DETERMINANTS OF INTERNATIONAL SOCCER

PERFORMANCE IN THE FIFA WORLD CUP

Will Carpenter

[Pick the date]

A RESEARCH PAPER

Presented to

Dr. Peter Schuhmann of the Economics Department

The University of North Carolina Wilmington

By

William R F. Carpenter

Niels Sommerfeld

May 2014

DETERMINANTS OF INTERNATIONAL SOCCER

PERFORMANCE

Niels Sommerfeld & William Carpenter

University of North Carolina Wilmington

ABSTRACT

The FIFA World Cup is one of the most anticipated sporting events on earth. The purpose of

this research is to identify the determinants of international football team performance in the FIFA

World Cup. In addition to soccer-related statistics, we examine the relationship between a country’s

success in the FIFA World Cup and measures of wealth, culture and the popularity of international

football. Contrary to previous research, we find that nations do not need to be wealthy to have

success in the FIFA World Cup. We have found that countries with a cultural predisposition toward

football as their main sport and the popularity of football within the nation are more statistically

significant variables in describing a nation’s winning percentage than per capita wealth.

KEYWORDS: FIFA World Cup, Winning Percentage, Football Popularity, Culture Predisposition

TABLE OF CONTENTS

ABSTRACT…………………………………………………………………………… ii

ACKNOWLEDGEMENTS……………………………………………………………. iii

I. INTRODUCTION………………………………………………………… 1

II. LITERATURE REVIEW…………………………………………………. 2

III. DATA……………………………………………………………………… 3

IV. RESULTS…………………………………………………………………. 5

V. DISCUSSION……………………………………………………………... 7

VI. CONCLUSION……………………………………………………………. 8

VII. SOURCES…………………………………………………………………. 9

ACKNOWLEDGEMENTS

Conducting research and completing our paper has been a difficult although rewarding

process. We would like to thank Dr. Peter Schuhmann for sharing his knowledge and expertise in

Econometrics and advising us throughout the entire project. He offered productive criticism and

allowed us to understand a higher knowledge of uncovering relationships through econometric

methods, while making this research valuable yet gratifying.

INTRODUCTION

The Federation Internationale de Football Association (FIFA) sponsors what is considered

to be the most popular sporting event in the World: The FIFA World Cup. Founded in Paris on

May 21st, 1904, the FIFA World Cup is held every 4 years since 1930 except 1942 and

1946(WWII). In 2014 it will be held in Rio De Janero, Brazil. The anticipation for the 2014 World

Cup was a major contributor to why we are conducting this study. In preparation for the World

Cup, countries dedicate their most talented players and a large amount of resources towards their

country’s international squad. For this World Cup there were 208 nations who competed in

qualifying matches to set the stage for a 32-team tournament. According to FIFA, in 2006 there

were 265 million male and female soccer players or 4% of the World’s population. The Worldwide

popularity of this sport has fueled football into a billion dollar industry and success in the World

Cup can lead to positive externalities for a nation. The popularity of the sport is no secret. At the

2010 FIFA World Cup in South Africa at the stadiums alone there were over 750,000 liters of beer

and 390,600 hot dogs sold (FIFA). In addition to the popularity FIFA has become highly profitable,

with total revenue over 4 years of $4.189 billion and a profit of $631 million. With this kind of

money involved, nations with deeper pockets would be assumed to have an advantage because of

their ability to fund their programs and develop the best teams.

Football has become a worldwide sport and received international attention but the success

of each nation differs tremendously. Since the first World Cup in 1930 there have only been 2

continents in which countries have won the World Cup, South America and Europe. Within those

continents only 8 individual countries have won 19 World Cups with Brazil leading at 5 wins. Most

of the World champions were participants in the first World Cup in 1904, and have since been

frequent competitors in the World Cup. Empirical studies regarding football success are still

relatively scarce in the literature, only really gaining popularity in the late 1990s. Many of those

past studies have used measures of wealth to explain the relationship between a nations success in

the World Cup. However, our results suggest that a country’s cultural disposition towards football

and the sport’s popularity are more important factors of World Cup Performance than wealth.

LITERATURE REVIEW

There is a substantial amount of macro-level economic research for determinants

international football performance, including previous studies that examine the relationship

between economic, demographic, match play variables, and World Cup success. The existing

literature on these topics are reviewed in the following section.

