Ooghe, H. (2006). 35 years of studies on
business failure: An overview of the classic statistical methodologies
and their related problems. British Accounting Review, 38(1), 63-93.
Barajas, A., & Mareque, M. (2012). La calidad de la information
financiera en el futbol espanol. Estrategia Financiera, No. 293/Abril,
30-35.
Barajas, A., & Rodriguez, P. (2010). Spanish football
clubs' finances: Crisis and player salaries. International Journal
of Sport Finance, 5, 52-66.
Barajas, A. (2005): El valor economico del futbol. Radiografia
financiera del futbol espanol. Pamplona: EUNSA.
Barajas, A. (2010), Competitive balance and concentration ratios in
economic terms in Liga BBVA. Working paper available at SSRN:
http://dx.doi.org/10.2139/ssrn.2283411
Beaver, W. H. (1966). Financial ratios as predictors of failure.
Journal of Accounting Research, 4(SUPPL.), 71-111.
Boritz, J. E., Kennedy, D. B., & Sun, J. Y. (2007). Predicting
business failures in Canada. Accounting Perspectives/Perspectives
Comptables, 6, 141-165.
Bosca, J. E., Liern, V., Martinez, A., & Sala, R. (2008). The
Spanish football crisis. European Sport Management Quarterly, 8,
165-177.
Cantoni, E. (2004). Financial statement analysis and insolvency
forecast models: A proposal for local firms. Economia Aziendale 2000, 4,
1-17.
Charitou, A., Neophytou, E., & Charambolous, Ch. (2004).
Predicting corporate failure: Empirical evidence for the UK. European
Accounting Review, 13, 465-497.
Deakin, E. (1972). A discriminant analysis of predictors of
business failure, Journal of Accounting Research, 10, 167-179.
Dimitras, A. I., Slowinski, R., Susmaga, R., & Zopounidis, C.
(1999). Business failure prediction using rough sets. European Journal
of Operational Research, 114, 263-280.
Franck, E. (2010). Private firm, public corporation or
members' association--governance structures in European football.
International Journal of Sport Finance, 5, 108-127.
Franck, E. (2013). Financial fair play in European club
football--What is it all about? Working Paper No. 328, Department of
Business Administration, University of Zurich.
Garcia, J., & Rodriguez, P. (2003). From sports clubs to stock
companies: The financial structure of football in Spain 1992-2001.
European Sport Management Quarterly, 3, 253-269.
Garcia-del-Barrio, P., and Szymanski, S. (2009). Goal! Profit
maximization and win maximization in football leagues. Review of
Industrial Organization, 34, 45-68.
Gay Saludas, J. M. (2009a). Futbol & finanzas: La economia de
la liga de las estrellas (I). Radiografia economica del futbol espanol
(temporada 2006/07). Partida doble, No. 208, 62-89.
Gay Saludas, J. M. (2009b). Futbol & finanzas: La economia de
la liga de las estrellas (II). Radiografia economica del futbol espanol
(temporada 2006/07). Partida doble, No. 209, 62-87.
Grice, J. S., & Ingram, R. W. (2001). Test of the
generalizability of Altman's bankruptcy prediction model. Journal
of Business Research, 54, 53-61.
Hamil, S., & Walters, G. (2010). Financial performance in
English professional football: 'An inconvenient truth.' Soccer
& Society, 11, 354-372.
Kesenne, S. (1996). League management in professional team sports
with win maximizing clubs. European Journal for Sport Management, 2,
14-22.
Kesenne, S. (2000). Revenue sharing and competitive balance in
professional team sports, Journal of Sports Economics, 1, 56-65.
Kesenne, S. (2009). The financial situation of the Belgian
'Jupiler League': Are players overpaid in a win-maximization
league? Football and Finance Congress. Paderborn, 3-5 April.
Kuper, S., & Szymanski, S. (2009). Soccernomics: Why England
loses, why Germany and Brazil win, and why the US, Japan, Australia,
Turkey--and even Iraq--are destined to become the kings of the
world's most popular sport. New York, NY: Nation Books.
Lago, U., Simmons, R., & Szymanski, S. (2006). The financial
crisis in European football: An introduction. Journal of Sports
Economics, 7, 3-12.
Mora, A. M., Laredo, J. L. J., Castillo, P. A., & Merelo, J. J.
