RIVALRIES in SPORTS COMPETITIONS and in the GLOBAL MEDIA SHOWCASE Rivalidades En Las Competiciones Deportivas Y En El Escaparate

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García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201.

RIVALRIES IN SPORTS COMPETITIONS AND IN THE GLOBAL MEDIA SHOWCASE Rivalidades en las competiciones deportivas y en el escaparate mediático mundial Pedro Garcia-del-Barrio, Nicolás Becerra Flores, Jef Schröder Aubert Universitat Internacional del Catalunya, Spain

ABSTRACT: This paper examines how players compete in the global media showcase as well as in the sporting field. Special attention is paid to the role that players’ rivalries might have to raise the interest on particular sport disciplines worldwide. The paper initially compares the individuals’ media status, as a way to measure of the degree of attention they draw from supporters and the public around the world. To selected the group of superstar players, we first identify the Top-10 athletes with the greatest levels of visibility in the media. The appraisals, based on “Google Trends”, are computed based on the intensity of searches made by Google users that are related to each individual. Cristiano Ronaldo emerges as the player with greatest number of searches, thereby taking the reference value 100. Then, adopting a complementary approach, the paper examines the Top-10 most popular soccer players worldwide. In this case, our calculations are based on MERIT approach (methodology for the evaluation and rating of intangible talent), which evaluates the level of talent by counting the news articles that each superstar generates in the media. We actually calculate the individual index of media value as the factor by which the number of news articles associated to each player multiplies the corresponding figure of the representative (average) player in our data base. KEY WORDS: Sport stars; sport rivalries; media visibility

RESUMEN: Este artículo examina cómo compiten las estrellas del deporte por estar presentes en el escaparate mediático global, además de competir en el terreno de juego. El análisis concede especial atención al papel que las rivalidades entre jugadores pudieran jugar de cara a aumentar el interés de ciertos deportes en todo el mundo. La comparación del estatus mediático se efectúa evaluando el grado de atención mundial que los jugadores reciben de parte de los aficionados y del público en general. Primero, identificamos el Top-10 de estrellas del deporte, de cualquier disciplina, que disfrutan de mayores niveles de visibilidad mediática. Nuestras valoraciones inicialmente se basan en “Google Trends”, que proporciona datos de la intensidad con que los usuarios de Google buscan información de cada protagonista. Cristiano Ronaldo resulta ser el jugador con más número de búsquedas en los últimos años, por lo que se le asigna el valor de referencia 100. En segundo lugar, adoptando un enfoque complementario, se analiza el Top-10 de los futbolistas más populares del mundo. En este caso los cálculos se elaboran mediante el enfoque MERIT (metodología para la evaluación y calificación del talento intangible), que elabora índices para medir el talento a través del número de noticias generadas en los medios por las estrellas deportivas. Concretamente, el índice individual del valor mediático se calcula como el factor por el que el número de noticias asociadas a un jugador multiplica a las noticias correspondientes al jugador representativo (medio) de nuestra base de datos. PALABRAS CLAVE: Estrellas del deporte; rivalidad deportiva; visibilidad mediática Received/recibido: 12-10-2019 Accepted/aceptado: 10-12-2019 Contact information:

Corresponding author Pedro Garcia-del-Barrio Nicolás Becerra Flores Jef Schröder Aubert [email protected] [email protected] [email protected] c/Immaculada 22, 08017 c/Immaculada 22, 08017 c/Immaculada 22, 08017 Barcelona, Spain Barcelona, Spain Barcelona, Spain

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 185 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201.

“Their matches [between Roger Federer and Rafael Nadal] were definitely great, but there were big rivalries like Boris Becker and Stefan Edberg, Andre Agassi and Pete Sampras, me [John McEnroe] and Bjorn or me [John McEnroe] and Jimmy (Connors). But the level reached by Roger, Rafa and Novak is historically unique.”

