MASARYK UNIVERSITY FACULTY OF ECONOMICS AND ADMINISTRATION

Superstars’ wages in collective sports

MASTER THESIS

Mgr. Matej Drozd

Brno, 2016

MASARYKOVA UNIVERZITA Ekonomicko-správní fakulta

ZADÁNÍ DIPLOMOVÉ PRÁCE

Akademický rok: 2015/2016

Student: Mgr. Bc. Matej Drozd

Obor: Veřejná ekonomika a správa

Název práce: Superstars’ wages in collective sports

Název práce anglicky: Superstars’ wages in collective sports

Cíl práce, postup a použité metody: Theory suggests that an imperfect substitution of consumer preferences combi- ned with technology capable of duplicating an artist’s performance leads to out- sized rewards for a few superstars in mass entertainment businesses. This phe- nomenon is observed in the national sport leagues, where the best-performing sportsmen earn far higher wages than the average among their teammates. This thesis discusses the increase in wage inequality in the collective sports over the past decades. It includes empirical analysis testing whether superstars’ high wages can be attributed to the spread of communication technologies, which enable suppliers to reach a larger number of consumers. The application of results to different segments of economy will be discussed and motivate the policy debate on the justification of superstars’ wages.

Rozsah grafických prací: Podle pokynů vedoucího práce

Rozsah práce bez příloh: 60 – 80 stran

Literatura: LUCIFORA, Claudio a Rob SIMMONS. Superstar Effects in Sport: Evidence From Italian Soccer. Journal of Sports Economics, 2003, roč. 4, č. 1, s. 35-55.

HALL, Stephen, Stefan SZYMANSKI a Andrew S. ZIMBALIST. Testing Causality Between Team Performance and Payroll: The Cases of Major League Baseball and English Soccer. , 2002, roč. 3, č. 2, s. 149-168.

ROSEN, Sherwin. The Economics of Superstars. American Economic Review 71, American Economic Association, 1981, s. 845-858.

The wages of winstaking measure of the many myths in modern sport. Edited by David J. Berri - Martin B. Schmidt - Stacey L. Brook. Stanford, Calif.: Stanford Business Books, 2006. xiii, 282. ISBN 0804752877.

MANASSEA, Paolo a Alessandro TURRINI. Trade, wages, and ‘superstars’. Journal of International Economics, 2001, roč. 54, č. 1, s. 97–117.

Vedoucí práce: Mgr. Martin Guzi, Ph.D.

Pracoviště vedoucího práce: Katedra veřejné ekonomie

Strana 1 z 2 Datum zadání práce: 25. 5. 2015

Termín odevzdání diplomové práce a vložení do IS je uveden v platném harmonogramu akademického roku.

...... vedoucí katedry prof. Ing. Antonín Slaný, CSc. děkan

V Brně dne: 1. 5. 2016

Strana 2 z 2 Declaration

Hereby I declare that this paper is my original authorial work, which I have written on my own. All sources, references and literature used or excerpted during elaboration of this work are properly cited and listed in complete reference.

Mgr. Matej Drozd

Advisor: Mgr. Martin Guzi, Ph.D.

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Acknowledgement

I would like to thank Martin Guzi for his words of advice, professional leading and for giving me the opportunity to realize this thesis by agreeing to be my advisor. My deep gratitude belongs to all my lecturers from our faculty for their pedagogical work as well as for their patience and professionalism. Last but not least I would like to thank my family, friends and colleagues for supporting me, helping me, listening to me and standing by me during all my studies and writing of this thesis as well.

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Abstract

The aim of this thesis is to describe the superstar effect in collective sports. In collective sports there are individuals who are earning significantly higher salaries than other players. We are explaining this phenomenon using a superstar theory which we are further developing. The thesis explains why the technology is the main factor for the superstar effect. To confirm our theoretical assumptions we have analysed data from three sport leagues (English Premier League, National Hockey League and Major League Soccer) and by constructing econometric models we have observed that the empirical analysis supports the theory.

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Keywords competition, income, internet, popularity, salary, sport, superstar, technology, television, wealth

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„Football is very well remunerated at this level. It’s like we live in a bubble. With respect to the rest of society, we earn a ridiculous amount.”

Juan Mata, Manchester United Midfielder, earning £140,000 per week, in interview for the Spanish TV programme Salvados

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Table of Contents

Introduction ...... 1 Chapter 1. Nature of winning ...... 2 Chapter 2. Economics of Superstars ...... 5 2.1. Theoretical framework ...... 5 2.2. Superstar theory in a closed market ...... 6 2.3. Case study: Pelé, Ronaldo and the satellites ...... 7 Chapter 3. Major achievements in sports ...... 9 3.1. Individual competitions ...... 9 3.1.1. Boxing ...... 9 3.1.2. Tennis ...... 9 3.1.3. Golf ...... 10 3.2. Collective competitions ...... 10 3.2.1. Football (Soccer) ...... 11 3.2.2. Formula One...... 11 3.2.3. Baseball ...... 12 3.2.4. American Football ...... 12 3.2.5. Basketball ...... 13 3.2.6. Ice Hockey ...... 13 3.2.7. Rugby ...... 13 3.3. Sport support and public funding ...... 14 Chapter 4. Spread of multimedia and rise of wages ...... 15 4.1. Technology and wages ...... 15 4.2. Spread of television ...... 15 4.2.1. Development of satellite TV ...... 16 4.3. Rise of the Internet ...... 18 4.4. Sports broadcasting ...... 20 Chapter 5. English Premier League, MLS and NHL ...... 22 5.1. English Premier League ...... 22 5.1.1. Financial structure of the Premier League clubs ...... 24 5.2. Major League Soccer ...... 26 5.3. National Hockey League ...... 27 Chapter 6. Data collection for empirical analysis ...... 30 6.1. English Premier League ...... 30 6.2. Major League Soccer ...... 31

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6.3. National Hockey League ...... 33 6.4. Television and internet ...... 36 Chapter 7. Models from the empirical analysis ...... 37 7.1. Results ...... 37 Conclusion ...... 39 References ...... 40 List of Figures...... 52 List of tables ...... 53 List of appendices ...... 54

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Introduction

You probably know some of them. You heard about them, you read about them. You can see them on TV, in advertisements, when surfing the Internet. Superstars. Extremely popular, very talented individuals with the exceptionally high incomes even by the standards of their profession. Why do these talented actors, sportsmen, musicians generate such a huge income relative to the average wage in their field? The economic theory explains the phenomenon through the Theory of superstar. The seminal works by Sherwin Rosen and Moshe Adler suggest that the super high income of talented individuals can be explained by the increase of wealth in the society and the role of technology. The main goal of the thesis is to examine the existence of superstar wages in collective sports with a particular focus on the role of technology. Moreover, we are examining the existing theoretical framework of the superstar theory, eventually developing it with our own additions. The thesis is structured into seven chapters. In the first chapter we review works that describe the fundamental roots of competition, stressing that the competition is a part of genetic behaviour of all living beings. In the second chapter we describe the theoretical background of the superstar theory and we bring the case study to demonstrate the role of technology. We make an extension to the theory by describing the superstar effect in the closed market and the role of expected talent. The third chapter describes the achievements in collective and individual sports from the financial point of view. To illustrate the development of technology and to show the important milestones in technology development we discuss two most important technologies for sport broadcasting, the television and the internet in the fourth chapter. In this thesis we argue that the role of technology in the superstar theory is more significant than the role of wealth in society. Chapter five introduces the data from three sport leagues used in the analysis: the English Premier League (football), the North American National Hockey League (ice hockey) and the North American Major League Soccer (football). Understanding the most important restrictions and rules and therefore the differences between these leagues is important to understand the role of institutions (regulations, limitations). The sixth chapter introduces the data used in the empirical analysis. The data from different leagues allows us to differentiate the superstar effect in the free and regulated markets. In the last chapter we discuss findings from models with different set of explanatory variables. Results from the empirical analysis confirm the significant and positive impact of technology on the superstar wages in collective sports.

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Chapter 1. Nature of winning

Winning. We can hardly find someone who does not like the feeling of a win. But why? Why is winning so important it is deeply rooted in our human nature? It is not just the human nature which causes this need. Every living thing is struggling every day, every second to win. Living beings are struggling to win their place in the world, to win the moment and secure their living for a little longer. Life may be basically described as a competition. Those who win are those who survive. Charles Darwin calls it “The Struggle for existence” (Darwin, 1895). He uses it in large and metaphorical sense but the point is there. Living beings struggle all the time for food, for place, for the social interaction – with that for the opportunity to reproduce. In “The Descent of Man” Darwin states: “With social animals, the young males have to pass through many a contest before they win a female, and the older males have to retain their females by renewed battles. They have, also, in the case of mankind, to defend their females, as well as their young, from enemies of all kinds, and to hunt for their joint subsistence. But to avoid enemies or to attack them with success, to capture wild animals, and to fashion weapons, requires the aid of the higher mental faculties, namely, observation, reason, invention, or imagination.” (Darwin, 1871 p. 564). Famous biological phenomenon is Sperm Competition (Britannica, 2015) which is used for situation when two males are mating with one female. There are many tactics by which males are trying to secure their chance of reproduction, and to describe and examine them would probably make for a separate work. The famous British biologist Richard Dawkins has further developed these ideas. Darwin was thinking only about competition between higher living species. Dawkins goes to the very fundamentals of life. In his famous book “The Selfish Gene” he argues that even molecules are programmed to compete between themselves. Thus, the competition is rooted in our genes: “The next important link in the argument, one that Darwin himself laid stress on (although he was talking about animals and plants, not molecules) is competition. The primeval soup was not capable of supporting an infinite number of replicator molecules. For one thing, the earth's size is finite, but other limiting factors must also have been important.” (Dawkins, 1976 p. 18) Later in the same book he examines various examples of competition between species. In the tenth chapter Dawkins provides the example of stotting Thompson gazelles noticing the hunting lion. He explains the theory of Israeli evolutionary biologist Amotz Zahavi according which gazelles are showing which of them can jump higher. By this they do not want to impress other gazelles but they aim to show the lion which of them is harder to catch. The one which is the poorest jumper is also probably the easiest target. This might lead us to the biological way to answer the fundamental question: “Why do we like winning?” As all the species are competing so the humans are. To provide an examples from more recent studies, (Rhea, et al., 2003) shows that weightlifters are lifting 2kg more in average when competing with other weightlifters. Or the study (Cooke, et al., 2010) reported that male and female participants that were competing in groups of six were able to sustain the tight hand-grip for 21 seconds longer on average (which is about 22% increase) compared to those who challenged alone. Competition is leading us to better results. Is the cause psychological or is the reason much more genetic? Besides the difference in final results in hand-grip, (Cooke, et al., 2010) reported the increased heart rate, decreased heart rate variability and increased muscle activity. Providing such results may not be completely surprising considering the activity the competitors were performing. (Harrison, et al., 2001), however, made an experiment on 36 participants playing Scalextric toy car racing game in a competitive, a cooperation regime and in a single-player mode. During the

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Nature of winning competitive regime participants had higher blood pressure and heart rate as well as shortened cardiac pre-ejection period. How competitiveness affects our hormones was observed by (Suay, et al., 1999) who in their study compared judoists before, during and after competitive bouts against judoists performing non-competitive exercise. Suay and his team found that competing judoists had higher levels of testosterone and cortisol even before the bout and also after the performance. They also found that winners had higher levels of testosterone than losers. This difference was greater amongst men. Competition creates rivalry. Also rivalry can lead to better performances. (Kilduff, et al., 2010) analysed the rivalry between NCAA 1 basketball teams to confirm or disprove several hypotheses. (Kilduff, et al., 2010) confirmed that previous knowledge that rivalry is increasing the competition between two subjects, and the longer the rivalry has existed the stronger the impact is on the behaviour of competitors. For our work the most important finding is that in rivalrous competitive environment the competitors are getting better results than in standard competitive situations. In the results of their research they found slightly better statistical numbers in the matches between rivalrous basketball teams. All these researches are proving that humans are programmed for competition and rivalry. Nowadays, humans are not competing the way animals are. Is the genetically programmed competition affecting modern society? Some theories are explaining the development of human society as the competition. American urban sociologist Robert E. Park described four processes of interaction: competition, assimilation, conflict and accommodation – with the competition being “elementary, universal and fundamental form” of interaction. (Park, et al., 1921) Moreover, he writes that: “Competition is the process through which the distributive and ecological organization of society is created.”, and: “The division of labor and all the vast organized economic interdependence of individuals and groups of individuals characteristic of modern life are a product of competition.” (Park, et al., 1921). Thus, the elementary competition led us from struggle between molecules, through struggle between animals and human race as the developing species to modern, organized society. Principles are the same although the environment has changed. The competition can lead to better performances in various areas of human life. (Eisenberg, et al., 2011) performed an experiment where they played a piece of Prokofiev piano work to keyboardists and made them compete in improvisation. The improvised performances were more creative (but not more technical) than those of keyboardists who were improvising on their own. In sports there are no lions to eat the competitors. The losers will not die. The looser are, however, punished by loss of social status and by facing the criticism of fans. On the opposite, the winners are rewarded with money but also with social acknowledgement and, regarding the previous statements, they will be satisfied biologically as their existence is based on winning the competitions. We can observe competitiveness also in various areas of economy. Competitive markets are the most common example of such. Although it is an ideal model which, in real world, is much more complicated, one of the basic outcomes of such model is that subjects providing goods on the market can compete for the customer by lowering their prices to the levels of production expenses and also by continuous increase of the production effectiveness. These effects in much smaller scale are also in monopolistic and oligopolistic models but the difference against competitive markets is very significant. The difference is made right because of the competition. (Mankiw, 2014) Game theory is helping to describe some processes in economics. “Zero-sum is a situation in game theory in which one person’s gain is equivalent to another’s loss, so the net change in wealth or benefit is zero.” (Investopedia, 2015) Popular examples are poker and gambling. From the very

1 National Collegiate Athletic Association

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Chapter 1 basic point of view, when winning is considered as the one and only important feature, the sport is a zero-sum game as well. However, if we look at sports in more complex way and consider side effects of sports like money-generating, entertainment for masses, positive health effects and so on, the sports look more like a non-zero sum game. „Non-zero-sum games differ from zero-sum games in that there is no universally accepted solution. That is, there is no single optimal strategy that is preferable to all others, nor is there a predictable outcome.” (Chen, et al., 1998) Sure, in sports your primary goal is winning, but even losing may not mean that there was no positive outcome (financial or other) from the sport game or event for losers. Sometimes, the benefit of losing may be even greater than winning, for example when aiming for a specific spot in play-offs or when bribery takes its role. But we do not want to do an extensive discussion on this matter. We could further demonstrate some examples of competitiveness in the economic field. However, it is clear, that competitiveness is embedded in our genes and is affecting our behaviour and had a huge impact of society. Moreover, it is the competition which helps men doing greater performances and which is pushing forward the whole development of society and humans as such.