(2007). Predicting financial distress: A case study using
self-organizing maps. In F. Sandoval, A. Prieto, J. Cabestany & M.
Grana (Eds.), Computational and Ambient Intelligence: 9th International
Work-Conference on Artificial Neural Networks, IWANN 2007 (pp. 774-781).
Berlin-Heidelberg: Springer. DOI: 10.1007/978-3-540-73007-1_93.
Mourao, P. (2012). The indebtedness of Portuguese soccer teams:
Looking for determinants. Journal of Sports Sciences, 30, 1025-1035.
Noll, R. (2002). The economics of promotion and relegation in
sports leagues: The case of English football, Journal of Sports
Economics, 3, 169-203.
Perry, S., & Leach, S. (2011). The European club footballing
landscape: Club licensing benchmarking report FY2010. UEFA.
Perry, S., & Leach, S. (2012). The European club licensing
benchmarking report FY2011. UEFA.
Perry, S. (2009). The European club footballing landscape: Club
licensing benchmarking report FY2008. UEFA.
Perry, S. (2010). The European club footballing landscape: Club
licensing benchmarking report FY2009. UEFA.
Philosophov, L. V., & Philosophov, V. L. (2002). Corporate
bankruptcy prognosis: An attempt at a combined prediction of the
bankruptcy event and time interval of its occurrence. International
Review of Financial Analysis, 11, 375-406.
Pitrova, K. (2011). Possibilities of the Altman Zeta model
application to Czech firms. Ekonomika a Management, 3, 66-76.
Sloane, P. (1971). The economics of professional football: The
football club as a utility maximizer. Scottish Journal of Political
Economy, 17, 121-146.
Szymanski, S. (2010). The financial crisis and English football:
The dog that will not bark. International Journal of Sport Finance, 5,
28-40.
Szymanski, S., and Valletti, T. (2005). Promotion and relegation in
sporting contests, Rivista di Politica Economica, 95, 3-39.
UEFA (2010). UEFA Club licensing and financial fair play
regulations. Edition 2010. Nyon.
Angel Barajas ([dagger]) and Placido Rodriguez ([double dagger])
([dagger]) University of Vigo. Observatorio Economico del Deporte
([double dagger]) University of Oviedo. Observatorio Economico del
Deporte
Endnotes
(1) These clubs went under administration when they were at
Professional Football (First and Second Division A). Some of them are
playing in lower tiers.
(2) These criteria are going to be explained in detail in
Anticipating Financial Distress.
(3) For a detailed explanation of the financial ratios, see Altman
(2000).
(4) For an economic analysis of this, see Noll (2002) and Szymanski
and Valletti (2005).
(5) Sloane (1971) already pointed out that English clubs are not
profit maximizers. Franck (2010) asserts that "profit is a burden
on the spending power of the club, which deteriorates its competitive
advantage in the contest" (p. 110). In the same line, Franck (2013)
asserts that "the format of the competition in European football
helps to explain why football clubs are confronted with a typical arms
race environment. Over investment and gambling on [sporting] success are
to some extent 'normal' in this environment. They are
'normal' in the sense that even rational and profit-maximizing
clubs would engage in such dissipation of revenues" (p. 8). Thus,
if a club has as objective maximizing its profit, it can increase
revenues and/or reduce expenses. As in many cases, increasing revenues
is a difficult task; the option to get more profits is minimize
expenses. The main cost in a football club is related to the wages and
salaries. There is a strong correlation between them and the performance
in the pitch. For that reason it could be expected that maximizing
profit could result in a worse sporting performance and even in
relegation.
(6) Spanish Professional Football is organized by Liga de Futbol
Profesional (LFP). It includes the two top tiers. They used to be named
as Primera Division (First Division) and Segunda Division A (Second
Division A). In 2007, the LFP signed an agreement with one of the
biggest banks (BBVA) in order to name the First Division as Liga BBVA
and the Second Division A as Liga Adelante. It has become popular among
non-Spanish journalist and academics to refer to Spanish Professional
Football just as La Liga. Here we are going to use indistinctively:
First Division or Liga BBVA and Second Division A or Liga Adelante.
(7) Most of the clubs under administration entered in this
situation when they were in Liga Adelante or relegated to this division.