John McEnroe, 2019)1

1. Introduction

This paper studies how sportspersons compete in the global media showcase as well as in the sporting field. The scope of the paper includes examining the role that players’ rivalries might have concerning their capacity to expand the attention paid to different sports worldwide. Rival contenders in sports are tied by rules that are binding for every specific discipline that the athletes perform. On the contrary, the global media showcase offers to all kind of individuals – regardless of the sport they engaged at – the chance to compete under the same terms to pursue the same goal: trying to draw the interest of followers, journalist and the general public. To measure the degree of popularity and media visibility of the selected group of star players – who concentrate the attention of sport fans and the public – we adopt two approaches. The complementarity of these approaches is apropos for analyzing also the extent to which sport rivalries between certain players is related to the degree of media exposure and popularity. The paper’s objective is not to modeling or assuming statistical causality links, but rather to examining the involvement that sport rivalries may have concerning the superstar players’ visibility in the media. The enjoyment of consumers of sport entertainment depends on the level of excitement delivered by sport spectacles and competitions, which in turn depends on aspects like: empathy feelings, the presence of attractive icons or sport rivalries. Previous papers focused on how “Uncertainty of Outcome” (UO) affects the degree of interest of the followers of sport competitions2. The economic literature has also discussed, since long ago, several aspects related to the role of prominent superstars and the peculiar features occurring in the markets where they are present. The seminal paper by Rosen (1981) stressed the link between sport talent and the superstar status, while Adler (1981) also mentioned the externalities associated to the individuals’ popularity. Precisely, extensions of these ideas invite studying further the role of local and global rivalries in sports3. The literature (Cf. Brandes et al. (2008); or Franck and Nüesch

1 Retrieved on Sept. 2019 from: https://www.tennisworldusa.org/tennis/news/Roger_Federer/77248/mcenroe- shares-why-roger-federer-v-rafael-nadal-rivalry-is-not-the-greatest/ 2 The “Uncertainty of Output Hypothesis” (UOH) is a central aspect in economics of professional sports: Cf. Rottenberg (1954) and Neale (1964). There is however disagreement on the relevance of the UOH, given the contrasting evidence on how competitive balance affects fans’ interest in sports: Cf. Borland and Macdonald (2003); Garcia and Rodriguez (2002); Coates and Humphreys (2010); and Coates and Humphreys (2012). 3 Cf. Garcia-del-Barrio (2018), who identifies global sport icons in Soccer and Formula One and compares a

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 186 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201.

(2012), among others) highlights the relationships between sport talent, popularity and superstar status. More recently, other researchers (Cf. Garcia-del-Barrio and Pujol (2016) and Korzynski and Paniagua (2016)) provide empirical evidence to support that visibility in the media works along with sport talent to explain the players’ actual market value. The interest on sport events depends on factors that explain its success in terms of both entertainment quality and economic returns. Important variables in this regard include: concentration of sport talent; identification with certain players, teams or leagues; sport brands predominance; team dynasties; excitement in betting; outcome uncertainty; superstars’ popularity; local and global rivalries, etc. This paper deals with the aforementioned factors, paying special attention to stardoms and rivalries. Sport rivalries, between individuals or teams, have always been an important source of excitement for attracting people to follow sport events and competitions. In recent times, thanks to the development of new technologies, we have witnessed some top- class global rivalries, involving contenders from the most popular sport disciplines worldwide: soccer, basketball and tennis. Precisely, John McEnroe referred to this issue when a journalist asked him about the current rivalry between Federer and Nadal. In his answer, the famous former tennis player mentioned other rivalries, like those held by: Boris Becker vs. Stefan Edberg, Andre Agassi vs. Pete Sampras, he [McEnroe] vs. Bjorn or he [McEnroe] vs. Jimmy Connors, while considering that: “the level reached by Roger, Rafa and Novak is historically unique.” In this paper we examine to what extent these exceptional sport rivalries go along with outstanding levels of media visibility and popularity.