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Chapter 2. Economics of Superstars

In the first chapter we showed where the competitiveness is coming from and how it is affecting not only humans but living beings in general. We also mentioned some examples of competition in economy. In this chapter we will further examine the existing theoretical concepts which are explaining why there are so well paid individuals among us. This theory is called “the Economics of Superstars”. We will also provide an own extension to this theory.

2.1. Theoretical framework

(Rosen, 1981) was the first to introduce the term of “the Economics of Superstars” in a paper with the same name. Rosen explains the significantly higher earnings of exceptional individuals by having their product highly available for broad mass of consumers. Because consumers want the best possible product on the market, the product of an exceptional individual is massively consumed. Therefore, its price is rising. Rosen is not the first economist to come with such theory. Alfred Marshall wrote in 1890 that changes in technology and trade meant that “the operations in which a man exceptionally favoured by genius and good luck can take part are so extensive as to enable him to amass a large fortune with a rapidity hitherto unknown” (Marshall, 1890 p. 151). In fact he saw two causes behind this: general growth of wealth and “development of new facilities for communication by which men, who have once attained a commanding position, are enabled to apply their constructive or speculative genius to undertakings vaster, and extending over a wider area, than ever before” (Marshall, 1890 p. 151). Alfred Marshall did not call this phenomenon by the term “Superstar” but the basis for the theory was there. Rosen builds on Marshall’s work and uses the example of Mrs. Billington, who was an exceptional singer, and also had exceptional earnings through her carrier but since she lived at the beginning of the 19th century, there was no possibility to make her voice “available” for more listeners than for those who came to the Italian Opera in Covent Garden ad Drury Lane. He is comparing her to Pavarotti who has been earning millions through his carrier which is much more than Mrs. Billington, even adjusted by inflation. In the paper “The Economics of Superstars”, Rosen analyses two main premises for existence of the Superstar phenomenon. One of them is an imperfect substitution. In entertainment, the worse entertainer is a very bad substitution for a better one. You can listen to ten mediocre singers in row, but your needs will not be as satisfied as when you will listen to one great singer. Besides the personal taste, another factor is technology. A performer will always do one performance regardless of whether there are 10 or 1000 people to see it. Technology is helping talented individuals to cover greater parts of the market and address potential customers with minimal effort and additional expenses. Moreover, the ones who are unwilling to pay for the performance can be excluded from consumption. Moshe Adler further develops and extends this theory in his paper “Stardom and Talent” from 1985 (Adler, 1985). Adler looks more on the process of how the Superstar is born. He describes how knowledge of a customer is determining what performers he or she prefer. To search for the best performers the customer is making a research of market in a specific field he or she is interested in and due to limited time he or she can put in the consumption of the preferred good, the customer will stay with a small group of preferred performers. If the preference changes or a better performer appears, the selected group of artists/sportsmen will change. This theory is derived from application of the “consumption capital” theory by George Sigler and Gary Becker (Stigler, et al., 1977).

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Chapter 2

According to this theory the most popular performers are easiest to find, because when one is searching for the best fulfilment of his or her needs, they will probably start with the well-known ones. However, acquiring the knowledge of what is best suited for a consumer requires an extended interaction with other consumers and a market research. Adler indeed agrees that the talent is important. But the reason whether two performers with the same talent will become popular is attributed to luck, according to Adler. To illustrate his argument in regard to the previous article, imagine that we have a group of performers with the same talent. The preference over these performers is randomly distributed between customers. If there is one performer who only has a slightly higher share on the customer market than the others, in time this artist will snowball into a star. This is because other customers which preferred someone else will more likely get to know him and he will became part of their “consumption capital”. The more consumers will prefer this artist, the more likely the ones that do not know this performer will get to know him in shorter period of time. (Adler, 1985) In his conclusion, Adler notes that: “If there are stars, that is, artists that everybody is familiar with, a consumer would be better off patronizing these stars even if their art is not superior to that of others.” These two major papers by Rosen and Adler remain the fundamental basics for the superstar theory till nowadays. (MacDonald, 1987) explains his dynamic model on how young music artists may become stars. He examines the role of feedback from fans to artists. Since young artists are not so certain about their talent they start with small performances. With positive feedback a young artist starts to play in front of bigger audiences. The further the artist advances, the greater the requirements are. Here is where the talent factor comes. Therefore, more talented artists become stars and the less talented are coming off the market. MacDonald sees the earnings as an increasing convex function of an artist’s talent. However, he sees the function to have rather stochastic than deterministic properties which is in contrary to Rosen who sees it the other way. (Franck, 2001) also points out that superstars serve the role of quality assurance. He argues that we can expect from a superstar to maintain high level of given performances. Moreover, superstars themselves should control to what performances they are connected not to harm their reputation. E.g. when you are famous you have to maintain a certain level of quality. This is something MacDonald came in his work as well, that fans know that they can expect perfect quality from their favourites. Further developed, young artists may choose more technical or complex art to impress and find their position in the market among older performers with stable reputation. On the contrary older artists tend not to experiment too much and rather perform their normal standard not to harm their reputation as explained above. (MacDonald, 1987)

2.2. Superstar theory in a closed market

When we look at the previous article and apply it to sports, we can surely say, that sport stars are for certain assurers of certain high quality of sports game. The difference between arts and sports is in the role of subjective opinion. In arts you can hardly compare two artists by some objective measures and determine which one is better. The fame of artists is determined by the sum of subjective opinions which may be caused even by luck as (Adler, 1985) stated. In sports you can directly compare any sportsman or sport club by their performance in a sport game or event. Therefore, the luck factor goes more with the availability of facilities or financial background which can vary depending on, for example, where or to whom the sportsman was born. Even though the popularity may still be one of the factors for the sportsman salary, it is more likely to be determinant of the height of commercial endorsements, not the determinant of main salary from the sports performance although we do not disapprove that the popularity does have some effect on sportsman salary.

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Economics of Superstar

Sure, there are examples of players who were considered as exceptional talents and failed to prove so. For example in 1994, Glenn Robinson was the first player chosen on the NBA2 draft. Robinson, however, refused to play for the Milwaukee Bucks, the team that originally drafted him, unless Milwaukee offered him a huge contract. Robinson thus signed a contract that guaranteed him the salary close to the salary of Michael Jordan, maybe the best basketball player ever 3 . The difference was, that in 1995-1996 for each win that Jordan secured by best performance in the match, the Bulls “paid him” USD 150,000 (when we divide his salary to those matches). For each win that Robinson created the same way, the Bucks paid him USD 780,000. (Berri, et al., 2006) Can this be considered as a deviation to the theory presented above? We discussed that the talent is a determinant of the salary. In the free agent market in sports, there are players with various level of talent. Looking at the free agent market as a closed market, the players who are considered as the most talented will probably get the best offers. There are various ways how to determine the talent. (Berri, et al., 2006) in chapter six and seven examine the various ways of a player comparison to determine which player is better. However, there is usually no mathematical analysis when signing new players so the talent level and expected future performance is determined significantly subjectively by subjective measures using perception and previous experience of managers and sport scouts. In the 2000-2001 NHL4 season the previously rather average player Martin Lapointe, usually scoring about 6-16 goals per season, scored 27 goals and collected 57 points. 27 goals per season in NHL is good enough for a player of the second formation. The Boston Bruins owner Jeremy Jacobs saw the one season wonder as strong evidence that Martin Lapointe will be a good player in following seasons as well. So Jacobs offered Lapinte a four year contract for USD 20 million. The contract is considered to be one of the worst in the history of NHL as Mr. Lapointe only collected 82 points in total during his three-year stay at Bruins. (Sportak, 2004) The reason for such behaviour was that Martin Lapointe was considered by the Bruins owner as the most talented player on the market. On the NHL free market in 2001, Martin Lapointe was the Superstar according to Jeremy Jacobs. So was Glenn Richardson for Milwaukee Bucks on the 1994 NBA draft. Managers signed these players based on their potentially great performance as an assurance in the way (Franck, 2001) described. It is again about preference, trying to fulfil one’s needs in the best possible way with not a very good substitution. Every other available player on the market besides Lapointe or Richardson was seen as not good enough by Bruins and Milwaukee respectively. Therefore, if some player will get the good contract and he fails the expectations it does not mean that it is contrary to the theory. His predicted talent at the time of the contract signing was equal to the size of the contract. However, sometimes the predictions and expectations may go wrong. This also means that we do not need a huge market for the superstar effect to be observed. Consumers are able to find a superstar even in a relatively small group of performers (several tens of performers).

2.3. Case study: Pelé, Ronaldo and the satellites

In the previous subchapter we looked deeper at the application of the Superstar theory to sports and a free agent market. That part was more about the talent and the customer preference. We did not look at the technological factor which is, as we stated, one of the premises of the phenomenon.

2 National Basketball Association 3 Examples of lists where Michael Jordan is considered as best Basketball/NBA player ever: (Altenor, 2013), (ESPN.com , 2016), (McCallum, 2016) 4 National Hockey League

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Chapter 2

Why would Jeremy Jacobs even offer such money to Martin Lapointe? Current earnings of clubs are made from sponsoring, merchandise, tickets and TV rights. The total sum is usually determined by mid and long term performance of sports club, e.g. more successful clubs have higher revenues. Due to existence of technology which enables the broadcast of sport event to more fans, not just those watching the game directly on the stadium, the income of sport club is increasing. Higher salaries then allow higher wages of players. Mr. Jacobs was signing Martin Lapointe with belief that he will improve his team’s performance and, therefore, the Boston Bruins will be more attractive for fans (and sponsors). We know that the acquisition finally probably did not pay off. What is important is that technology enabled this high contract to happen. Then you have the case of Pelé and Ronaldo. In 1958 a football player named Pelé has made a debut on the World Cup. Only seventeen, he became an instant star. Every team on the planet wanted him on the roster. In 1960 he was reportedly paid USD 150,000 per year, which is, adjusted by inflation, about USD 1.,2 million in today’s money (The New York Times, 2010). Cristiano Ronaldo, today’s football superstar is, in comparison, paid about USD 1 million per week by Real Madrid, which makes 52 million per year. Is Ronaldo fifty times better than Pelé? Surely not. Is he even better than Pelé? Hard to say. Again the technology plays an important role here. In 1960, there was not any television satellite orbiting the earth. The first television satellite was released in 1962. The 1954 World Cup in Switzerland was the first one to be televised. But the first World Cup to be broadcasted as we know it, with the TV rights contract and quality of production and involvement of commercial TV was the 1966 World Cup in England. Despite mostly covering England itself, still, World Cup in 1958 and 1962, where Pelé won the first two of his three World Cup Champions trophies, could be only watched by visitors of the event on the stadium and a limited number of TV viewers. Thus, the number of spectators was 868,000 for 1958 in Sweden and 776,000 for 1962 in Chile (Statista, 2016). However, in 1966 there were not only 1,614,677 spectators watching games on stadiums (England had about twice as high attendance, probably due to better infrastructure) but also, due to better coverage and production, about 400 million television viewers. The contract was negotiated for USD 800,000 (Chisari, 2006). The 2014 World Cup in Brazil was watched by global in-home television audience of 3.2 billion people. The final match was watched by about 1 billion in-home viewers. Moreover, about 280 million people watched matches on mobile devices and via internet broadcasting (FIFA.com, 2015). This huge increase in audience can be credited to new technologies. All these viewers are consumers of a product which is produced by football players. Technology enabled this product to be consumed by so many consumers. The FIFA5 revenue generated by TV rights fees was USD 2.4 billion (Manfred, 2015). This is illustrating the implications we described in the previous subchapters. Technology enables greater consumption of the product, thus generating higher revenue, so that the producer can be paid much more. This explains why Ronaldo is paid much more than Pelé even if he is probably not a better player.

5 Fédération Internationale de Football Association

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Chapter 3. Major achievements in sports

We have already discussed what the success in sports means. For some individuals the success may be a long and happy career, for another one it might be winning the school championship. However, in this chapter we will show the most famous, important or money generating achievements in individual and collective sports.

3.1. Individual competitions

This work is focusing on collective sports but we will briefly introduce what we may consider as success in various individual sports.

3.1.1. Boxing

To describe the success in boxing in monetary terms is not trivial. Famous heavyweight boxer Wladimir Klitchko is among TOP 100 highest paid athletes, but according to Forbes he comes on the place #63 despite owning four of five heavyweight organisations titles and being the second longest reigning heavyweight champion. However, boxing is nowadays the most money-generating individual sport. It may be a surprise, but two highest-paid athletes in the world are welterweight boxers (Forbes, 2015). Income of Floyd Mayweather and Manny Pacquiao comes mainly from the salary and winnings. All eight athletes that are coming next on the list get more money from endorsements (usually advertising and contracts with manufacturers) than these two boxers. Forbes is stating: “Mayweather's May 2 fight against Manny Pacquiao crushed multiple boxing financial records, including PPV buys ($4.4 million), total gate ($73 million) and sponsorships ($13 million). The fight is expected to gross more than $600 million once everything is counted.” Despite Mayweather being a five-time division champion (winning five crowns, titles, medals, belts, or other distinctions) and winning twelve world titles, the most important for his success are individual matches, such as that with Pacquiao. Also, Mayweather has generated approximately $1,311,000,000 in pay-per-view6 revenue for service provision and $19,530,000 in pay-per-view buys throughout his career, surpassing the likes of former top pay-per-view attractions Mike Tyson or Lennox Lewis (data gathered from various pages of espn.com).