Usually, the main effect on financial ratios (mostly due to the
reduction of debt) is experienced in Second Division clubs.
(8) Note that for the financial year ending June 2011 accounts were
only available for 19 out 20 Liga BBVA clubs.
(9) Please note that the figures in Table 6 collate the total
losses of Spanish football clubs as there are no clubs that distribute
dividends. So retained earnings and profits or losses are the same
amount.
(10) Malaga went under administration in 2006. The club had to deal
with that stressful situation and tried to return to being managed,
avoiding losses and risky levels of leverage. From 2008, Malaga was able
to get profit during three years in a row with 24.6MM [euro] total
revenues on average during those years. But in 2011, with the
expectations generated by the new owner of the club, the wages and
salaries bill rose from 16.2MM [euro] in 2010 to 47.7MM [euro].
Consequently, terrible losses and new insolvency problems arose. And
with them, the correspondent sanctions were imposed UEFA.
(11) It is important to remark that the tax authorities
haven't given up on being paid. In some cases, they just agree to
new calendars of payments.
(12) The advantages of a reduction in the debt and longer terms for
the payments could suggest that clubs should try to enter under
administration. Nevertheless, there are some counterparts that managers
and owners have to take into account. For example, a new managerial team
or at least a supervisor can be appointed by the judge. This implies the
loss of control of the club and some hidden information can arise.
Moreover, criminal and civil responsibilities can be derived from the
process. It means that managers or directors can be prosecuted and they
could have to cover the credit with their own patrimony or even to enter
into prison.
Table 1: Number of Clubs in the Sample by
Year and Division
Liga BBVA Liga Adelante
2007 20 14
2008 19 16
2009 20 12
2010 20 17
2011 19 16
Source: Own elaboration
Table 2: Financial Ratios Evolution (Comparative 2008 vs. 2011)
TD/TA 2008 TD/TA 2011
Average 1st Division 0.81 1.25
nd Average 2nd Division A 2.83 1.42
TD/TR 2008 TD/TR 2011
Average 1st Division 1.61 1.93
nd Average 2nd Division A 2.27 2.16
Source: Barajas & Rodriguez (2010) and own elaboration
from annual accounts
Table 3: Summary of the Main Variables Average Values (Liga BBVA)
(Mill. TA CA Eq LTL CL
[euro])
2011 198.9 57.4 16.2 58.3 115.1
2010 185.6 51.6 10.3 53.5 111.7
2009 190.0 56.3 15.4 74.5 92.4
2008 197.6 60.7 17.8 61.3 88.6
2007 170.0 55.3 11.8 55.3 74.7
(Mill. TR W&S Amort. Net
[euro]) Profit
2011 83.5 53.9 18.5 -2.5
2010 77.3 48.4 19.5 -4.0
2009 70.8 46.9 18.3 -0.9
2008 66.6 46.9 18.7 3.4
2007 61.4 41.4 14.8 0.3
Source: Own elaboration from annual accounts
Table 4: Summary of the Main Variables Average Values
(Liga Adelante)
(Mill. TA CA Eq LTL CL
[euro])
2011 20.4 5.1 -12.6 15.5 11.6
2010 31.9 7.0 -9.2 18.4 12.7
2009 23.5 10.0 -8.4 10.5 19.1
2008 16.2 6.7 -12.6 12.5 10.0
2007 20.3 5.9 -7.0 6.6 14.3
(Mill. TR W&S Amort. Net
[euro]) Profit
2011 5.2 5.9 1.1 -4.5
2010 5.8 7.2 1.7 -4.2
2009 6.7 8.1 2.1 -3.0
2008 5.5 6.2 0.8 -1.4
2007 5.5 6.1 1.1 -3.3
Source: Own elaboration from annual accounts
Table 5: Percentage of Clubs with X1 (WC/TA)
Positive or Negative by Division at 2011
Liga BBVA Liga Adelante
[X.sub.1]>0 21.1% 37.5%
[X.sub.1]<0 78.9% 62.5%
Source: Own elaboration from annual accounts
Table 6: Percentage of Clubs with X2 (Retained
Earnings/TA) Positive or Negative by Division (2011)
Liga BBVA Liga Adelante
X2>0 47.4% 43.8%
X2<0 52.6% 56.3%
Source: Own elaboration from annual accounts
Table 7: Statistics of the Main Variables for Liga BBVA (2011)
Mean Standar Min. Max.
dev.