2. Methodology and data collection

To accomplish the goals of this paper we combine different methodological approaches. Initially, we select the Top-10 athletes using data from two main sources: the “World Fame 100” ranking elaborated by ESPN and “Google Trends”. The former source helped us to identify the most important athletes around the globe in terms of popularity and status4. Once we identify the top 10 individuals, we lined up the ranking based on relative searches using Google Trends. In order to accomplish this, we carried out a more refined analysis with monthly appraisals from “Google Trends”. The final result was obtained by computing the average number of monthly searches made by Google users in the last five years (2014-2019), associated number of rivalries within a global analysis framework. Other papers address the use of social media to examine business development and brand management. (For instance, Parganas et al. (2015) and Baines (2019) address the global industry of soccer, focusing on Twitter’s followers). 4 Retrieved on June 2019 from: http://www.espn.com/espn/feature/story/_/id/26113613/espn-world-fame-100- 2019. A methodological description is provided from the same source: “Search score: Measuring how often a name is searched on Google. We took a weighted average of an athlete's Google Trends peak score (how much he spiked on his most searched day) and his average score (how much he was searched throughout [a particular year], on average); Endorsement dollars: sources ranged from Forbes to ESPN contributors; Social media followers: Since not all athletes are on every platform, only the number from their most popular account was used.”

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 187 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201. to every sportsperson (where the individual with the highest value, Cristiano Ronaldo, appears as the reference, taking value 100). We first examine the sport rivalries among the Top 3 superstar players in each selected sport discipline: soccer, tennis and basketball. To this aim, instead of Google Trends, we adopt the MERIT (methodology for the evaluation and rating of intangible talent) approach, a more versatile methodology that allows us performing searches involving two competitors simultaneously. This procedure enables us capturing the join popularity (and comparative appraisals) of rivalries between pair of individuals. The actual figures of the latter are calculated as the joint number of appearances found in Internet (Google Web) over the last 8 years. We then focus on the Top-10 most popular soccer players worldwide. Again, we resort to the MERIT approach to compute the calculations and produce appraisals of the social and media value of talent. This task is accomplished through collecting the number of news articles generated by each of the sport superstars. We actually calculate the individual index of media value as the factor by which the number of news articles associated to a player multiplies the news of the representative (average) player of our sample of more than 5,000 individuals. Additional information on the MERIT project and methodology can be found at: www.meritsocialvalue.com. Notice that the MERIT approach is actually able to capture the players’ personal skills jointly with their attractiveness beyond sport performance. Therefore, the method used to capture the players’ talent comprises the value of sport talent along with its capacity to generate commercial revenues. In that way, we acknowledge that the intensity with which individuals are exposed in the media showcase is the result of their sport performance, but also derives from the recognition of skills that make them attractive to the public.

3. Discussion of the results

This section is organized in three parts. First, Top-10 global sport superstars are identified and ranked according to their level of popularity, based on calculations elaborated from Google Trends’ figures. Second, Top global rivalries are studied for three major sports: soccer, tennis and basketball. Then, we also try measuring the empirical link between those rivalries and the attention paid by the public to every sport discipline. Finally, our attention focusses on the Top-10 soccer players. To identify this selected group, we rely on data on the degree of visibility in the media during the last eight years. In this context, a regression analysis is applied in estimating models to examine the relationship between sport performance and degree of attention of the supporters and the general public.

Top-10 global sport superstars

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 188 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201.

We start selecting the Top-10 athletes relying on two sources: the “World Fame 100” ranking released by ESPN (2019); and comparative figures reported by “Google Trends”. The former source helped us selecting the most relevant sportspersons worldwide in terms of public attention: endorsements revenues, followers in social networks and Internet search score. The chosen Top-10 sportspersons are then ranked on the grounds of the status they achieved according to monthly Google Trends appraisals. Table 1 reports average records of the Top-10 competitor players who show a high- profile global dimension. The records are obtained by computing the average number of monthly searches made by Google users during the last five years (2014-2019) associated to each athlete. In the analysis, the individual with the highest number of searches is Cristiano Ronaldo, who is thus appointed as the reference value of 100. The results of our analysis are similar to the ranking produced by ESPN, although there are several changes of hierarchy. Among other results, it seems that soccer players are the most popular athletes worldwide. Other sport disciplines that also stand out are: tennis, basketball and golf. A more detailed analysis of individual rivalries is carried out later in this section.