Previous studies have also focused on the determinants of FIFA World Cup success as this

sport has seen a sharp increase in popularity from economists since the late 90s. Other studies have

used the dependent variables of the historical excellence at FIFA World Cup final tournament

(Torgler 2004) and FIFA World Ranking (Hoffman, Ging, and Ramasay). Yet, there is a

disadvantage of using the FIFA World Ranking as it only dates back 20 years and the World Cup

dates back to 1930. We have chosen to model all time winning percentage as we believe it best

describes World Cup performance, the reason they play is to win.

Hoffman et al. (2002) and Bernard and Busse (2000), respectively have previously studied

the determinants of International Football and Olympic success. Their research serves as a basis

for our hypotheses. Past results suggest that the size of a country’s population is not significant to

International Football success, but the size of Latin countries in which soccer is a large part of their

culture is significant. The rational being that the larger the population in a Latin country, the more

likely the sport chosen by young athletes will be soccer rather than other sports (Hoffman et al.,

2002). Further research on the Macro-level that determines Olympic success shows that GDP is

highly significant with medal shares for a country (Bernard and Busse 2000). Benard and Hoffman

have done a wonderful job in explaining the relationship between Macro elements and athletic

performance; however we find their work incomplete because popularity has not been addressed .

Therefore, the current study may require some modification. We also present an alternative

perspective on the importance of measures of wealth in regard to international sports performance.

Based on an analysis of socio-economic determinants of international soccer performance,

Name (year) r comes to two conclusions; First, that most countries spend a lot of national resources

on sports, a potential reason to limit to government spending. Also, the study offered a partial

explanation of football success and that government intervention could be beneficial because

widespread sports participation is good for a countries health and offers positive externalities

(Hoffman et al., 2002). We agree that widespread participation in the sport is good for a country’s

health but we do not believe that participation nor international success is caused by national

spending or a nation’s per capita wealth. We have hypothesized that the cultures that are

predisposed to football as their first sport with larger populations and football popularity will be

associated with international soccer success.

DATA

Data for every match that has occurred in each world cup from the first FIFA World Cup

in 1930 until the latest one in 2010 were obtained from FIFA.com. Statistics gathered applied to

every country that has participated in the World Cup events with at least 9 wins. Countries with

less than nine wins were excluded. Morocco, Saudi Arabia, and Tunsinia were not included due to

insufficient Macro level statistics. We have used statistics from England to represent the United

Kingdom because it is the largest country in the United Kingdom. This method has been used in

past studies (see Hoffmann, Ging and Ramasay 2002 and Torgler 2004) Hence, Northern Ireland,

Scotland and Whales were not included in our analysis since several of our independent variables

including GDP per capita, Population size and Viewership were only available at the UK level. In

addition, to match statistics for each qualifying country, we obtained statistics for major economic

variables that we hypothesize to affect team performance.

Our data consists of 40 countries from all around the world that meet the above criteria.

The determinants (X variables) are split into 2 separate categories that we perceive as having an

effect on the winning percentage (Y variable) of each country in the FIFA World Cup. The first

category involves match variables which include World Cup matches played, total amount of goals

scored against their team, total points, number of World Cup appearances, and the Golden Shoe

(Player on the team that has scored the most goals in each World Cup). The second category

involves socioeconomic variables that affect each country’s team, including percentage of world

cup viewership in 2010 (which indicates the amount of fans for each country’s team watched a

match for 20 or more consecutive minutes), Average temperature for each country (in Fahrenheit),

and Per Capita wealth. All the variables and there definitions can be seen in Table 1.

Table 1. Variable Names and Definitions

DEFINITIONS

Independent Variable

wPct

Dependent Variables

pctView

popLatin

popEuro

avgTemp

pcWealth

pcWealth2

Dummy Variable (1 = countries that have hosted at

least one World Cup since 1930)

host

Total population of a country in Europe

Annual average temperature of a country

Per capita wealth of a country

Quadratic Per capita wealth of a country

The total percentage a country's team has won

matches in the FIFA World Cup since 1930

Definitions

Total percentage amount of a country's population that

watch match for 20 or more consecutive minutes

Total population of a country in Latin America

Descriptive statistics for variables used in this study are shown in Table 1.2. Winning

Percentage on average is 0.37 with a range of 0.57, the minimum being 0.11 (Iran) and a maximum

of 0.6907 (Brazil) for the data set of our 41 observed countries. The average amount of percentage

World Cup viewership for each country is 63%. The country with the highest percentage World

Cup viewership is Japan with 86% and the country with the least percentage of viewership is

Cameroon with a low of 17%. The average per capita wealth in each country is $24,368. The

highest amount of per capita wealth by a country is $80,158 (Switzerland) and the lowest amount

is $1,205 (Cameroon). The average temperature in each country is 57 degrees Fahrenheit. The

highest average temperature in a country is 80.2 degrees Fahrenheit (Ghana) and the lowest average

temperature is 30.3 degrees (Russia). The average total population in Latin American countries are

about 11.8 million persons. The country with the highest amount of total population in Latin

America is Brazil with 202 million persons and the country with the lowest amount is Uruguay 3.3

million persons. Looking at total population in Europe, the average is about 14.3 million persons.