Current assets 57.4 68.9 4.6 204.7
Total assets 198.9 224.8 18.3 843.4
Equity 16.2 66.9 -71.7 245.0
Net profit -2.8 15.3 -43.9 31.4
Long term liabilities 58.3 63.4 7.6 238.1
Current liabilities 115.1 128.2 12.9 410.0
Wages & salaries 53.9 63.7 11.6 240.6
Amortization 18.5 25.9 0.9 104.5
Total revenues 83.5 125.5 18.1 445.5
Working capital -57.6 85.0 -302.1 30.5
TD/TA 1.0 0.5 0.6 2.7
Expenses on players/ 0.9 0.4 0.5 2.2
operating revenues
Source: Own elaboration from annual accounts
Table 8: Statistics of the Main Variables for Liga Adelante (2011)
Mean Standar Min. Max.
dev.
Current assets 5.1 3.1 1.2 11.4
Total assets 20.4 15.5 2.3 50.1
Equity -12.6 19.7 -67.1 6.0
Net profit -5.0 12.0 -36.0 2.6
Long term liabilities 15.5 21.9 0.0 83.4
Current liabilities 11.6 14.3 2.1 56.9
Wages & salaries 6.4 4.9 2.9 23.5
Amortization 1.1 2.0 0.0 8.0
Total revenues 5.7 2.9 2.9 15.4
Working capital -6.5 14.7 -53.5 6.8
TD/TA 1.5 1.3 0.3 5.7
Expenses on players/ 1.0 0.5 0.3 1.9
operating revenues
Source: Own elaboration from annual accounts
Table 9: Z-scores for Clubs in Liga BBVA Estimated
from Financial Data at June 30, 2011
CLUB Z [Z.sub.1]
LEVANTE 1.88 1.65
OSASUNA 0.60 0.51
VILLARREAL 0.31 0.20
UD ALMERIA 0.64 0.60
RCD MALLORCA 0.82 0.82
REAL MADRID 0.82 0.79
DEPORTIVO 0.23 0.26
DE LA CORUNA
SEVILLA 0.57 0.58
RCD ESPANYOL 0.04 0.11
REAL SOCIEDAD 0.31 0.40
ATLETICO MADRID -0.12 -0.02
SPORTING GIJON 1.00 1.21
FC BARCELONA 0.10 0.35
GETAFE -0.54 -0.31
ATH. CLUB DE BILBAO -0.46 -0.16
VALENCIA -0.48 -0.17
REAL ZARAGOZA -1.14 -0.73
MALAGA -3.83 -2.87
RACING SANTANDER -4.22 -2.95
CLUB [Z.sub.2] Status
LEVANTE 3.41 Safe
OSASUNA 0.92 Risk of Bankruptcy
VILLARREAL 0.53 Risk of Bankruptcy
UD ALMERIA 0.25 Risk of Bankruptcy
RCD MALLORCA 0.01 Risk of Bankruptcy
REAL MADRID -0.16 Risk of Bankruptcy
DEPORTIVO -0.67 Risk of Bankruptcy
DE LA CORUNA
SEVILLA -0.82 Risk of Bankruptcy
RCD ESPANYOL -0.98 Risk of Bankruptcy
REAL SOCIEDAD -1.14 Risk of Bankruptcy
ATLETICO MADRID -1.47 Risk of Bankruptcy
SPORTING GIJON -2.44 Risk of Bankruptcy
FC BARCELONA -3.27 Risk of Bankruptcy
GETAFE -3.59 Risk of Bankruptcy
ATH. CLUB DE BILBAO -3.95 Risk of Bankruptcy
VALENCIA -4.42 Risk of Bankruptcy
REAL ZARAGOZA -5.51 Risk of Bankruptcy
MALAGA -12.64 Risk of Bankruptcy
RACING SANTANDER -16.39 Risk of Bankruptcy
Source: Self production
Table 10: Z-scores for Clubs in Liga Adelante
Estimated from Financial Data at June 30, 2011
CLUB Z [Z.sub.1]
ALCORCON 4.07 3.94
GRANADA 1.92 1.56
NUMANCIA 2.07 1.54
HUESCA 1.91 1.54
GIMNASTIC 0.78 0.59