Table 1. Top-10 Global Athletes (Google Trends Average: April 2014 to April 2019)

Google Trends Athlete Sport Country Average (wrt 100)

1 Cristiano Ronaldo Soccer Portugal 100,00 2 Lionel Messi Soccer Argentina 71,21 3 Neymar Jr. Soccer Brasil 45,23 4 LeBron James Basketball United States 34,87 5 Roger Federer Tennis Switzerland 22,41 6 Rafael Nadal Tennis Spain 19,50 7 Stephen Curry Basketball United States 17,80 8 Novak Djokovic Tennis Serbia 12,38 9 Kevin Durant Basketball United States 11,75 10 Tiger Woods Golf United States 11,41

Source: authors’ calculations from Google Trends Web

An illustrative description on how the popularity of the Top-10 superstars evolved over the 5-years period is shown in Figure 1. The information is again taken from Google Trends, which provides comparative figures of the number of Internet searches associated to individuals, expressing them with respect to the maximum reference value of 100. Notice that these findings can be interpreted as the popularity ranking produced by hundreds of thousands and more often millions of Internet users, whose intensity in their searching activity deliver meaningful comparative figures that allow us ranking the media and popularity status of the players.

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 189 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201.

100 Google Trends - Global Sports 90 80 70 60 50 40 30 20 10 0

LeBron James Stephen Curry Tiger Woods Roger Federer Cristiano Ronaldo Lionel Messi Neymar Rafael Nadal

Figure 1. Top-10 Global Athletes Evolution (Google Trends Average: 2014-2019)

Not surprisingly, the two picks with greatest attention are associated to circumstances concerning Cristiano Ronaldo. First, in October 2014, he became the first sportsperson to reach 100 million followers in the Facebook fanbase. Besides, he was the foremost player of the Portugal national team in the World Cup 2014, one of the teams that reached the semi-finals.5 The second pick, occurring around July 2018, was presumably related to Ronaldo’s change of team, as he moved from Real Madrid to Juventus Turin.

Global rivalries in soccer, tennis and basketball

In this section, our attention focuses on the analysis of rivalries among the Top 3 superstar players in each of the selected sport disciplines: soccer, tennis and basketball. As it was already explained, we adopt to this aim the MERIT approach, which permits carrying out searches including two rivals at the same time. Thus, we capture joint popularity levels to capture the intensity of the existing rivalries between pairs of individuals. The actual figures are calculated as the joint number of contents in Google Web search engine during an 8-years period. Table 2 reports the number of players’ appearances (in Millions) found in Internet for the period: from September 2011 to September 2019. The values of individual players are highlighted in bold in the main diagonal of the each of the matrices. The

5 Ronaldo suffered from a knee injury that threatened his World Cup participation, but was eventually ready to face Germany in the semifinal. Moreover, in the same year 2014, Ronaldo was named in Time 100. Time’s annual list of the most influential people in the world: “Cristiano Ronaldo by Pelé: TIME 100”. Time, 23 April 2014. Retrieved on: February 2020.

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 190 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201. other values (also in Millions), not highlighted in bold, measure the popularity levels attached to the rivalries of the pairs of stars players that were considered in our analysis. Table 2. Global rivalries of sport superstars – Soccer, Tennis and Basketball Ronaldo Messi Neymar Ronaldo 102 73.8 47.6 Messi - 80.2 43.5 Neymar - - 41 Federer Nadal Djokovic Federer 20.6 21.5 11.6 Nadal - 37.6 11.8 Djokovic - - 13.9 LeBron Curry Durant LeBron 28.7 10.3 18.2 Curry - 26 11.9 Durant - - 33

Source: authors’ calculations with MERIT approach from Google Web

Table 3 displays additional calculations to compare the absolute and relative importance of the main global rivalries in the three professional sports under scrutiny. It seems that the most prominent rivalries, attracting the greatest attention levels are found in soccer. A deeper examination of the results reveals that, in absolute terms, the rivalry between Ronaldo vs. Messi is at the top, followed by the rivalry between Ronaldo vs. Neymar and Messi vs. Neymar, respectively. Far behind there are the main rivalries found in tennis and in basketball. Apart from soccer, the rivalry between two tennis players (Federer vs. Nadal) displays high levels of popularity, followed by the rivalry of LeBron vs. Durant. The primacy of soccer over other sports is anyway undisputable, reaching levels of 4 times greater than the attention drawn by basketball rivalries and nearly 3.7 times greater than the ones found in tennis. Expression (1) and (2) illustrate some calculations:

!"##$% !"#$%&'( !"#$%&"'( !"#.! = = 4.08 (1) !"#$%&'"(( !"#. !"#$%&"'( !".!