3.1.2. Tennis

During season, there are many tournaments, with the Grand Slams being the most lucrative and highest paid. Despite Wimbledon being the most famous and also most watched tennis tournament (Forbes, 2012) it is second in prize money of USD 42 million, while the US Open is the first with prize money of more than 42 million dollars. The Australian Open and French Open are third and fourth with 31 and 30 million respectively (Totalsportek2, 2015). To win the Wimbledon is the biggest achievement a tennis player can achieve during the season. Roger Federer, Novak Djokovič or Martina Navratilova sees this event as the most famous one. To win US Open means to win the most of the money. US Open not just guarantees the highest prize money for the winner but also the most prize money in total.

6 Satellite or cable TV service which charges viewers a fee (in addition to the fixed monthly charge) for viewing special programs such as sports events. (Business Dictionary, 2016)

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Major achievements in sports

Aside of the every-year tennis calendar, there are the Olympics. The finals of 2012 men’s Olympic tennis tournament were watched in the USA by two times more viewers than 2012 men’s Wimbledon finals (Willis, 2012). However, the prize money for winning the gold medal at the Olympics in London 2012 was “just” USD 25,000 USD (Zillman, 2014).

3.1.3. Golf

Golf belongs to the best paid individual sports. Golf player Tiger Woods has earned the most money amongst all athletes over the last 10 years – USD 845 million in total. Sure, when we account only income from sport events we get only 1/10 of the total earnings (Badenhausen, 2015). But still, the winner of FedEx Cup, the final cup of the season gets USD 10 million (Porter, 2015), which is 3-5 times more than the main prize from any Grand Slam tennis tournament. Total prize money of the FedEx Cup is smaller than in the US Open or Australian Open (USD 35 million). When we look at the total income of athletes from the last 10 years: Tiger Woods has made the most money from all sportsmen during that time and his PGA7 tour colleague Phil Mickelson is on the fifth place. Boxers Mayweather and Pacquiao are on the second and eight places respectively and the best paid tennis player Roger Federer is the sixth, while another tennis player Rafael Nadal is the seventeenth. The whole list can be found in Table 1(Badenhausen, 2015). From this we can assume, that golf may be the most prestigious individual sport in the past ten years.

PLACE NAME SPORT EARNINGS OVER PAST 10 YEARS 1 Tiger Woods Golf 845 million USD 2 Floyd Mayweather Box 660 million USD 3 Kobe Bryant Basketball 475 million USD 4 LeBron James Basketball 472 million USD 5 Phil Mickelson Golf 468 million USD 6 Roger Federer Tennis 455 million USD 7 David Beckham Football 441 million USD 8 Manny Pacquiao Box 432 million USD 9 Cristiano Ronaldo Football 407 million USD 10 Lionel Messi Football 350 million USD 11 Alex Rodriguez Baseball 291 million USD 12 Fernando Alonso F1 289 million USD 13 Dale Earnhardt, Jr. NASCAR 277 million USD 14 Valentino Rossi Moto GP 275 million USD 15 Derek Jeter Baseball 271 million USD 16 Kimi Raikkonen F1 261 million USD 17 Rafael Nadal Tennis 253 million USD 18 Maria Sharapova Tennis 250 million USD 19 Lewis Hamilton F1 246 million USD 20 Peyton Manning American Football 243 million USD Table 1: Sports top earners over past 10 years. Source: (Badenhausen, 2015)

3.2. Collective competitions

In collective sports, individuals usually earn regular salary. Performance bonuses are also part of the salary, usually as a financial bonus provided as an addition to the regular salary. Individuals usually do not have any performance bonuses directly paid to them by competition organizers. Sportsmen

7 Professional Golfers' Association

10

Chapter 3 earn their salary based on their contract. For this reason we included Formula One in collective sports, not in the individual ones, because there is no prize money for successful drivers other than salary bonuses paid to drivers by their team. Bonus is only given to the team for their overall performance. Also, we are not mentioning some famous sport contracts even if in Table 1 we can see that basketball, football, F1 and baseball players are among the best paid sportsmen in the world. However, in long term their salary is usually determined by the team performance. Even if an individual can surely attribute to the team success, a highly performing individual in an underperforming club is more likely to move to a more successful organisation.

3.2.1. Football (Soccer)

Soccer is arguably the most popular sport in the world. It’s probably because you need only a ball, legs and a place to play. Many sports are popular only in certain areas of the world. But football is a worldwide phenomenon. FIFA World Cup (WC) is the most watched sports event in the world, surpassing even the Olympics, while the UEFA Champions League (CL) is the fourth and the FIFA Confederations cup is the fifth (Waugh, 2015). That means three out of five most-watched sporting events in TV history are football events. The number of cumulative watchers is 1.7 billion for UEFA CL and 3.5 billion for FIFA WC. Despite being less popular, the prize money for UEFA CL is much bigger than that for FIFA World Cup. There are bonuses for each match in CL and also for each stage the team will advance. In comparison, prize money in WC is only given by the final standing of a team. The winner of the World Cup takes USD 35 mil. (Arshad, 2014) in comparison with the winner of the Champions League which takes EUR 15 mil.. However, when taking into account the bonuses from all matches and rounds, the winning team can earn EUR 50 to 54 mil plus the Market pool money to elevate the possible total to EUR 100 mil. (Totalsportek, 2015). In total, the Champions League has a prize fund of EUR 1.1 billion compared to USD 324 million for the competing teams of the World Cup (Thomsen, 2015).

3.2.2. Formula One

Formula One is one of the most expensive sports, if not the most expensive sport in the world in terms of costs required to participate. Budget of some Formula One teams is comparable to that of the biggest football teams. For example, the budget of Red Bull racing team for 2015 season is according the Business Book GP estimated as EUR 468.7 million (Crash.net, 2015) which is almost as high as the 2014 budget of EUR 509 million EUR of currently the second most valuable football and the fourth most valuable sport team of the world (being second in 2014) Barcelona (Badenhausen, 2015) (FCBARCELONA.CAT, 2013). Sure, the budget of Formula One teams ranges from EUR 80 mil. to the aforementioned 468.7 mil., but so does the budget of Spanish football teams range from EUR 18 million to 509 mil. (Classora, 2014). And with the budget of EUR 80 mil., the Manor Formula One team ties with the FC Sevilla on the fifth place in La Liga who are the winners of UEFA Europa League, the second most prestigious European club trophy. Why is Formula One not included in individual sports? F1 drivers have fixed salaries which do not depend on winning. Sure, the salary is based on the driver’s success in previous years, but the season bonuses and prize money apply only to the team performance, thus we included Formula One in collective sports. It is like sports team winning the trophy with one player as the best scorer of the tournament.

11

Major achievements in sports

The prize money system and the money distribution system in general in Formula One is rather complicated. There is an operating profit of Commercial Rights Holder Group which divides 50:50 between Formula One Group and F1 Teams. From Formula One Group budget the Constructor’s championship fund is financed. And there are also historical payments to Mercedes and Williams. Budget of Formula 1 teams is split in equal shares and performance bonuses, again 50:50. Moreover, Ferrari gets 2.5% from both Formula One Group and F1 Teams, thus 5% of the whole operating profit as an acknowledgement of Ferrari’s importance to the sport. Complete diagram can be seen bellow with numbers of 2013:

Figure 1: Distribution of profit in Formula One. Source: (Totalsportek, 2015)

Thus, if we do not count Ferrari’s 90 million USD of fixed income, the prize money of one F1 team can be more than USD 100 million from the Formula 1 Teams budget and with the prize from the Constructor’s Championship fund it can be theoretically more than USD 200 mil. in total. (Totalsportek, 2015)

3.2.3. Baseball

The Major League Baseball in the United States is the most prominent baseball league. Amongst the most popular sports in the USA (baseball, basketball, American football, ice-hockey) it is the baseball league, which comes with the biggest prize money for the final tournament of the season. The World Series, the best-of-seven series of matches between the winner of the National League and the American League (which together are creating the MLB) promises to the winning team more than USD 22 million (Axisa, 2014). Overall, the Baseball offseason comes with USD 66 mil. prize pool.

3.2.4. American Football

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Chapter 3

American football, as the name suggests, is a sport competition based in the USA. Therefore, the most important sport event is the playoff final of the American NFL league – the Super Bowl. Although there are some debates about the impact of the Super Bowl (Matheson, et al., 2004), it is still arguably the biggest sporting event in the North America, with the expected economic impact in 2015 to be as high as USD 500 mil.. A 30-second advertising spot during the Super Bowl finals costs USD 4.5 million (Smith, 2015). It is important to point out that with the Super Bowl finals we are talking about one match, not a series as it is usual in other sports. Considered as an unofficial national holiday in the USA, the number of Super Bowl watchers increases every year, with 114.4 million in 2015 (Statista, 2015). It may be surprising then, that the Super Bowl has not the highest prize money of all sports events in the North America. Considering the size of a team, USD 11 million for the winning team (Thomsen, 2015), when divided between players, makes the prize money per player the third best after MLB and NBA (Golden, 2015).

Bonuses in 2014-2015 for the Per player (USD) Number of players World Championship in a squad Baseball MLB 388,606 40 Basketball NBA 275,000 13 American Football NFL 165,000 53 Ice Hockey NHL 100,000 23 Table 2: Bonuses in 2014-2015 for the World Championship per player. Source: (Golden, 2015) 3.2.5. Basketball

The most prestigious and arguably the best basketball league in the world, is the North American National Basketball Association (NBA). Then it might be a surprise, if we look at the prize money, where in 2014 the winner of the league playoffs San Antonio Spurs got USD 4,104,811 and the runnerup Miami Heat took USD 3,631,684. Also the total prize pool for NBA playoffs relatively dwarfs beside other leagues with USD 14 million (Chiari, 2014). The reason why the individual prize money is still relatively high compared to other sports in the US is that NBA team’s rosters are limited to 13 players (Sheridan, 2012), which is much less than in other sports: 40 players in MLB (Baseball Almanac, 2015), 53 in NFL team’s roster (Lillibridge, 2013), 23 in NHL (NHL.com, 2015). Thus when a team divides the total prize money between its players, NBA players get the relatively high individual salary compared to other collective sports in the USA. Popularity of NBA finals is rising with averaged 19.94 million viewers per final game (Rovell, 2015).

3.2.6. Ice Hockey

Ice Hockey and its National Hockey League is the least popular of the four major US leagues. Yet, NHL is arguably the best hockey league in the world with a little competition by Eurasian KHL. When looking closer at the prize money of NHL playoffs, it is more comparable to the prize money of the US Open more than that of other collective sports in the USA. Despite doubling the prize money in 2013, the winner of the Stanley Cup takes “only” USD 3.75 million and the total prize money is USD 13 million for the whole play off (Johnston, 2013).

3.2.7. Rugby

13

Major achievements in sports

A specific of the Rugby World Cup is that there is no prize money from the tournament. Instead, each national team is awarded with the money from its national rugby association. There are bonuses per player and the numbers are comparable to those from Table 2, for example winners from New Zealand getting USD 250,000 or England getting USD 350,000 for each player. National rugby associations then divide the revenue according to undisclosed percentage. (Totalsportek, 2015)

3.3. Sport support and public funding

There is a relationship between private sport clubs and public funding. There are public subsidiaries for certain activities and of course, sport organisations are paying taxes. In the United Kingdom the government is co-funding sports via the Sport England organisation (Gov.uk, 2016) but as stated in the official information of the organisation (Sport England, 2016) £ 324.9 million are invested in non-profit sports, sport communities, talent development, administration and facility development. For example, there is cooperation between the Sport England and the Football Association of England to build grassroots in England (Bond, 2014). But private clubs are not usually co-funded from private funds, unless there is any public interest (Waldron, 2014). For example, Manchester City received USD 170 million from public funds to build Etihad Stadium because the grounds were built to host the Commonwealth games (Conn, 2013). Another example is West Ham United which will play for two years on a national stadium but the club has to pay a part of maintenance (Gibson, 2014). Tottenham London is receiving tax subventions (Conn, 2013). On the opposite, Arsenal London built its Emirates Stadium using only private funding (with a 30-year mortgage of USD 420 million) (Cameron, 2005). Another way of public funding in the United Kingdom is via the UK Sport, a government organisation. The UK Sport is funding athletes, coaches and sport organisations using funds from the Ministry of Sports and the National Lottery. The complete system of funding can be found on (UK Sport, 2015) and the diagram of funding in Appendix 1. We will not examine the UK Sport further in this work because it is not supporting the sport structures we are examining. Contrarily to the UK where there is minimal public funding of private clubs, in the USA the public funding of private stadiums is usual. During the last 15 years the government has spent USD 12 billion of public money on privately owned stadiums. Even if there are several studies that show that private stadiums are not a good investment for the government, these plans are backed also by the public opinion (Heller, 2015). As for the income tax from the Premier League football clubs´ revenues, it was £ 25.4 million in 2015 (O’Connor, 2016), (own calculation). Considering practically non-existent public funding of sport clubs in the UK, the incomes to public funds are extending the public expenses.

14

Chapter 4. Spread of multimedia and rise of wages

As we write in the second chapter, according to (Rosen, 1981) there are two reasons for the superstar effect in economy. One is an increase of wealth in the society, the other is the rise of new technology. And by technology we will mainly mean multimedia, because that is the part of technology which enables more users to “consume” the “product” of famous people, of whom we are interested in sportsmen. In this chapter we will argue that technology is the main reason for the superstar effect, because of how technology affected the total wealth in the society. With technology having the main impact on superstar wages we will go through the history of two most important technologies to enable consumers from around the world to consume the product of sportsmen: the television and the internet. We have to describe the historical development of these technologies to observe how the effect of the technologies in the superstar theory was changing in time. It will help us to create the timeframe.