The country with the highest amount of total population in Europe is Turkey with 81.6 million

persons and the country with the lowest amount is Croatia with about 4.5 million persons.

Table 1.2. Descriptive Statistics

wpct PctView popLatin PopEuro host avgtemp pcwealth pcWealth2

Mean 0.3702 0.6323 11837334 14344671 0.3659 57 24369 1014065742

Standard Error 0.0216 0.0307 5801036 3729160 0.0762 2 3241 224991149

Median 0.3810 0.6795 0 4470534 0.0000 55 14831 219963432

Mode 0.5000 #N/A 0 0 0.0000 61 #N/A #N/A

Standard Deviation 0.1385 0.1967 37144751 23878272 0.4877 12 20754 1440646277

Sample Variance 0.0192 0.0387 1.37973E+15 5.70172E+14 0.237804878 139 430727510.5 2.07546E+18

Kurtosis -0.714 0.495 19.150 2.205 -1.754 -0.402 -0.212 4.043

Skewness 0.070 -1.300 4.230 1.846 0.578 0.243 0.905 1.911

Range 0.5796 0.6913 202656643 81619392 1 50 78953 6423951600

Minimum 0.1111 0.1639 0 0 0 30 1205 1452806

Maximum 0.6907 0.8552 202656643 81619392 1 80 80159 6425404407

Sum 15.1773 25.9259 485330698 588131518 15 2348 999125 41576695442

Count 41 41 41 41 41 41 41 41

Table 1.2 shows that the Skewness for World Cup Viewership is greater than 1, indicating

that the distribution on our data is far from symmetrical. Figure 1.1 shows a histogram in for World

Cup Viewership in 2010 by country, again revealing a right-skewed distribution due to a majority

countries having <10,000,000 viewers who watched a match for 20 or more consecutive minutes.

Figure 1.1 shows that there are a few outliers, Japan and Brazil, who each had over 100 million

viewers in 2010 causing us to create the interaction variable of Percentage viewership of a country

portraying the popularity of football by percentage of population in each nation.

RESULTS

To investigate empirically the economic determinants of success in FIFA World Cup, we

estimated a number of different regression models. In our model selection processes, we observed

a variety of issues and results from examining different combinations of variables. Equation (1)

below provides an overview of the model which involves all of the economic variables mentioned

in our data section that were used in previous studies and what we hypothesized would have a

strong relationship in winning percentage. Equation (1) was estimated using the Ordinary-Squares-

Least Squares technique:

= 0 + 1 + 2 + 3 + 4 + 5 ℎ + 6ℎ

where i indexes the countries in the sample. We first ran each independent variable individually to

test their significance on the dependent variable. The next step was adding each independent

variable one by one until we reached an equation with all independent variables included. This

resulted in an increase of the Adjusted R-square until we included average temperature, per capita

wealth, and dummy variable host.

Table 1. Regression Results

Note: *, **, and *** denote significance at the 10, 5, and 1% - levels respectively.

About 35% of the winning percentage for international football teams is explained by the

economic variables in the first regression. Note in Table 1, pctView, and popLatin are statistically

significant at the 5% level based on their respective t-statistics and p-value’s. Also note that

popEuro is statistically significant at the 1% level based on their respective t-statistic, suggesting

that this variable explains variation in winning percentage better than the population for countries

in Latin America.

The estimated coefficients can be interpreted as follows; for every country’s percentage

increase in World Cup match viewership, its football teams winning percentage increases by

0.213% while controlling for population increase in Latin America and Europe. If a country that is

located in Latin America can increase their population by 100,000 persons, its football teams

winning percentage increases by 0.001%, while controlling for percentage of viewership and

European population. Also, if a country that is located in Europe can increase their population by

100,000 persons, its football teams winning percentage increases by 0.0026%, while controlling

for percentage viewership and Latin American population. Our results indicated that Europe has a

stronger presence of football in their culture and therefore increases their chances on winning.