!"##$% !"#. !"#$%&"'( !"#.! = = 3.67 (2) !"##$% !"#. !"#$%&"'( !!.!

Our interest involves also investigating to what extent sport rivalries act as a driving force to expand the attention levels paid by fans and the public to certain star players and to their respective sport discipline. To this aim, we also perform calculations of the rivalries expressed in relative terms. The results of this exercise are reported in the last column of Table 3, revealing closer and more evenly distributed results than

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 191 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201. absolute rivalries. To rightly interpret the meaning of relative rivalries, consider the questions they try to answer: To what extent do rivalries between two players contribute to the joint popularity of both players? Are they an important driving force to increase the interest of people in the respective players and their sport discipline? What are the most valuable rivalries irrespective of the specific sport discipline considered?

The answers to these questions are found in Table 3 and Figure 2. Notice that several relative rivalries appear as being very close to each other. Actually, even if the rivalry between Ronaldo vs. Messi is again greater than any other rivalry concerning relative figures (as in absolute terms), the relative rivalry between Federer vs. Nadal is almost as relevant as the former one. Besides, relative rivalries in basketball are also closer to the soccer ones: LeBron vs. Durant, for instance, is only 11 points behind the top rivalry between Ronaldo and Messi.

Table 3. Global rivalries of sport superstars – Soccer, Tennis and Basketball Joint Absolute Relative Absolute Relative Popularity Rivalry Rivalry Rivalry Rivalry (GWEB: player (GWEB: player (B/A*100) (wrt 100) (wrt 100) "i" OR "j") "i" AND "j") A B C B (wrt C (wrt (in Mill.) (in Mill.) (B/A*100) Max. Max. =100) =100) Ronaldo vs. 182.2 73.8 40.5% 100.0 100.0 Messi Ronaldo vs. 143.0 47.6 33.3% 64.5 82.2 Soccer Neymar Messi vs. 121.2 43.5 35.9% 58.9 88.6 Neymar Federer vs. 58.2 21.5 36.9% 29.1 91.2 Nadal Federer vs. 34.5 11.6 33.6% 15.7 83.0 Tennis Djokovic Nadal vs. 51.5 11.8 22.9% 16.0 56.6 Djokovic LeBron vs. 54.7 10.3 18.8% 14.0 46.5 Curry LeBron vs. 61.7 18.2 29.5% 24.7 72.8 Basket Durant Curry vs. 59.0 11.9 20.2% 16.1 49.8 Durant

Source: authors’ calculations with MERIT approach from Google Web The calculations of relative rivalries are interesting for comparison purposes, as they allow us to rank their importance across sport disciplines. Indeed, the overall popularity of a particular sport may inflate or penalize the relative relevance of a pair of players’ rivalry. Moreover, the analysis of rivalries may help to understand the increasing success of European soccer worldwide. To facilitate interpreting the previous analysis, Figure 2 illustrates the main findings.

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 192 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201.

Figure 2. Global Rivalries in Soccer, Tennis and Basketball (Google Web Average: 2011- 2019)

An extension of the study on how sport rivalries relate to rivalries in the global media showcase can be made examining the empirical relationship between sport performances and the degree of interest generated. To illustrate this point, we focus on the tennis industry of spectacle; where, given the structure of the games, the rivalries do typically involve pairs of players. Initially, for illustrative purposes, Figure 3 shows the results of the regression analysis applied to the baseline model, where levels of the fans’ interest, proxied by search intensity in Google are explained based on the players’ sport performances, as captured by the ATP points. The empirical analysis is conducted on a data set

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 193 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201. comprising six players (Rafael Nadal; Roger Federer; Andy Murray; Novak Djokovic; Juan Martín del Potro and Kei Nishikori) over a 10-years period (from 2010 to 2019).