4.1. Technology and wages

Is the technology a complement to personal skills? There are two views of the relationship between skills and technology (Caselli, et al., 2001). One sees it as the “skill in adoption”, where educated workforce is always a critical factor in new technology adoption. Thus, the adoption of any new technology depends on human capital, and the role of human capital becomes less important over time. The second view sees this as a “skill in use” and argues that certain technologies are inherently skill biased, e.g. complementary with educated workers. In this case only adoption of skill-biased technology depends on human capital. In this theory the role of human capital also will not diminish over time (Caselli, et al., 2001). Caselli, et al. stated in 2001 that there is no study that shows which of these theories is more likely to be true. We were unable to find any newer study on this matter. Moreover, some studies like (Acemoglu, 1998) show that the new technology is a complement to skills, but cannot fully explain the reason why it is that. What is important for us is that literature suggests that technology is increasing the wage of skilled workers. Again, if we go back to the two reasons given by Rosen about why the superstar effect occurs, we see that one is about the technology and second about the increase of wealth. But as we explained above, the new technology also contributes to a wage increase mainly in higher educated workers. The consequent effect is increase of wealth in the society. Therefore, technology can be seen as the most important reason of the superstar effect, when positively affecting the second main reason as well.

4.2. Spread of television

The history of technology that led to the television dates from late 1800s when a German student, Paul Gottlieb Nipkow developed the first ever mechanical module of television. With the help of a rotating metal disk he sent images through the wires. At that time it was called the “electric telescope”. In 1907 an English inventor A.A. Campbell-Swinton and a Russian scientist Boris Rosing at the same time though separately, added a cathode ray tube to the metal disk and created a television system. (Jezek, 2015) In 1923 an American inventor Charles Jenkins invented the first ever practical mechanical television system based on Nipkow’s idea. His Radiovisor Model 100 was being sold as a complete kit of mechanical television, starting in 1931. In 1926, John Logie Baird, a British inventor has

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Chapter 4 succeeded in transmitting moving pictures through the mechanical disk system designed by Nipkow. Later, he started the first ever TV studio. (Jezek, 2015) By 1934 all mechanical systems had converted into an electronic system. The electronic system foundation was placed in 1907 with the cathode ray tube, but it was a 21-year-old student Philo Taylor Farnsworth 20 years later who was able to capture moving images with a beam of electrons which was a direct ancestor to modern television. RCA which had dominated the radio business at that time invested USD 50 million in development of an electronic television. In 1939, RCA8 televised the opening of the New York World’s Fair, including a speech by President Franklin Delano Roosevelt, who was the first president to appear on television. Next year, RCA paid the license for Fainsworth’s television and started selling electronic television sets. The first had 12.7 by 24.4 cm picture tubes. The company also began broadcasting regular programs and started using a mobile unit. BBC started regular transmissions even sooner. Since 1936 they started broadcasting from Alexandra Palace in London. Broadcast only reached about 100 television sets in the South-East England. (BBC, 2016) In 1939 the seven-day TV broadcast started. (BBC, 2016) The first newscasts in the USA started in 1941 by the Columbia Broadcasting System (CBS). In 1943 RCA had to sell one of its two radio networks and the new network became the American Broadcasting Company (ABC). Full- scale commercial television broadcasting did not begin in the United States until 1947. (Stephens, 1998) Number of television sets in the United States rose sharply from 6,000 in 1946 to around 12 million by 1951. By 1955 half of the US homes had one black and white TV which makes about 24 million TV sets (Infoplease, 2008). The coronation of Queen Elizabeth II in 1953 was the turning point for the television in Britain and probably in the world. Many from 22 million watchers cited that the coronation was the reason for purchase of a television set. This was the first time that the television audience outnumbered that of the radio. (BBC, 2016) The first mechanical colour television system was developed by John Logie Baird in 1928. In early 1940s CBS pioneered the three colour transmission system. The Federal Communications Commission (FCC) tested the CBS system, along with the compatible system by RCA. The electronic-mechanical CBS system was adopted in 1951, but it was the upgraded, all-electronic, RCA system which was adopted as a standard in 1953 (later known as NTSC system). Colour TV systems began to be sold at that time but due to the lack of content, high price and low reliability, the sales were relatively low with only 150,000 of colour TV sets sold at the end of 1957. By solving the mentioned problems of colour TV system in the 1960s the sales began to rise and sales of the colour TV system exceeded the sales of the black and white system for the first time in 1970. (Early Television Museum, 2016)

4.2.1. Development of satellite TV

In 1945 Sir Arthur C. Clarke proposed a global satellite communication system (Clarke, 1945), an idea for which he won the Stuart Ballantine Medal9 in 1963 (The Franklin Institute, 2016). The first TV satellite, Telstar, built by AT&T was launched on 10th of July, 1962 from Cape Canaveral atop of a NASA Thor-Delta Rocket. After a successful test of transmission, the first public transmission was done on 23rd of July of the same year. About 100 million people in Europe were watching alive,

8 Radio Corporation of America 9 A science and engineering award presented by the Franklin Institute, of Philadelphia, Pennsylvania, USA. It was named after the US inventor Stuart Ballantine.

16

Spread of multimedia and rise of wages black and white broadcast of the Statue of Liberty in New York, then legendary newsman Walter Cronkite intoned: “Good evening, Europe. This is the North American continent live via AT&T Telstar, July 23, 1962.” Next the broadcast of a baseball game was shown and the broadcast was concluded with President’s John F. Kennedy press conference. Only a 20-minute broadcast at the time was possible during the window in each two-and-a-half hour long orbit. (Klein, 2012) The first geosynchronous satellite was Syncom 2, launched by NASA from Cape Canaveral on 26th of July 1963. It was an experimental satellite, placed over the Atlantic Ocean and Brazil. It began its regular service on 16th of August and it was handed over to the Department of Defense of the USA on 1st of January 1965. (Darcey, 2016) The first commercial communications satellite was Intelsat 1, launched into synchronous orbit on 6th of April 1965, placed in commercial service on 28th of June. It was built for the Communications Satellite Corporation (COMSAT) by the Space and Communications Group of Hughes Aircraft Company (currently Boeing). It was in service for 3.5 years. (Krebs, 2014) Despite the United States launching the first satellite, it was the Soviet Union, which established the first analogue satellite network in 1967 (Windstream, 2016) called Orbita and using Molniya satellites to cover the whole country with satellite TV broadcast (The Moscow Times, 2016). The first Canadian satellite used for TV broadcasts was called Anik 1 and was not used until 1972, almost 5 years later than the original Soviet network launch. (Windstream, 2016) At that time the satellite dishes had several feet in diameter and for many people, especially in rural areas it was too complicated to receive a signal from satellite. (Tech-FAQ, 2015) The direct to home satellite dishes started to prevail in the beginning of 1980’s. It was, again, the Soviet Union, which launched the first satellite of the Ekran system (a.k.a. Stationar-T) on 26th of October 1976 (Encyclopedia Astronautica, 2016). It was the first Soviet geosynchronous satellite but also the world’s first direct-to-home TV service satellite, providing colour television broadcast to Siberia and the Far North. The Ekran system was accepted to operational service in 1980 and consisted of 18 satellites. (Krebs, 2015) The last one was launched on 6th of May, 1988. (Encyclopedia Astronautica, 2016) With direct-to-home satellite systems, anyone could receive the satellite TV broadcast, which made television companies go to the court with attempts to restrict the TV signal. However, the newly established Federal Communications Commission opposed TV companies with the “open skies” policy. Therefore, TV broadcasters decided to start with encryption of the signal. Since then, not only a satellite dish was required but also a special equipment to decrypt the signal of many commercial television channels. (Tech-FAQ, 2015) In 1990, National Broadcasting Co., Hughes Communications, Rupert Murchdoch’s News Corp. and Cablevision Systems co-created a 1 billion USD satellite venture which had to be received by personal satellite dishes (Richter, 1990). Hughes failed in creating the venture and Sky Cable was launched in 1990 as the first high-power digital television service. Then, in 1994, DirecTV satellite service was launched, providing service for North America and Caribbean and reaching one million customers in 1995, ten million in 2001 and becoming the world’s largest pay-TV provider with more than 27.5 million customers (DirecTV, 2016). The difference was that DirecTV was focusing more on small customers with small satellite dishes. The importance of satellites for this paper is that satellites made the television broadcast global. Thanks to the satellite systems we are able to watch almost any TV broadcast at any place in the world. That means, we may consider any owner of a TV set to be able to receive for example some of the mentioned sport broadcasts and thus to become one of the “consumers” in our Superstar theory. In 2011 there was an estimated number of 1.6 billion TV sets in use in the world, serving a viewing audience of 4.2 billion people. (Ahonen, 2011) During the last five years the numbers might very likely rise. This is the rise of the technology we described in Chapter 2.

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Chapter 4

4.3. Rise of the Internet

It is hard to determine where the idea of the Internet begun. According to (Leiner, et al., 2016) from the Internet Society, the description of social interactions which may be enabled through networking were described by J.C.R. Lickinder from MIT10 in a series of memos (Licklider, et al., 1962) from August 1962. (History.com Staff, 2010) states that the proposal was a reaction to fear of US scientists and military that the whole nation’s communication network (e.g. telephone) might be easily destroyed with a Soviet attack. Lickinder then proposed a “Galactic Network” of computers that could talk to each other. He then became the first head of the computer research program in DARPA11 (ARPA at that time), starting in October 1962. While at the company, he convinced his colleagues about the importance of the networking concept. (Leiner, et al., 2016) Significant improvement was the introduction of packet switching theory by Leonard Kleinrock from MIT in his paper "Information Flow in Large Communication Nets" (Kleinrock, 1961) and later the book Stochastic Message Flow and Delay (Kleinrock, 1964). He and MIT researchers working for DARPA, Lawrence G. Roberts and Thomas Merrill connected TX-2 computer in Massachusetts with Q-32 in California with low speed dial-up telephone creating the first wide-area computer network ever in 1965 (Roberts, et al., 1966). Roberts had started planning his “ARPANET” since 1966 and described it in his work “Multiple Computer Networks and Intercomputer Communication“ (Roberts, 1967). However, at the same conference, there was another paper on the packet network concept from the UK by Donald Davies and Roger Scantlebury (Leiner, et al., 2016). There was also a third paper on the similar topic with a paper on packet switching networks for secure voice in military by Paul Baran’s group from RAND (Baran, 1964). So it happened that three groups of researches worked in parallel on the same topic without knowing about each other. Also the word “packet”12 was adapted from the NPL’s paper. Using some of the insights from other works, Roberts worked on the ARPANET which was brought online in 1969 under a contract let by DARPA and it connected four major computers at universities in the southwestern US – UCLA 13 , Stanford Research Institute, UCSB 14 and the University of Utah (Howe, 2014). The first communication over the ARPANET was between UCLA and Stanford when Stanley Kline tried to send a message “LOGIN”. The system crashed at the letter “G” but sending at least the first two letters (History.com Staff, 2010). Computers started to be connected in the network and after the first four Universities, the BBN15 of Cambridge, MIT, Harvard and Systems Development Corp in Santa Monica were added in 1970. And when the Sanford, Carngie-Mellon, NASA/Ames, Rand and others started to join from January 1971, the ARPANET became an important and recognized project among the nation. (Howe, 2014) Internet became global when London’s University College and Royal Radar Establishment in Norway was added in 1973 (History.com Staff, 2010). The more Internet was becoming global, the more problematic it became to maintain the communication between computers in network

10 Massachusetts Institute of Technology 11 The Advanced Research Projects Agency (ARPA) changed its name to Defense Advanced Research Projects Agency (DARPA) in 1971, then back to ARPA in 1993, and back to DARPA in 1996. (DARPA, 2016) 12 The unit of data that is routed between an origin and a destination on the Internet or any other packet- switched network. (Rouse, 2007) 13 University of California, Los Angeles 14 University of California, Santa Barbara 15 Buckingham Browne & Nichols, Massachusetts

18

Spread of multimedia and rise of wages without utilising some central points. The initial idea of a network was to provide independent communication without dependency on any central device or infrastructure. Robert E. Kahn from DARPA wanted to maintain this original idea and proposed the Transmission Control Protocol/Internet Protocol (TCP/IP) which enabled communication between devices on the Internet not dependent on any technology or operating system (Kahn, 1972). TCP/IP was adopted as defence standard by DARPA in 1980 and since 1st of January 1983 ARPANET has switched its host protocol from old NCP to TCP/IT. This activity was planned several years in advance and the transition was surprisingly smooth. (Leiner, et al., 2016) Another barrier was overcome in the spread of this technology. In 1991 an introduction of the World Wide Web by a Swiss programmer Tim Berners-Lee was introduced. It enabled sharing information and data on “web”. The published information could be retrieved by anyone on Internet and, therefore, the Internet became more than just a tool for transferring data between devices. In 1992, a group of students and researchers from the University of Illinois developed a user friendly web browser called Mosaic (later Netscape), which became the prototype of a modern user browser which we use nowadays. (History.com Staff, 2010) As the Congress decided that the Web could be used for commercial use, we observed the rise of services which also helped with the spread of multimedia on internet which, we will show, affected the superstar wages. In the second half of the 1990’s the first experiments with the internet streaming occurred, with the first streaming of concerts, sports games or political speeches. However, the sport streaming became common in 2000’s especially with the foundation of YouTube in 2005. (Vicent, 2015) Digital advertising is a rising market, reaching USD 170 billion in advertisement spending for 2015, being roughly on par with TV advertising revenues for the first time in history, expected to exceed the TV in 2016 (Statista, 2016). Revenue, m£ 700,00

600,00 Real Madrid

FC Barcelona Manchester United 500,00 Paris Saint-Germain Bayern Munich Manchester City Arsenal Chelsea 400,00 Liverpool

Juventus 300,00 Borussia Dortmund Schalke 04 Tottenham Hotspur 200,00 AS Roma AC Milan Atlético de Madrid Everton Internazionale Newcastle United 100,00 West Ham United

0,00 0,00 20,00 40,00 60,00 80,00 100,00 120,00 140,00 Social media followers Figure 2: Revenue and social media followers 2014/2015. (millions)Source: (Deloitte., 2016)

2000’s are also the time when social sites were coming to the scene. This can be useful also for our research. Numbers of followers on social sites are showing the popularity of sport clubs. These followers are all most likely the customers which may increase the total revenue of the club.