Variables Coefficients t Stat P-value

Intercept 0.1861961749 3.12696*** 0.00343

PctView 0.2132325629 2.27645** 0.02870

popLatin 0.0000000010 2.06675** 0.04581

PopEuro 0.0000000026 3.31413*** 0.00206

Adjusted R-Square = .34849

Table 2. Regression Results

Note: *, **, and *** denote significance at the 10, 5, and 1% - levels respectively.

Comparing regression results from Table 1 and Table 2, we observe that the Adjusted R-

Square has decreased to about 32% after adding the average temperature and per capita wealth of

each country, as well as the dummy variable host. Note in Table 2, host is not statistically significant

at any level based on their respective t-statistic and p-value. Also note that avgTemp, pcWealth,

and pcWealth2, are not statistically significant at any level based on their respective t-statistic and

p-value. This result indicates that countries that have hosted the FIFA World Cup in the past does

not have a strong impact on the winning percentage of a country’s football team. In contrast to

previous studies, the average temperature of a country throughout the year does not significantly

affect the performance of a country’s football team. Also, our results imply that the amount of per

capita wealth in each country does not have a strong relationship with the winning percentage of

their football team. Based on these results, we conclude the success of a country’s football team in

FIFA World Cup is mostly explained by the popularity of the sport in a country and its population

size rather than the average temperature, per capita wealth, and whether or not a country has hosted

a World Cup.

DISCUSSION

Variable Coefficients t Stat P-value

Intercept 0.2029085220 1.26147 0.21599

pctView 0.1589965703 1.40188 0.17029

popLatin 0.0000000013 2.23275** 0.03247

popEuro 0.0000000024 2.85661*** 0.00735

host -0.0376340053 -0.84699 0.40310

avgTemp -0.0004308493 -0.21082 0.83432

pcWealth 0.0000044548 1.16391 0.25281

pcWealth2 -0.0000000001 -1.01692 0.31659

Adjusted R-Square = .31466

Our results implty that the total percentage of a country’s population that watches a match

for 20 consecutive minutes or more has a strong association with the variation in winning

percentage. We also observe an interaction term between Latin American/European origin and

population size to be significant in our study, as reported. This implies that population size has no

impact on football performance if a country is not located in Latin America or Europe. The result

also indicates that the larger the population size for a country located in Latin America or Europe,

the higher winning percentage a country’s team will have, as football is a large part of the culture

in these countries. Increasing population is a benefit to these countries footballing success because

these people will more likely be engaged in football than any other sports, which would be the

opposite case in Olympics study, where a range of sports are concerned. (Bernard & Boose 2000).

If you are playing the odds in Vegas, you have a better chance of winning by picking a

country’s football team in Latin America or Europe. You will also increase your odds by picking a

team where soccer has a strong following within the country. Other researchers can use this

information to uncover the relationship between other sports and popularity. Governments can use

this information to identify how popularity of the sport within the country affects their team’s

football performance. With this information governments may choose to launch marketing

campaigns to improve the popularity of their football team which can lead to higher profits brought

into the country as well as creating other positive externalities, such as an increase in participation

with soccer therefore leading to a healthier population.

CONCLUSION

We derived our findings from an OLS multiple regression analysis. Our results can be

used to help explain the relationship between overall winning percentage and other socio-

economic variables. Our study has taken into account the past studies on both international

football success as well as Olympic success (Hoffman, et al). Previous studies have taken into

account specific football game statistics as well as other socioeconomic variables. However, the

past studies have not included popularity of the sport in countries that attracts the best talent,

coaches and resources. This study has shown that popularity, and the population size of countries

,which have a predisposed position to football in their culture, are more important than a

countries per capita wealth. Nations do not have to be in the best economic standing to have

experienced international football success in the FIFA World Cup. Future research could look

deeper into popularity and wealth variables to further prove this relationship.

SOURCES

Bernard, Andrew B., and Meghan R. Busse. "Who Wins The Olympic Games: Economic Resources

And Medal Totals." Review of Economics and Statistics 5.9 (): 413-417. Print.

Hoffmann, Robert, Lee Chew Ging, and Bala Ramasamy. "The Socio-Economic Determinants of

International Soccer Performance." Journal of Applied Economics V (): 253-272. Print.

Torgler, Benno. "'Historical Excellence' In Football World Cup Tournaments: Empirical Evidence With

Data From 1930 to 2002." Rivista di Diritto ed Economia dello Sport 2 (): 101-117. Print.