y = 1.5011 x + 3.5096 35 R² = 0.4634

10 Google Trends Index Index Trends Google

0 0 2.000 4.000 6.000 8.000 10.000 12.000 14.000 16.000 18.000

ATP Points

Figure 3. Baseline Model: Google Trends versus ATP Points – Tennis Players

Nonetheless, other model specifications overperform the too simple one shown in the figure. Table 4 reports the estimation results of alternative models. The first one, in column (1), presupposes a non-linear (quadratic) functional form, which is typically associated to productivity. The explanatory power of model (1) is greater (R2=0.536) than the baseline model, but it is far below the models discussed in the next paragraph. Actually, the role of rivalries and their capacity to boost the popularity of sport spectacles is presumably linked to winner-take-all effects. The winner-take-all phenomenon was extensively discussed by Frank and Cook (1995), who claim that increasing number of markets − including arts, sports and pop culture – exhibit rewarding schemes in which the fact of being marginally better than your rival competitors implies outcomes greater than proportional to your performance. More recently, Rosen and Sanderson (2001) argue that winner-take-all effects impact on an increasing number of activities and labour markets. More recently, Garcia-del- Barrio and Pujol (2007) and (2015) provide empirical evidence of a strong presence of winner-take-all elements in, respectively, the soccer and tennis industries.6

6 Their paper actually shows that the winner-take-all phenomenon affects more intensively to tennis players

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 194 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201.

Table 4. Sport Performance vs. Google Trends and winner-take-all effects in Tennis.

Dependent Variable Google Trends Index

Pooled OLS Pooled OLS Pooled OLS Fixed Effects

Model (1) Model (2) Model (3) Model (4) Points ATP 3.4274 *** 1.0686 *** 1.2077 *** 1.1095 *** (5.10) (14.13) (4.41) (4.01) Points ATP Squared -0.1380 ** -0.0096 -0.0081 (-3.00) (-0.53) (-0.44) Winner-Take-All_1&2 13.7928 *** 13.6528 *** (20.88) (19.08) Constant -0.8049 1.6203 ** 1.3376 0.7767 (-0.39) (2.93) (1.73) (0.87)

Fixed Effects No No No Yes

R-squared 0.53675 0.93797 0.93828 0.94504 Adjusted R-squared 0.52050 0.93579 0.93497 0.91841 Multiple corr. coeff. 0.73264 0.96849 0.96865 0. 97213 No. Obs. 60 60 60 60

Note: t-statistic in parentheses. *** P-value < 0.001; ** P-value < 0.01; * P-value < 0.05 ***, **, and * denote significance at the 99%, 95%, and 90% confidence levels, respectively.

Precisely to complement the variable capturing sport performance, and to corroborate the existence of winner-take-all effects, models (2) and (3) incorporate to the estimations a dummy variable called “Winner-Take-All_1&2”, which takes value one for the ATP leaders (the tennis superstars: Federer and Nadal) and zero for the other players. On one hand, the results of models (2) and (3) in Table 4 reveal the significant impact of the winner-take-all element; and, hence, the important role that global rivalries may have in increasing the fans’ degree of interest. Concerning the statistical properties of the models suggest that the preferred one may be model (2), with Adjusted R2=0.935. On the other hand, the estimation results of the fixed effects model (4), reported in the last column, are also enlightening, as they convey similar results than model (2) while taking into account individual heterogeneity elements. Besides, we find that the values of the fixed effect associated to each of the Top-2 players (Roger Federer: 15.86 and Rafael Nadal: 13.88) clearly exceed the other contestants. Notice anyway located in the upper tier of the talent distribution. Specifically, there is evidence that the players’ visibility in the media increases along with sport performance, but as regards top players - like Nadal or Federer – the growth in rewards (either money prizes or visibility) is more than proportional to their sport achievements. Furthermore, Garcia-del-Barrio and Pujol (2015) conclude that a substantial part of the global media attention raised by tennis tournaments in 2007 was due to just some top 20 players, who were responsible of 30% of the total media exposure.

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 195 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201.

that, since the number of superstars is a matter of choice, the regression analyses were made for different arrangements of players. However, grouping the players in pairs is not casual, since tennis contests structure typically entail rivalries where the two protagonists share a similar level of interest. (Cf.: Garcia-del-Barrio & Pujol, 2015). This is particularly the case at the top, for players who reach the finals, but also applies to earlier stages of tennis tournaments.