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Chapter 4

Therefore, there should be a correlation between the number of fans on social sites and the revenue of clubs. (Deloitte., 2016) has analysed social media followers from Facebook likes, Twitter followers and Instagram followers of sport club profiles on respective sites with club revenue in 2014/2015. Results are shown in the following Figure 2 (Deloitte., 2016). Scatter plot shows a correlation between the revenue and the social media followers, which can indicate the importance of internet and social media for sport revenues, thus probably also for superstar wages, which we will examine further.

4.4. Sports broadcasting

There have always been attempts to recreate a sport game for those who were unable to sit physically on the stadium, i.e. to watch the game personally. Nowadays we just watch the live broadcast on TV or on the Internet, or just watch the replay. But that was not possible in the past. In 1911 a group of people were recreating a game of football previously played about which they learned through telegraph. Although very primitive, this may be considered as the first time someone was able to watch the sport game without actually directly watching it. (McSorley, 2014) Before television, there was radio. The first sport game to be broadcasted through radio was the football match between the University of Texas and Texas A&M on 25th of November, 1920 by WTAW16 (Nachman, 2011). The first sport event to be televised was the 1936 Summer Olympics at Berlin. Two German firms, Telefunken and Fernseh used RCA and Farnsworth equipment, respectively to provide 72 hours of live transmission transmitted to special viewing booths, called “Public Television Offices” in Berlin and Postdam (Television History, 2015). The first televised event in Britain was 1937’ Wimbledon and the next year the first televised sport match - a football (soccer) game of English FA Cup was transmitted (BBC, 2016). The first televised sports game in the USA was a baseball game between the Princeton and Columbia Universities on 17th May 1939 (Stephens, 1998). At that time, about merely 400 TV sets were able to receive the broadcast (Koppett, 1999). In took more than 10 years for the first colour broadcast. The rivalry between colour TV standards was apparent also in sport broadcasting. As a part of the campaign of CBS to establish its electronic-mechanical system as the standard, they were doing the first colour telecasts of Dodgers games in August and September 1951. The first use of colour in a national game was in 1955 when NBC broadcasted the “Subway Series” between Dodgers and Yankees. However, it again took more than a decade till the major improvement in the colour broadcast quality was introduced with the RCA TK-43 “Big Tube” in 1967. (Engineering and Technology History Wiki, 2015) More innovations came to sports broadcasting, with “Instant replays” in 1955, which actually took thirty seconds of preparation time for the moment to be re-lived. The real “instant” replay came in 1963 using VCR. In 1956, ABC developed a recorder which could retrieve 30 second replays within 4 seconds and which had slow-motion controls and frame freezing. On-Screen Graphics came in 1965. (Nachman, 2011) On the 7th of September, 1979, the sport channel Entertainment and Sports Programming Network, widely known as ESPN was launched. It was the first television channel to broadcast nothing but sports. 24 hours per day, 7 days in a week. ESPN showed, that the televised sports is a market large enough to create such television, a model which was later adopted by many other television channels (Fox, CBS, NBC). (ESPN Founder, 2016) Despite several specialised sport channels, the viewer still had to rely on the broadcaster that his sports event will not be disrupted with airing of a different show. This changed with DirecTV

16 A radio station from Texas. Abbreviation means “Watch The Aggies Win”

20

Spread of multimedia and rise of wages service. NFL Sunday Ticket gave fans the ability to choose any game they wanted, no matter what channel was carrying the game or where it was played. Nowadays, all major sports and major leagues offer similar “all access” packages on satellite and cable. (Nachman, 2011) Also, with the introduction of VCRs and moreover with DVRs (digital video recorders), users were able to record their games and watch them anytime they wanted (Strickland, et al., 2016). With the improvement of the internet technology, computer speed and network bandwidth, the streaming of sports through the internet became regular. The first sport streaming was done by RealNetworks, when they televised the MLB playoffs in 1995 (Vicent, 2015). However, the breaking point for internet streaming of sports came in 2005, when ESPN launched their new online-only network, the on-demand service ESPN3.com (Nachman, 2011).

21

Chapter 5. English Premier League, MLS and NHL

This chapter summarizes a brief history and specifics of leagues which we will use in the analysis. We included the English football Premier League, the North American football (soccer) Major League Soccer (MLS) and the North American Ice-Hockey National Hockey League (NHL). Why these? The Premier League is the most famous, best paid football league in the world according to (Gaines, 2015) and has minimum salary regulations, and among European leagues it is the only one with the accessible wage data. We selected MLS for comparison within the same sport but as a league with much more regulations. NHL is chosen for comparison with a different sport. Also, both North American leagues have easily accessible salaries data.

5.1. English Premier League

The English Premier League, which may be surprising, had not existed until 1992 (Premier League, 2015). Its predecessor, the old Football League was founded in 1888 and is the oldest such competition in the football world (The Football League, 2004). We might only guess whether the Premier League would be created, if it was not for the Heysel Stadium Disaster where “39 people died and more than 400 were injured when a wall collapsed at the stadium in Brussels during violent riots just before the European cup final between Liverpool and Juventus” (BBC, 1985) which led UEFA to ban English clubs inform the European football cups and competitions for 5 years. This led the Football league to lose its prestige and the greatest players to leave clubs in favour of Spanish La Liga and Italian Serie A (Premier League, 2015). Since the ban for English clubs in European football cups and competition was raised in 1990, the situation of English Football league began to improve. However, there was a problem with division of revenues from television rights. In 1986 the Football league signed a 2- year TV deal with BBC/ITV worth £ 6.3 million (£3.1m per year), but in 1988 it was already a 4-year deal with ITV worth £ 44 million (£11m per year) (Crawford, et al., 2002). It was the sign that there is a significant amount of money in TV rights and clubs did not want to share their piece with the league. So 10 “rogue” clubs started to threaten the league to sign their own TV contract and create their own league. They were, however, persuaded to stay by a High Court injunction and after the conditions of dividing the TV rights revenues were changed (Reuter, 1988). The idea of a new league creation, with larger income and no representatives from outside of football clubs was still present. And eventually, it became real when the First Division of football clubs resigned from the Football league and founded the Football Association (FA) Premier League (FAPL) on 27th May 1992 as a corporation owned by 20 member clubs of the Premier League (Premier League, 2015). Each club is a shareholder with one vote on issues such as rule changes and contracts. Also clubs elect the chairman, the chief executive and the board of directors to oversee the daily operation of the league (Premier League, 2006). The new league serves the former Football League in the same way as its First Division used to. FA Premier League became the First Division, while the Football League, later the Championship became the second, third and fourth respectively (The Football League, 2004). The FA Premier league changed its name to simply the Premier League17 in 2007 (Premier League, 2007). This change would not have been possible without a financial background. During the discussions about its creation, a new television contract was signed. This was possibly one of the

17 We will refer to it as English Premier League

22

English Premier League, MLS and NHL major reasons why the new league was founded only in the ownership of the clubs. A new 5-year contract with BskyB18 was worth £191.5 million (£38.3m per year) (Crawford, et al., 2002). TV rights earnings rose during that time, so the new contract for 2016-2019 was worth £5.136 billion (£1,7b per season) which is a 71% rise against 2013-2016 contract (see Figure 3)(BBC, 2015). The contract was signed with Sky which will pay £1.39b per year and BT Group19 with a share of £320m per season. With 168 games to be shown live (126 on Sky and 42 on BT) this makes £10,19m per game. (BBC, 2015) 2016 - 1,712b£ 1800

1600

1400

1200 2013 - 1b£ 1000

800 2010 - 591m£ 2007 - 569m£ 600 2001 - 400m£ 400 1997 - 167,5m£ 1992 - 38,2m£ 2004 - 341m£ 1986- 3,15m£ 200 1988 - 11m£

0

1995 1997 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1996 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Figure 3: First Division and Premier League TV rights earnings p/y.

Source: (Crawford, et al., 2002), (BBC, 2015)

The English Premier League has the highest average wage of all football leagues in the world, being the league with the fourth highest average wage in the world, after N. American Basketball NBA (USD 4.58 m), Indian Cricket IPL20 (USD 4.33 m) and N. American Baseball MLB (USD 4.17 m) with USD 3.82 m average salary (Gaines, 2015) (see Appendix 2 for more information). However, despite having the highest aggregate attendance, the English Premier League is the second in average attendance for one match behind the German Bundesliga (Harris, 2014). One explanation is that the wages are rising because of the interest of TV-viewers across the world. Their interest can be also derived from TV revenues. Technology, therefore, made the English Premier League a superstar between football leagues. There are 20 clubs playing in the English Premier League. Each year the three worst performing teams are relegated to the Championship21 and three best clubs from the Championship are promoted to the English Premier League. The English Premier League does not have a salary cap neither a limit for the number of foreign players on the roster. (Premier League, 2015) Low

18 Currently known just as „Sky“, rebranded in 2014 (Sweney, 2014) 19 British Telecommunications 20 Indian Premier League 21 England’s second football division. Each year three worst performing English Premier League clubs are relegated to the Championship and three best performing clubs from the Championship are promoted to the EPL.

23

Chapter 5 regulations in the league are leading to a free flow of players without limitation, which might be another important factor for the height of salaries which we will examine later.

5.1.1. Financial structure of the Premier League clubs

The English Premier League is led by the former “Big four”: Arsenal, Liverpool, Manchester United and Chelsea, joined in the last years by the incomes and expenses of the Premier League clubs as decribed. We use Deloitte Football Money League survey (Deloitte., 2016) as a primary source of information.

Figure 4: Premier League 2013/2014 - Profit/(Loss) after Tax. Source: (O’Connor, 2015)

(Deloitte., 2016) has published the information on Top 20 sports clubs by the highest revenue of 2014/2015 season and there are nine clubs of the Premier League in this list: Manchester United, Manchester City, Arsenal, Chelsea, Liverpool, Tottenham Hotspur, Newcastle United, Everton and West Ham United. There are also another eight Premier League clubs in the next 10 places as mentioned, which means that 17 of 20 clubs from the Premier League are in the Top 30. Figures are not reflecting the current TV contract which started in 2016. Next year probably all Premier League clubs will make it to the TOP 30. The full list can be found in the Appendix 3. The revenue of clubs is divided into three categories in the publication: Matchday, Broadcasting and Commercial. Matchday revenue consists of direct match ticket revenues. Broadcasting revenue originates from TV rights. Commercial revenue is a combination of advertising, sponsorship and various other incomes from private sources. The distribution between these categories among 9 clubs from the TOP 20 is 20% for Matchday, 48% for Broadcasting and 32% for Commercial. The importance of broadcasting revenues is best seen among teams from the bottom of the list, where it makes 60, 69 and 65% of the total revenues for Newcastle, Everton and

24

English Premier League, MLS and NHL

West Ham, respectively. Detailed information can be found in Appendix 4. When the TV rights contract increased in 2016 the share of Broadcasting will increase. The other categories vary by the club. High commercial revenues usually go to those clubs with a strong brand (Manchester United) or a club which is supported by a rich sponsor (Manchester City). Matchday solely depends on ticket price and the number of tickets sold. Arsenal leads in this category thanks to a high ticket price as well as Manchester United thanks to high capacity of the stadium. We are analysing the revenue of clubs because we want to see if the clubs can still be profitable with the high and still increasing player salaries and how these expenses are covered. As shown in Figure 4 (O’Connor, 2015), most of the Premier league clubs were in profit in 2013/2014 season. But it was not always like that. The change came with the TV rights contract in 2013. As shown in Figure 5 (O’Connor, 2015), more than a half of clubs were in loss for previous 4 seasons in total. The biggest loss made by Manchester City was due to large spending during the rebuilding of the club when purchased by Sheikh Mansour bin Zayed Al Nahyan (Armitstead, 2008).

Figure 5: Premier League Profit/(Loss) before Tax - total from 2009/2010 to 2013/2014 season. Source: (O’Connor, 2015)

From these numbers we can see that Premier League clubs mostly rely on TV rights revenue, except for the richest one, when the matchday and especially commercial revenues are rising. There are also clubs that are able to generate profit, however, many are also generating significant loss. This is caused either by extensive spending during club rebuilding which is usually covered by loans or private funding from a rich owner e.g. Manchester City, Chelsea, or some clubs are not underperforming and still not able to generate profit, e.g. Fulham, Hull, Sunderland. This may change with 2016’s TV contract when, taking the increase of broadcasting revenue in account, the income of all Premier League clubs should increase.