ELCHE 0.85 0.66
UD LAS PALMAS 0.51 0.46
CELTA DE VIGO 0.37 0.33
CARTAGENA 0.30 0.44
CORDOBA -0.38 -0.24
VALLADOLID -1.16 -0.88
XEREZ -1.45 -0.59
UD SALAMANCA -1.84 -1.00
BETIS -4.92 -4.00
RECREATIVO DE HUELVA -2.45 -1.45
RAYO VALLECANO -10.70 -8.23
CLUB [Z.sub.2] Status
ALCORCON 5.06 Safe
GRANADA 4.76 Safe
NUMANCIA 3.46 Safe
HUESCA 3.01 Safe
GIMNASTIC 2.56 Grey Zone
ELCHE 2.16 Grey Zone
UD LAS PALMAS 0.83 Risk of Bankruptcy
CELTA DE VIGO 0.42 Risk of Bankruptcy
CARTAGENA -2.35 Risk of Bankruptcy
CORDOBA -2.80 Risk of Bankruptcy
VALLADOLID -3.97 Risk of Bankruptcy
XEREZ -9.36 Risk of Bankruptcy
UD SALAMANCA -10.03 Risk of Bankruptcy
BETIS -11.58 Risk of Bankruptcy
RECREATIVO DE HUELVA -11.85 Risk of Bankruptcy
RAYO VALLECANO -32.72 Risk of Bankruptcy
Source: Own elaboration
Table 11: Z2 Scores of the Clubs that Entered under
Administration since 2007
Club Date of (2007) (2008) (2009)
administration
CELTA DE VIGO 2008 July -12.47 -0.57 n.a.
REAL SOCIEDAD 2008 July -2.48 n.a. n.a.
LEVANTE 2008 July -0.46 n.a. -0.96
REAL MURCIA 2009 February n.a. -5.61 -7.52
XEREZ 2009 November -92.69 -41.48 -56.47
ALBACETE 2010 April -6.20 -3.04 -9.72
MALLORCA 2010 June -2.35 -1.09 -2.18
RECREATIVO 2010 September -0.23 -1.17 -4.54
DE HUELVA
BETIS 2011 January 2.39 -2.06 -1.47
RACING DE 2011 July -0.18 -1.24 -0.85
SANTANDER
HERCULES 2011 July -53.87 -46.97 -102.41
CORDOBA 2011 June n.a. n.a. -6.44
RAYO VALLECANO 2011 June n.a. n.a. -3.06
REAL ZARAGOZA 2011 June -1.30 -2.01 -2.80
VALLADOLID 2012 January -3.38 -4.40 -2.15
DEPORTIVO DE 2012 November -0.05 -0.02 -0.56
LA CORUNA
Club Date of (2010) (2011)
administration
CELTA DE VIGO 2008 July -0.51 -0.02
REAL SOCIEDAD 2008 July -0.83 -1.67
LEVANTE 2008 July -0.37 3.58
REAL MURCIA 2009 February -3.43 n.a.
XEREZ 2009 November -9.70 -9.36
ALBACETE 2010 April -8.19 n.a.
MALLORCA 2010 June -3.63 -0.21
RECREATIVO 2010 September -12.81 -11.85
DE HUELVA
BETIS 2011 January -7.97 -11.62
RACING DE 2011 July -7.70 -16.46
SANTANDER
HERCULES 2011 July n.a. n.a.
CORDOBA 2011 June -2.11 -3.97
RAYO VALLECANO 2011 June -3.43 -32.78
REAL ZARAGOZA 2011 June -6.72 -5.51
VALLADOLID 2012 January -2.41 -3.97
DEPORTIVO DE 2012 November -0.38 -0.67
LA CORUNA
Source: Self production
Table 12: Summary of Average Needs to Get a Safe Financial
Situation by Division
(Mill. [euro]) [DELTA][nabla] [nabla]Debt [DELTA]LTL
Revenue
Average 1st div 3.8 13.6 8.6
Average 2nd div 5.9 0.2 2.4
(Mill. [euro]) [nabla] CL [DELTA]Equity
Average 1st div 22.1 31.7
Average 2nd div 2.6 12.6
Source: Own elaboration