Top-10 superstar soccer players worldwide

The next analysis concentrates on the Top-10 most popular soccer players. This time, to identify the selected group of athletes, instead of using Google Trends figures, we rely on the MERIT approach’s capacity to measure the degree of interest shown by supporters, journalist and the general public. Notice that this is the same methodology than the one we used in the precedent section to obtain the individual and joint ratings of players in order to compare the relative interest generated by global rivalries. In Table 5 we report the MERIT media value index corresponding to the Top-10 superstar soccer players whose media value (on average during 8 seasons) was above the scores reached by other competitors. Table 5. Soccer Players Media Value – Seasons 2010/11 to 2017/18

Player 2010/11 2011/12 2012/13 2013/14 2014/15 2015/16 2016/17 2017/18 Average 1 Lionel Messi 36.35 46.55 33.72 24.52 52.78 67.12 90.53 95.36 55.87 2 C. Ronaldo 29.94 36.57 30.75 37.89 49.92 59.27 91.74 81.44 52.19 3 Neymar Jr. 1.2 7.19 13.27 16.36 26.5 42.74 42.94 67.27 27.18 4 W. Rooney 19.09 15.47 17.48 16.57 36.94 30.49 30.13 10.88 22.13 5 Luis Suárez 2.1 10 10.48 8.73 29.94 28.77 22.35 35.35 18.47 6 Gareth Bale 6.53 4.44 10.34 19.77 22.13 23.65 25.35 25.69 17.24 7 S Ramos 6.39 9.27 9.71 15.66 10.01 16.12 21.57 24.89 14.20 8 Ibrahimovic 10.02 16.92 11.16 6.55 5.92 16.83 27.41 14.54 13.67 9 A. Iniesta 14.54 16.2 11.96 8.66 8.29 14.21 17.64 15.27 13.35 10 Benzema 8.88 14.65 8.3 12.29 7.93 16.52 19.48 16.09 13.02 Source: MERIT social value – Author’s own calculations. Among other findings, Table 5 suggests that the rivalry between Messi and Ronaldo, the two colossal soccer players, is long-lasting. Indeed, these two players represent the utmost icons in professional soccer over the last decade. Since the signing of Cristiano Ronaldo for Real Madrid in 2009, both players have been protagonists of a fierce competition in-field, but also off-field to attract attention in the media showcase. They have been the main leaders of their respective clubs, forming one of the greatest historical sport rivalries worldwide. Their role into the squad has also helped their clubs, Real Madrid and FC Barcelona, to build perhaps the strongest

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 196 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201. team rivalry ever seen in the context of professional European soccer. Then, behind these two giants, we found Neymar Jr., who experienced a noteworthy development in recent years. At joining the FC Barcelona, in season 2013/14, he became an important element in the rivalry between Real Madrid and Barcelona, who even competed in popularity share with Messi and Ronaldo. Most of the other players in the ranking are the leader player in their own clubs and domestic leagues. Finally, this section presents the results of using regression analysis as an indirect tool for exploring the role of rivalries, as inferred from the existence of non- linearities and/or significant statistical effects of the dummy variables capturing winner-take-all elements. To this aim, we carry out a prospective analysis by estimating linear and non-linear functional forms of an index of media visibility status with respect to the corresponding rank position of the players, also measured by the MERIT index. Of course, this exercise does neither aim to verify causality links or to corroborate the obvious positive signs of the estimated coefficients for rank. Instead, the purpose is looking for empirical evidence on the presence of winner- take-all patterns in sports spectacles, which might be due to the capacity of global sport rivalries to generate greater levels of interest among the public and sport fans. This simple empirical exercise is apropos for exploring initially the existence of winner-take-all elements that are typically at work in professional sport labour markets. Actually, the comparison between Model (1) and (2) leads to conclude that, rather than the non-linear relationship, it works better including dummies to account for winner-take-all elements: the “Winner_All_1&2” variable, collecting in this case Messi and Ronaldo. In other words, the better statistical properties of Model (2) seem to suggest that the initial seeming non-linearity may be explained, to a very large extent, by controlling for the observations of the Top-2 players.

Table 6. Rivalries and winner-take-all effect in Soccer - Pooled OLS.