25

Chapter 5

5.2. Major League Soccer

Nowadays, the soccer is short of popularity enjoyed by “big four” sports, i.e. Basketball, Baseball, American Football and Ice-Hockey. In the past, soccer was more popular. Soccer came to North America around the year 1850 from England. It was fairly popular and the American Football Association was formed in 1884 and it was the second oldest sport association in the US right behind the Baseball Association with strong connections to English Football Association (Murray, 1910). More football associations were established but it was causing more problems than good. The fight for power between associations and the Great Depression in 1930’s stopped the promising development of this sport (Pyne, 2016). The first resurrection of football (or soccer, in the US) came in 1967. England won the World Cup and associations in the US wanted to use the situation of increased interest in football. So the United Soccer Association and the National Professional Soccer League put the rivalry aside and merged to form the North American Soccer League (NASL). (U.S. Soccer, 2016) NASL began in 1968, consisting of 17 teams with no relegation rules. The problem was that there were not enough domestic professional football players in the USA so foreign players had to be attracted with higher wages. Rise of wages in a developing league with not many supporters and low wage receipts became a problem. So there were rule changes to bring the attention of supporters such as sudden death overtime or bonus points which caused that the league was not taken seriously worldwide. (Pyne, 2016) A change came in 1975 when Pelé started to play for New York Cosmos. Pelé picked up a huge salary for that time, USD 1.4million per year (U.S. Soccer, 2016). The attention he generated helped the league to develop. Other talented and famous players entered the league, such as Franz Beckenbauer (Royal Soccer Academy, 2016). Some games of New York Cosmos were attended by around 70,000 fans. The league has expanded to 24 teams. However, Pelé left the league in 1977 but no other star of the same calibre joined the league. The attention was falling to a fraction of that from Pelé´s times and the league finally succumbed in 1984. (Pyne, 2016) NASL may seem like not being successful but the number of registered football players in the USA rose from 100,000 before the establishment of the league to more than 4 million at the time of its end. (Pyne, 2016) Success of the football tournament at 1984 Summer Olympics in Los Angeles convinced FIFA to organize the FIFA World Cup of 1994 in the USA. One of the conditions was that there will be a division 1 football league created in the USA, utilizing the international FIFA football rules. (Soccer Maniak, 2016) The Major League Soccer (MLS) was launched in 1996, averaging 17,000 fans per game (U.S. Soccer, 2016). The league consisted of 10 teams, divided to 2 conferences, so the teams will not need to travel long distances (Royal Soccer Academy, 2016). The further development of the league began in 2007, when David Beckham signed with Los Angeles Galaxy. LA Galaxy was able to sell out every game they played home or away. Following the success with Beckham, other former star players, such as Roy Keane, Thiery Henry or recently David Villa or Kaká became players of the MLS. (Royal Soccer Academy, 2016) Currently, there are 20 teams in MLS. The best eight at the end of the regular season are advancing to play-off, while the winner of the play off is also the winner of the season. The regular season winner is not the winner of a league season. There is no relegation in the league. (Soccer Maniak, 2016) Compared to the English Premier League, MLS has a much stricter roster and expense regulations for the clubs. Each club can have 20 senior players on the roster, the maximum salary for

26

English Premier League, MLS and NHL any one player is USD 436,250 per year, with some exceptions that are not important for us. The important exception here is the so called designated player, when, under the Designated player rule the club can have a maximum of three players older than 24 years that are exceeding the ceiling for the normal player salary. (MLS Press Box, 2016) This is also called the “Beckham rule” because it was created to enable LA Galaxy to pay Beckham’s salary significantly exceeding the salary ceiling (Dyer, 2015). Only 8 foreign players are allowed on the roster. A designated player counts $436,250 against a team's cap. The salary cap is $3.49 million per team, not counting the extra salary of designated players. The whole MLS, since its creation, generates a loss (Silicon Beach VC, 2014). There are several articles describing MLS financial problems, such as (Davis, 2014). (Szymanski, 2015) analyses the MLS’ business model, analysing incomes and expenses and potential development. He points out the importance of football club owners’ determination when the prestige and entertainment of owning the sport club can equalise the financial losses that come with that. However, in the end he concludes that MLS is most likely to collapse in the following years because its model is financially unsustainable. The reason to analyse this league is to have a league for comparison with the Premier League with different league rules: - no relegation rules22, - salary ceiling, - weaker establishment (lower sponsorship, TV contract), - roster regulations, - organisation of season (playoff in MLS), to see, how these regulations affect wages in the league.

5.3. National Hockey League

There were several hockey leagues before NHL was created. Many of them were created to exclude some teams from playing with others or to simply form a new league of rogue teams that did not agree with management of their league. (Coleman, 2011) Such was the case also with NHL. The National Hockey League was formed in 1917 by club owners of the National Hockey Association (NHA), the first league, where six-player team hockey was adopted as well as three 20-minute period game, jersey numbers, match penalties and on the fly line changes. The aim of the new league creation was to get rid of Toronto Blueshirts owner Eddie Livingstone (Wright, 2010). There were five forming teams: Montreal Canadiens (the only club to remain without moving or a name change since the beginning of the league), Montreal Wanderers, Ottawa Senators23, Quebec Bulldogs and Toronto Arenas. Due to various financial and organisational problems, the number of active teams in the league was varying.24 Teams were competing for the trophy called the Stanley Cup, named after Lord Stanley from Preston who purchased a silver bowl in 1892 when serving as the Governor of Canada and gave it as a trophy for an amateur hockey team championship. As ice-hockey became more and more professional, the Stanley Cup became a prize for professional hockey leagues. In 1910 it came to

22 There is no second division for worst performing clubs of the MLS to be relegated to as it is in EPL. 23 There is a club of the same name in current NHL. This club, however was created in 1992. The original Ottawa senators were active since 1883 and played in league till 1934 and won 11 Stanley Cups (see 3.2.6. ) Neither the NHL nor current Senators claim the current Senators as continuation of the original organization of franchise. 24 In 1918 for example, only three teams were competing. Quebec withdrew due to financial reasons and Wanderer’s rink was destroyed in fire. (Wright, 2010)

27

Chapter 5 possession of NHA and from there it was inherited by NHL. However, till 1926 other leagues competed for Stanley Cup as well (Pacific Coast Hockey Association, Maritime and Western Hockey League). With all the other leagues folding, only NHL has remained to compete for the Cup since 1926. (Ticketcity, 2016) NHL expanded to ten teams until the Great Depression, when the number of teams was cut to six. These teams are referred as the “Original-Six”: the Boston Bruins, Chicago Black Hawks, Detroit Red Wings, Montreal Canadiens, New York Rangers and the Toronto Maple Leafs, all of which are still active clubs in the league. The first expansion came in 1967-68 season, expanding the league to 12 teams. With continuous expansions through time the league now consists of 30 teams with the Minnesota Wild and Columbus Blue Jackets being the last teams to join in 2000/01 season25. (Rauzulu's Street, 2004) Main or important changes in rules during the existence of NHL were: permission of goalie or fall to the ice to make saves in 1917 (a foul until that time), two minute minor penalties in 1921, forward passes in 1927, introduction of the centre red line in 1943, ice surface painted white in 1949 (Rauzulu's Street, 2004). Every season has two main parts. The first part, the so called regular season consists of 82 games per team where team are divided into 2 conferences and 4 divisions. The two best teams of a division are positioned the first and the second in the division and the rest of teams are ordered within division according to their performance during the season. After the regular season, the play-off begins. Play-off is organized in relegation style and split by conferences. Eight best teams from each conference play against each other where the best team plays against the eight team, the second against the seventh and so on. Teams are playing in a best-of-seven round. The winner is advancing to the next round, while for the losing team it is the end of the season. The finale of the league is play off between the winner of the eastern and the western divisions. Again, the best-of-seven round determines the winner of the whole league and the Stanley Cup. (NHL, 2014) NHL salaries are defined in the Collective Bargaining Agreement (CBA) (NHL, 2013) . According to CBA, 23 players under contract are allowed to be on NHL team roster, a team can have 50 active contracts also with players in lower leagues. The total number of all players in one team including main team roster, minor team players, prospects or drafted players is 90. NHL is using the term Salary Cap hit to determine the size of a player’s contract. It is calculated as the average salary of the player in the current contract26. The maximum limit of a player’s contract in NHL is 20% of the salary cap of the whole team (the sum of all salary caps). Salary Cap ceiling is the maximum sum of a team’s Salary Caps. The ceiling is changing, depending upon the revenue of NHL accumulated in previous seasons. For the 2015/16 season it is USD 71,400,000 (CapFriendly.com, 2016). The minimum player salary per-season is USD 575,000. Salary Cap floor is the minimal sum of Salary Caps which has to be paid by the club. For 2015/16 season it is USD 52,800,000. The floor exists to prevent clubs to trade away or deplete their roster in order to sacrifice their position in the table to secure a better position on draft. Also, it secures fair compensation to players. Each year before the seasons begins, unrestricted free agents (see Appendix 5) are able to choose a contract offer from any NHL club or leave to a different league. Each year, the annual NHL draft is held, when teams are selecting young players which have not played NHL before in a specific order with the worst team of the last season choosing first and the winner of the league choosing last.

25 Not taking in account the relocation of Atlanta Thrashers to Winnipeg and re-creation of Winnipeg Jets in 2011. 26 E.g. a player has a 5year contract with salaries coming as: USD 500 000, 600 000, 800 000, 500 000 and 600 000, the salary cap for this contract is therefore USD 600 000. Also performance bonuses are counting against the salary cap.

28

English Premier League, MLS and NHL

The draft has seven rounds. This is to give the worst performing club a chance to improve in next years with young players with a high potential. Draft picks can be traded between clubs for each other or for regular players. (NHL, 2014) Most of NHL teams recorded profit in 2014/15 (see Appendix 6). Most of the teams had, however, faced loss in the past years with improvement in rthe ecent years as the revenue is increasing (Appendix 7, also compare 2014/15 season with 2013/14 (Fox, 2014)). The biggest part of income are usually gate receipts (tickets and season passes) (Scott, 2012). As we are analysing the impact of technology on revenues, in his article (Silver, 2013) we will analyse why hockey clubs from Canada have been unable to win the Stanley Cup in the last 20 years. What is important for us is that in one part (Silver, 2013) there is a correlation between the highest revenue clubs and the popularity of the club on the internet. The popularity is determined by the number of google searches of NHL teams. Results are shown in Figure 6 (Silver, 2013). As we can see, there is a relationship between the popularity of the club on the internet and its operating income.

Figure 6: NHL fans in Media Market and Operating Income. Source: (Silver, 2013)

As we can see, the rules in NHL are quite bounding. We are analysing NHL to see, whether the superstar effect has the same determinants in different sports with different rules.

29

Chapter 6. Data collection for empirical analysis

In previous chapters we wrote about the Superstar theory related to sports and described what can be the cause of significantly higher salaries of selected individuals than other players. Whether our assumptions and theories are correct can be analysed using econometrics by construction of an econometric model of impact of selected variables on the players’ salaries. Before the model will be constructed, the important data had to be collected. In this chapter we will describe the collection of data, sources of data and present the data themselves and why they could be important for the model. We collected more data than might be used in the final model, but during preparations for the model creation we selected various variables that could possibly affect players’ salaries in selected leagues. Data sources are divided according to the league they are related to, as we estimate a model separately for each league and compare the results.

6.1. English Premier League

To gather players’ salaries with their historical development as well as “average attendance, average ticket price, estimated TV viewers, estimated fan base size and possibly revenues from merchandising” we contacted the English Premier League. The English Premier League organization does not hold the information according to their reply. However, they provided us with the contact to all current English Premier League clubs (for complete conversation see Appendix 8). Therefore, we contacted every single football club in the English Premier League. We received response from most of them with the same answer, that the players’ salaries is confidential information which could not be shared, or that they are not able to cooperate with every subject that is requesting some data for research (see Appendix 9 as the example of such a reply). Not being able to obtain the data directly from clubs, we searched alternative sources. Sports Interactive is each year releasing an officially licensed product, the Football Manager which contains salary information of all players from the most important leagues around the world. Despite trying to contact Sports Interactive in few different ways, we were unsuccessful in receiving any response. The last resort was to gather the data from various articles. A sport journalist Nick Harris who cooperates with Sporting Intelligence has released several articles with various data about players’ salaries. Again, we tried to contact Mr. Harris, however, without any success. We use his articles as the primary source of salary data in the English Premier League. In Figure 7, we can see comparison of an average and the maximum wage in the English Premier League since 1961 to 2014. Data for the average wage were collected from (Harris, 2011) and the rest were calculated using average wage expenses increase in the league according to the wage expenses information of English Premier League’s clubs from Totalsportek which were normalized against (Harris, 2011) to avoid discrepancy27. The bigger problem was the maximum wage. As we mentioned above, to gather individual salaries of players is complicated, and to collect the maximum wage means to know the specific salary of a specific player, which from the personal information point of view is much different than the average salary for the whole league. We have at least some examples of maximum wage mainly as wage height milestones from (Harris, 2011) and (Nepal, 2014). Since for the econometric analysis we need the data timeline more than pure “stochastic” data, we used the examples from these two

27 We calculated a percentage increase between years using data from Totalsportek and based on these increases we calculated each additional year using the last year from (Harris, 2011) as the baseline.

30

Data collection for empirical analysis sources to generate an estimated curve of maximum wage development using Wolfram Alpha (see Appendix 10 for complete equation). £300 000 £266 138

£250 000 Average Wage per week in EPL Max Wage per week in EPL £200 000

£150 000

£100 000

£37 696 £50 000

£0

2009 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2011 2013 1961 Figure 7: Average and maximum wage comparison in the English Premier League.

Source: (Harris, 2011), (Nepal, 2014), own calculations

As also for the impact of various sport indicators on salaries, we will have to gather historical ticket prices and league attendance. Data about television contracts are shown in Figure 3 (BBC, 2015). Average attendance was gathered from (Brandstatter, et al., 2015). We used ticket prices of Manchester United. This was due to the best availability of prices for this club. We assume that development of ticket prices of the club will reflect the development of ticket prices in the league in the long horizon. Same as with wage development, we are interested in timeline development rather than in distributed values. The mentioned ticket data was extracted from (Hinson, 2008) and the rest of prices were taken from ticket examples found on the internet. The estimated28 average match income in the English Premier League is shown in Figure 8. As we will analyse the impact of macroeconomic indicators as well, we gathered data about UK’s GDP and average wage in the UK from (Trading Economics, 2016). We were unable to collect the revenues from merchandising for such a long time period though. The fan base size will be gathered from “likes” of clubs´ Facebook page. This may not take in account older generation of fans, but there is hardly any other more accurate way to determine the fanbase size.

6.2. Major League Soccer

To get the complete data set of MLS salaries we will have to improvise as well. MLS salaries are well documented since 2007, as the Player Union is releasing the salary survey each year. But the

28 Since development of ticket price was only taken from Manchester United which has a ticket price about 25% over the average of the league (Bezants, 2016), we calculated match day income from average attendance multiplied by ticket price, divided by 1.25. We did not, however, take into account various ticket prices or season tickets. Therefore, the specific values may differ from reality but the timeline should reflect the real development.

31

Chapter 6

MLS exists since 1995. Moreover, to have the timeline with only 8 years is not enough for a reliable econometric model. £1 400 000

£1 200 000

£1 000 000

£800 000

£600 000

£400 000

£200 000

£0

1965 1975 1963 1967 1969 1971 1973 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 1961 Figure 8: Estimated average match income in the English Premier League.

Source: (Badenhausen, 2015), (Hinson, 2008), (Bezants, 2016) own calculations

To determine the salaries before 2007 we have to have in mind that there was a salary cap with no exceptions and so the average salary was about the same since 1996 till 2006. Even when we look at 2008’s salaries of Columbus Crew (Mitchell, 2008) which had no player under designated player rule exception (which was introduced in 2007, see 5.2.) we can still see, that the average salary is around USD 110,000 per year. We will use this value as the reference for years 1996-2006.

$160 000 Average Salary $140 000 Maximum Salary $120 000

$100 000

$80 000

$60 000

$40 000

$20 000

$0 1997199819992000200120022003200420052006200720082009201020112012201320142015

Figure 9: Average and maximum salary per week in MLS.

Source: (MLS Players Union, 2016), own calculations

32

Data collection for empirical analysis

For data since 2007 we can use information from (MLS Players Union, 2016). The complete development of weekly average and medium salaries is shown in Figure 9. Average attendance in MLS is published at the end of every season on (mlssoccer.com) in Full Season Stats. The problem is with historical ticket prices in MLS. We gathered information of 1997 season ticket prices from (Curry, et al., 2004), 2008’s season’s from (Slideshare, 2008), and information from 2015 were taken from (Miceli, 2015). Then, using Wolfram Alpha we have done a liner interpolation to get the development of ticket price (Appendix 11). From this we calculated Figure 1029.

$900 000

$800 000

$700 000

$600 000

$500 000

$400 000

$300 000

$200 000

$100 000

$0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Figure 10: Average MLS Matchday Income Estimation.

Source: (Curry, et al., 2004), (Slideshare, 2008), (Mitchell, 2008), (mlssoccer.com), own calculations

Until 2007 there was no TV rights deal in MLS as we know for example from the Premier League. There was a TV deal, but with right fees paid to the league. However, earnings from advertisement were divided between TV and the league (Sandomir, 1994). The first TV deal with right fees was signed with Univision in 2007. The deal was for 8 years with annual fee of USD 9.9 mil.. Additional TV contracts were signed the same year with AXS TV, Fox and ABC/ESPN. NBC joined in 2012. A new TV contract was signed in 2015 with Fox/ESPN and Univision. The contract ends in 2022 with annual fee of USD 90 million. A complete overview of TV deals can be found in Appendix 12 and development in Figure 11. HDP Data and average wage data were taken from (Trading Economics, 2016).

6.3. National Hockey League

It is no problem to obtain maximum wage since 1989-90 season of NHL. We can use for example (puckreport.com, 2015). Before 1989 the salaries were not largely know, although for example (hockeyzoneplus.com, 2016) has the information about selected players. This would not mean that they were the best paid players of the league even if most of them were amongst top star players.

29 Again, we refer to this as to estimation because there was no exact data used. We could for example possibly use different type of interpolation and results would be different.

33

Chapter 6

100 $90 mil 90

80

70

60

50

40 $28 mil $28 mil $28 mil 30 $21 mil $21 mil $21 mil $20 mil $20 mil 20

10

0 2007 2008 2009 2010 2011 2012 2013 2014 2015

Figure 11: Annual MLS TV fees. Source: (Ourand, et al., 2014), own calculations

Average wage had to be obtained from several sources: 1989-1990 (Kiley, 1990); 1990-1991 (Geeks on Finance, 2001); 1991-92 (NY Times, 1992); 1992-93 (Schram, 1997); 1993-94 to 2003- 04 (Rosner, et al., 2011); 2004-05 was a lockout, NHL was not played; 2005-06 to 2007-08 (Wilson, 2011); 2008-09 to 2013-14 from (USA Today, 2016) and 2014-2015 from (Dorish, 2015). $350 000 Average Salary $300 000 Maximum Salary

$250 000

$200 000

$150 000

$100 000

$50 000

$0

Figure 12: Average and maximum salary weekly salary in NHL. 30 31

Source: (Kiley, 1990); (Geeks on Finance, 2001); (NY Times, 1992); (Schram, 1997); (Rosner, et al., 2011); (Wilson, 2011); (USA Today, 2016); (Dorish, 2015); (puckreport.com, 2015); own calculations

30 NHL did not play in 2004-05 due to lockout, see 5.3. 31 Wage was adjusted to weekly wage to maintain compatibility with other leagues.

34

Data collection for empirical analysis

$1 200 000

$1 000 000

$800 000

$600 000

$400 000

$200 000

$0

Figure 13: Approximated Matchday Income NHL.

Source: (BonkTastic, 2012), (DiGiovanna, 1993), (Statista, 2016), own calculation

$700 mil $608 mil $600 mil

$500 mil

$400 mil

$300 mil

$200 mil $200 mil $120 mil $70 mil $100 mil $6 mil $13 mil$44 mil $17 mil $0 mil $31 mil $0 mil

Figure 14: NHl TV Rights revenue.

Source: (Macnow, 1991), (Bowen, 1992), (SBS, 2008), (Lepore, 2008), (Wyshynski, 2013), own calculation

Average attendance data were taken from (Hockeydb.com, 2015), average ticket price from (Statista, 2016) for 2006-07 to 2014-15, for season 1993-94 from (DiGiovanna, 1993) and 1994-95 from (BonkTastic, 2012). Using these data we approximated a timeline with significant accuracy

35

Chapter 6

(R2=0.945). Complete approximation is in Appendix 13. In Figure 13 we can see the Approximated32 Matchday Income in NHL. TV rights deals in NHL are slightly different than in football. There is always some league TV deal but clubs are making deals also with local broadcasters, each can bring them additional millions of USD (Settimi, 2013). Also, to gather the information about league TV deals was complicated, it was taken from several sources: (Macnow, 1991), (Bowen, 1992), (SBS, 2008), (Lepore, 2008), (Wyshynski, 2013).

6.4. Television and internet

Through the whole thesis we are mentioning the effect of technology on superstar wages. To analyse this effect we collected the number of internet users and television count. The number of internet users was taken from (ITU International Telecommunications Union, 2014). The number of television receivers in the world had to be approximated using data from (OK nation, 2008). In both variables we are using data for the whole world because of the technologies described in Chapter 4 any internet user or television viewer can potentially watch any sport match from described leagues. In Figure 15 we can see the development of internet user numbers and counts of television receivers. In our analysis we are also using the world population data collected from the United Nations.

3 000 mil

Internet users in the world 2 500 mil

Television receivers estimation in the world 2 000 mil

1 500 mil

1 000 mil

500 mil

0 mil

1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013

Figure 15: Internet users and television receivers estimation in the world.

Source: (ITU International Telecommunications Union, 2014) (OK nation, 2008), own calculation

32 Since timeline of ticket price was interpolated, the Matchday Income is an approximation.

36

Chapter 7. Models from the empirical analysis

The main hypothesis of this work is to observe the effect of technology on the maximum wage in collective sports in comparison to other factors. To analyse this we created eight econometric models which are observing the effect of several variables, including technology, on the maximum and average wage in three leagues we described in the previous chapters: English Premier League (EPL), National Hockey League (NHL), Major League Soccer (MLS) and on the compound data as well.

LOG_ MAXWAGE = β + β2 LOG_ TVRIGHTS + β3 LOG_ MATCHDAY +

β4 LOG_TECHNOLOGY + error

LOG_ AVGWAGE = β + β2 LOG_ TVRIGHTS + β3 LOG_ MATCHDAY +

β4 LOG_TECHNOLOGY + error

Variables used are LOG_ MAXWAGE (maxWage) which is a logarithm of deflated maximum salary in selected leagues. LOG_ AVGWAGE (avgWage) is a logarithm of deflated average salary. LOG_ TVRIGHTS (TVrights) is a logarithm of deflated TV rights income per year for the whole league. Variable LOG_ MATCHDAY (matchday) is a logarithm of deflated average matchday income which is calculated as an average ticket price in the league multiplied by average attendance in the league. LOG_TECHNOLOGY is a logarithm of technology variable which is represented as the sum of television receivers and internet users. The dummy variable TYPE is used for restricting the dataset. Its value is equivalent to 1 when the data is from EPL, equivalent to 2 when the data is for NHL and equivalent to 3 when the data is from MLS. We use deflated monetary variables to ensure that values are levelled to the same base year. When deflating all monetary variables we do not have to include a year variable into models. Numbers of television receivers and internet users are summed together to simulate the development of technology. All used variables are in the logarithmic values to ensure the normal distribution. The weak side of this analysis is a relatively small number of observations ranging from 20 to 99 for selected models.

Variable Description Mean(St. derivation) LOG_ MAXWAGE logarithm of deflated maximum wage per 4,5654 (0,78927) year LOG_ AVGWAGE logarithm of deflated average wage per 3,4261 (1,0138) year LOG_ TVRIGHTS logarithm of deflated income from TV 0,97871 (0,97639) rights per year LOG_ MATCHDAY logarithm of deflated average income 5,9303 (1,1107) from matchday per year LOG_TECHNOLOGY logarithm of technology factor per year 13,990 (1,0105) Table 3: Description of variables

7.1. Results Using the OLS estimation we employed samples from different leagues and ran separate models on the maximum and average wage. The set of explanatory variables remains identical in all models. Finally, we estimated the model with pooled data and included dummy variables to identify different leagues. Estimated results are in Table 4.

37

Chapter 7

League Dependent Technology Matchday TVRights R2 No. of variable observations ALL maxWage 0,211*** 0,229 0,281* 0,622 98 avgWage 0,510*** 0,197 0,292** 0,727 98 EPL maxWage 0,577*** 0,181*** −0,152*** 0,986 54 avgWage 0,937*** 0,421*** −0,332*** 0,975 54 NHL maxWage −0,059 0,450** 0,223*** 0,792 24 avgWage 0,306*** 0,0429 0,147 0,794 24 MLS maxWage 0,071 0,767*** 0,532*** 0,970 20 avgWage 0,091 0,649*** −0,157* 0,987 20 Standard errors in parentheses; * p < 0.05, ** p < 0.01, *** p < 0.001 Table 4: Regressions results

Our main focus aims at the analysis of the compound model. The reason is that only this model has a relatively significant number of observations to draw any resolute conclusions from. However, we also look briefly at the results from particular leagues. The compound model, labelled as ALL in Table 4 is showing a significant impact of variable technology on both maximum and average wage. Moreover, we see some impact of TVrights which is less significant on the maximum wage. This confirms our theoretical assumptions that technology is affecting the wages of exceptionally talented individuals. We have to consider players of these first class divisions we analysed as elite players, so the significant effect of technology on average wage as well is not in the contrast with the theory. The different effect of the TV Rights on the maximum and average wage can be explained by technology being rather a sole determinant of the maximum wage, while for the average wage there are other wage determinants such as the revenues of the club, in this case in the form of TV Rights. This observation confirms the theoretical assumptions as well. We can see that the R squared factor is around 0.6-0.7 in both models, which shows the good fit of the whole model as an explanation of the dependent variable. Briefly looking at the other models we see that results for the particular leagues are not always showing similar results as the compound model. The English Premier League (EPL) represents a league with minimum restrictions and almost free player market. We can see that the effect of technology is very significant. On the other hand, we can observe the negative coefficient for the TV rights variable which is not according to the theory, because the higher the TV rights revenues are the bigger wages should be. We also observe very high R2 which can sign a problem witch collinearity. The NHL is showing a significant effect of technology on average wage but on the max wage only revenues from matchday and TV rights are showing effect. NHL is a league with the salary ceiling and various restrictions for the height and length of the players´ contracts. Therefore, the effect of technology may prevail only on average wages where most of the contracts are not bounded by restrictions. Maximum wages on the contrary are all with maximum length and are all capped with a salary cap, therefore, technology is not prevailing and the height is more likely to be determined by the revenues of the club. Last of the league, the MLS is showing no effect of technology. MLS has the most salary restrictions from among the three analysed leagues. The salary cap was raised only for several players as the designated players rule only 8 years ago. These are too few observations to make any major conclusions. The R squared is high as well, but the significance of revenue variables may indicate effects of the salary cap.

38

Conclusion

This work discusses the determinants of superstar wages in sports. The basic assumption for existence of the superstar effect is the existence of competition. The academic literature gives many examples of the competition being fundamental to living organisms and their existence. We describe how the superstar theory works in a small market and argue that the extreme wage can be proposed to superstars only by their assumed talent implied from a small number of indices. In long term the real talent may differ from the expected. The central argument of the thesis is that the principal reason for the superstar wages is the spread of technology (the idea was first proposed by Sherwin Rosen). To this aim we collected data from three sport leagues that differ in the level of salary regulations and organization rules. The main difference is that the English Premier League has no salary ceiling or floor and has relegation rules on the contrary to the other football league – the North American Major League Soccer. The third league, the North American National Hockey league has a salary ceiling as well but the rules are generally not as strict as in MLS. The collection of data was not an easy task as data on wages of sportsmen are not regularly published and typically not available to public. What do we learn from the results? The findings confirm that technology has a significant effect on the maximum and the average wages as well. Furthermore, the role of technology is more important in the model with the maximum wage. The results from separate estimations of sport leagues suffer from small samples and we are not able to draw major conclusions. The presented results show that the influence of technology on wages is more significant in leagues with less regulations on salary and player trade. On the other hand, we observed a more significant role of the match revenues (based on the average price of tickets and match attendance) in more restrictive leagues. These findings should be corroborated in the further research when data from more leagues are collected. Finally, the thesis opens a discussion about the level of wages in the collective sports in relation to the development of multimedia. The information may be useful for policymakers when deciding the personal income tax scheme schedules.

39

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51

List of Figures

Figure 1: Distribution of profit in Formula One...... 12 Figure 2: Revenue and social media followers 2014/2015...... 19 Figure 3: First division and Premier League TV rights earnings p/y...... 23 Figure 4: Premier League 2013/2014 - Profit/(Loss) after Tax ...... 24 Figure 5: Premier League Profit/(Loss) before Tax - total from 2009/2010 to 2013/2014 season . 25 Figure 6: NHL fans in Media Market and Operating Income...... 29 Figure 7: Average and maximum wage comparison in the English Premier League...... 31 Figure 8: Estimated average match income in the English Premier League...... 32 Figure 9: Average and maximum salary per week in MLS...... 32 Figure 10: Average MLS Matchday Income Estimation...... 33 Figure 11: Annual MLS TV fees...... 34 Figure 12: Average and maximum salary weekly salary in NHL...... 34 Figure 13: Approxumated Matchday Income NHL...... 35 Figure 14: NHl TV Rights revenue...... 35 Figure 15: Internet users and television receivers estimation on the world ...... 36 Figure 16: UK Sport funding...... a Figure 17: Highest-Paying Sports Leagues - Average Player Salaries (2014/2015)...... b Figure 18: Revenue distribution of selected Premier League clubs...... d Figure 19: NHL teams operating income 2015...... f Figure 20: NHL average revenue per team 2005-2015...... g Figure 21:Maximum wage in EPL, approximation ...... l Figure 22: MLS average ticket price interpolation...... m Figure 23: NHL average ticket price approximation...... o Figure 24: Exponential estimation of television count...... p

52

List of tables

Table 1: Sports top earners over past 10 years...... 10 Table 2: Bonuses in 2014-2015 for World Championship per player...... 13 Table 3: Description of variables...... 37 Table 4: Regressions results...... 38 Table 3: TOP 30 most revenue football clubs 2014/2015...... c Table 4: MLS TV Deals History...... n

53

List of appendices

Appendix 1: UK Sport funding diagram ...... a Appendix 2: Average Player salaries – Highest Paying Sports Leagues (2014/2015) ...... b Appendix 3: TOP 30 most revenue football clubs 2014/2015 ...... c Appendix 4: Revenue distribution of selected Premier League clubs ...... d Appendix 5: Selected parts of NHL Collective Bargaining Agreement ...... e Appendix 6: Profit and loss of NHL clubs ...... f Appendix 7: NHL average revenue per team 2005/06-2014/15 ...... g Appendix 8: E-mail conversation with Premier League Customer Services ...... h Appendix 9: E-mail conversation with a selected Premier League club ...... j Appendix 10: Data approximations ...... l Appendix 11: MLS average ticket price interpolation ...... m Appendix 12: MLS TV Deals History ...... n Appendix 13: Linear approximation of NHL average ticket price ...... o Appendix 14: Exponential estimation of television count ...... p

54

Appendix 1: UK Sport funding diagram

Figure 16: UK Sport funding. Source: (UK Sport, 2015)

a

Appendix 2: Average Player salaries – Highest Paying Sports Leagues (2014/2015)

NBA, basketball (N.America) 4,33

IPL, cricket (India) 4,17

MLB, baseball (N. America) 3,82

EPL, football (England) 2,62

NHL, ice-hockey (N. America) 2,29

Bundesliga, football (Germany) 2,11

NFL, am. football (N. America) 1,86

La Liga, football (Spain) 1,74

Serie A, football (Italy) 1,49

Ligue 1, football (France) 0,66

NPB, baseball (Japan) 0,39

CSL, football (China) 0,31

Figure 17: Highest-Paying Sports Leagues - Average Player Salaries (2014/2015). Source: (Gaines, 2015)

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Appendix 3: TOP 30 most revenue football clubs 2014/2015

POS CLUB NAME 2014/2015 REVENUE M£ 1 FC Barcelona 560,8 2 Real Madrid 577,0 3 Manchester United 519,5 4 Chelsea 420,0 5 Arsenal 435,5 6 Bayern Munich 474,0 7 Liverpool 391,8 8 AC Milan 199,1 9 Paris Saint-Germain 480,8 10 Juventus 323,9 11 Manchester City 463,5 12 Borussia Dortmund 280,6 13 Atlético De Madrid 187,1 14 Tottenham Hotspur 215,5 15 AS Roma 180,4 16 Internazionale 164,8 17 Schalke 04 219,7 18 Everton 165,1 19 Newcastle United 169,3 20 West Ham United 160,9 21 Galatasaray 159,1 22 Southampton 149,5 23 Aston Villa 148,8 24 Leicester City 137,2 25 Sunderland 132,9 26 Swansea City 132,8 27 Stoke City 130,9 28 Crystal Palace 130,8 29 West Bromwich Albion 126,6 30 Napoli 125,5 Table 3: TOP 30 most revenue football clubs 2014/2015. Source: (Deloitte., 2016)

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Appendix 4: Revenue distribution of selected Premier League clubs

Revenue distribution in % of total

Matchday Broadcasting Commercial

Manchester United 22 27 51

Manchester City 12 39 49

Arsenal 30 39 31

Chelsea 22 43 35

Liverpool 19 42 39

Tottenham Hotspur 21 49 30

Newcastle United 21 60 19

Everton 15 69 16

West Ham United 16 65 19

Figure 18: Revenue distribution of selected Premier League clubs. Source: (Deloitte., 2016)

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Appendix 5: Selected parts of NHL Collective Bargaining Agreement

Full Agreement on (NHL, 2013), transcription taken from (CapFriendly.com, 2016)

Group VI UFA

A player whose contract is expiring and meets all of the following conditions shall become an unrestricted free agent (UFA):

1. The player is 25 years or older (as of June 30th of the calendar year the contract is expiring). 2. The player has completed 3 or more professional seasons - qualified by 11 or more professional games (for an 18/19 year old player), or 1 or more professional games (for a player aged 20 or older). This can include NHL, minor league, and European professional league seasons played while under an SPC. 3. The player has played less than 80 NHL games, or 28 NHL games of 30 minutes or greater for a goaltender.

NMC and an NTC

A No-Movement Clause (NMC) prohibits a team from moving a player, or assigning a player to the minor division without their consent (by trade, loan or waivers). This ensures the players’ presence on the team, unless they consent to moving. However, an NMC does not prevent a team from buying out or terminating a player’s contract. An NMC follows a player even if they waive the clause and are traded, but it does not protect a player from being bought out. A No-Trade Clause (NTC) is less restrictive, and only places restrictions on player movement as a result of trades. A player with an NTC cannot be traded to another team unless the player provides consent. However, player consent is not required for placement on waivers or assignment to minors. An NTC does not follow a player if they waive a full NTC, or are traded within the terms of a limited or modified NTC. A Partial or Modified No-Trade Clause (PNTC) is less restrictive than a Full No-Trade Clause, dependent upon specific conditions outlined in the players’ contracts. PNTC often include conditions outlined by the player (that may include a list of teams to which the team may not trade the player). Players will often have NMCs tied to their contracts with Partial or Modified No-Trade Clauses. These prevent the team from moving the player via loan or waivers, but give the team some options for trading the player. Players are not eligible for NMCs or NTCs in their contract until they are eligible for Group 3 Unrestricted Free Agency (7 accrued seasons or 27 years of age). Players may sign contracts with NMCs or NTCs that may become active partway through their contract, whereupon they become eligible for Group 3 Unrestricted Free Agency.

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Appendix 6: Profit and loss of NHL clubs

-40 -20 0 20 40 60 80 100

Montreal Canadiens New York Rangers Toronto Maple Leafs Chicago Blackhawks Vancouver Canucks Boston Bruins Calgary Flames Pittsburgh Penguins Ottawa Senators Dallas Stars Edmonton Oilers Philadelphia Flyers Winnipeg Jets San Jose Sharks Washington Capitals Columbus Blue Jackets New Jersey Devils Detroit Red Wings Buffalo Sabres Los Angeles Kings Nashville Predators Minnesota Wild Anaheim Ducks Tampa Bay Lightning Colorado Avalanche Phoenix Coyotes St. Louis Blues Carolina Hurricanes New York Islanders Florida Panthers

Figure 19: NHL teams operating income 2015. (Statista, 2016)

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Appendix 7: NHL average revenue per team 2005/06-2014/15

140 132,63 123,33 120 112,47 103 97,63 100 91,57 93,97 87,67 81,2 8075,57

60

40

20

0 2005/06 2006/07 2007/08 2008/09 2009/10 2010/11 2011/12 2012/13 2013/14 2014/15 33 Figure 20: NHL average revenue per team 2005-2015. (Statista, 2016)

33 Season 2012/2013 was only 48-game-long instead of standard 82 due to lockout caused by NHL CBA negotiation between NHL and the National Hockey League Players‘ Association (Hughes, 2013).

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Appendix 8: E-mail conversation with Premier League Customer Services

From: Matej Drozd To: Premier League Customer Service

Good day,

I am student of Masaryk University in Brno, Czech Republic. I am working on the thesis where I analyze various effects (mainly the role of media) on the wages in football. For my analysis I need anonymous information about player wages. In fact I only need the average and top wage from each year for as long period of time as possible. Also various other information like: average attendance, average ticket price, estimated TV viewers, estimated fanbase size and possibly revenues from merchandising. Would it be possible to obtain this data from you or some other organization?

Thank you Kind Regards

Matej Drozd Masaryk University, Brno, Czech Republic

To: Matej Drozd From: Premier League Customer Service

Hi Matej

I’m afraid this type of information is not generally available in the public domain and much of the data we have is held privately for our clubs to use.

We do have a research portal, which provides insight into activities across our League: http://fanresearch.premierleague.com/

Only clubs will have accurate data on player wages, but I suspect they are unlikely to share this widely. Ticket prices and attendance figures they may be better placed to share.

You will find contact details for our current member clubs in the document attached.

Sorry we can’t be of more help

Tommy

Supporter Services

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From: Matej Drozd To: Premier League Customer Service

Good day, thank you for reply and the information.

I will try to contact football clubs.

Or, maybe sportingintelligence may help? I found this article by Nick Harris: http://www.sportingintelligence.com/2011/01/20/from-20-to-33868-per-week-a-quick-history-of- english-footballs-top-flight-wages-200101/

So there may be the complex information.

Kind Regards

Matej Drozd

To: Matej Drozd From: Premier League Customer Service

Hi Matej

I can’t speak to the accuracy of the article, as it’s not an authorized source of information. Nick (through Sporting Intelligence) does a lot of work in this area, so it would certainly be worth contacting him for further guidance on sources, and to see what data he can share.

Best regards

Tommy

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Appendix 9: E-mail conversation with a selected Premier League club

From: Matej Drozd To: Leicester City FC Help

Good day, my name is Matej Drozd from Masaryk University, Brno, Czech Republic and I am doing an academy research where I am analyzing the impact of various factors on the height of average and top wages in football.

For my research I need the anonymized average wage of premier league for significant number of years and the top wage from every year (also anonymized).

I really don't need any names, just two numbers from each year for as long time period as possible. (e.g. average club wage, top club wage).

This data will very help to make this research as relevant as possible.

If you need more information about the research, or the University, or myself (I understand that the data I am requesting may be confidential) or some clarification of the research, please don't hesitate to ask.

Thank you very much in advance

Kind Regards

Matej Drozd

From: Leicester City FC Help To: Matej Drozd

Dear Matej,

Thank you for your email to Leicester City Football Club. Unfortunately this is not something we can help you with, I hope you understand that this is sensitive information and private to each individual.

I am sorry I can be of more help on this occasion.

Kind Regards

Jim

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From: Matej Drozd To: Leicester City FC Help

Good day, thank you very much for your quick reply.

The information about wages are of course confidential. But there are some occasions I found some clues about wages, like the articles from Sporting Intelligence or the Sports Interactive games. I don't know how they came to their data, I was unable to contact them. But somehow there might be possibility to acquire this data. I asked the Premier league as the organization for data or at least for some guide how to get those and they gave me contact for each of Premier League club to ask them (you) directly. So I did so.

I really don't need a personal data. I won't even mention which club has how big average wage or top wage. All I need is to analyze the effect of various factors on these two wage indicators for the whole league. So if I will be able to collect the data from each club, I will make the average wage for the whole group and take the top wage for each year. It is not important who was the best paid footballer in the league, only the number is important.

After the more-deep explanation, do you think you might help me somehow?

Thank you

Kind Regards

Matej Drozd

From: Leicester City FC Help To: Matej Drozd

Dear Matej,

Thank you for your further comments, unfortunately this is not something we would give out to anyone. We have a duty of care to all members of staff not to mention data protection of the issue.

Please accept my apologies once again for not being able to help you.

Kind Regards

Jim

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Appendix 10: Data approximations

Figure 21:Maximum wage in EPL, approximation. Source: (Harris, 2011), (Nepal, 2014), own calculation

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Appendix 11: MLS average ticket price interpolation

Figure 22: MLS average ticket price interpolation.

Source: (Curry, et al., 2004), (Slideshare, 2008), (Mitchell, 2008), own calculations

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Appendix 12: MLS TV Deals History

MLS TV Deals History Years Networks Total Avg. Annual Value 2015-22 Fox/ESPN $600 mil $75 mil 2015-22 Univision $120 mil $15 mil 2012-14 NBC $30 mil $10 mil 2007-14 ABC/ESPN $64 mil $8 mil 2007-11 Fox Soccer Channel $11 mil $2,2 mil 2007-14 Univision $79,4 mil $9,9 mil 2007-09 AXS TV (formerly HDNet) $3,25 mil $1,08 mil Table 4: MLS TV Deals History. Source: (Ourand, et al., 2014)

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Appendix 13: Linear approximation of NHL average ticket price

Figure 23: NHL average ticket price approximation.

Source: (Statista, 2016), (DiGiovanna, 1993), (BonkTastic, 2012)

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Appendix 14: Exponential estimation of television count

Figure 24: Exponential estimation of television count. Source: (OK nation, 2008)

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