Dependent Media Media Index (wrt Index Variable Visibility Visibility 100) Model (1) Model (2) Model (3) Model (4) Rank -14.0117 *** -13.9306 *** -6.4324 *** -18.2809 *** (2.2896) (2.2519) (0.4770) (2.1939) Rank_squared 0.8022 *** 0.9546 *** (0.2029) (0.1737) Winner_All_1&2 0.7981 *** 24.3533 *** 10.8763 *** (0.2002) (2.990) (3.5349) Constant 70.9098 *** 70.5407 *** 73.4284 *** 104.5377 *** (5.4823) (5.3751) (3.2168) (6.2887)

R-squared 0.60474 0.60584 0.891930 0.92266 Adjusted R-squared 0.59448 0.59561 0.889123 0.91960 Multiple corr. coeff. 0.77765 0.77836 0.94442 0.96055

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 197 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201.

No. Obs. 80 80 80 80

Note: Standard errors in parentheses. *** P-value < 0.001; ** P-value < 0.01; * P-value < 0.05 ***, **, and * denote significance at the 99%, 95%, and 90% confidence levels, respectively.

Then, for the sake of robustness, the estimation of Model (2) is replicated in Model (3) using the media visibility index re-scaled and expressed with respect to 100. The results are shown in Table 6. Notice that, even if both approaches are ultimately similar, the latter method is expected to yield better outcomes, as it avoids the loss of explanatory power associated to using different scales. Then, Model (4), the one that includes winner-take-all effects, along with the quadratic form, over performs the estimation results of Model (3). All the estimated coefficients in Model (4) are statistically significant, meaning that the non-linearity applies all along the media visibility distribution, and not just to the upper tier. To further illustrate the findings of the last empirical analysis, we collected the residuals of Model (3) and used them to plot the deviation of the “Media Visibility” model predicted values from the actual values. The main results are shown in Figure 4 and Figure 5.

120 Actual MV (blue+black) vs. Predicted MV (blue+white) Top-10 Soccer Players - From 2010/11 to 2013/14

100

Figure 4. Functional Form and Winner-take-all Effect

From the figures, it seems clear that the presence of winner-take-all elements may be able to explain the patterns found at the extreme of the players’ talent distribution. The relationship between the players’ rank and their media visibility index is of course positive. Besides, position improvements in the ranking go along with media visibility levels that are increasingly bigger. Furthermore, this pattern experiences a sharp increase for the top players in the ranking. We venture that these features, typically associated to the winner-take-all phenomenon, may be nurtured by rivalries

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 198 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201. between players. However, this hypothesis demands further research, as the gap affecting the star players at the top may be simply due to winner-take-all effects linked to individual media visibility, rather than due to the joint effect of their global rivalry.

120 Actual MV (blue+black) vs. Predicted MV (blue+white) Top-10 Soccer Players - From 2014/15 to 2017/18

100

Figure 5. Functional Form and Winner-take-all Effect

5. Conclusions and implications

In this paper, we examine how Top sport superstar players compete in the global media showcase. We actually measure the comparative status in the media of some selected Top sportspersons and further compare their global rivalries. To accomplish the paper’s objectives, we have performed three types of analyses. First, we identified the Top-10 athletes, competing in any professional sport discipline, who enjoy the greatest levels of popularity. Once identified, we lined them up in a ranking based on relative intensity of Internet searches (as captured by the “Google Trends” tool). The results of this approach allow us concluding that the most popular athletes worldwide happened to be soccer players; while other sport disciplines (tennis, basketball and golf) also stand out. Regarding global rivalries, we focused on analyzing sport rivalries among the Top 3 players in each of the chosen sport disciplines: soccer, tennis and basketball. In absolute values, the superiority of soccer over the other sports manifests itself in the popularity of global rivalries’: the rivalry between Ronaldo vs. Messi is far ahead of the one immediately behind. Anyway, this finding was expected, given that the overall attention drawn by soccer is typically greater than any other sport, which in turn may influence the overall interest paid to the corresponding rivalries as well.

2340-7425 © 2019 The Authors. This is an open access article under the CC BY license 199 (http://creativecommons.org/licenses/by/3.0) García-del-Barrio, P., Becerra, N., & Schröder, J. (2019). Rivalries in sports competitions and in the global media showcase. Journal of Sports Economics & Management, 9(3), 185-201.

We performed also calculations of relative rivalries to explore how the popularity of selected pairs of players are linked to the overall popularity of certain sport disciplines. Among other results, we conclude that even if rivalries in tennis and basketball are not as prominent, in absolute terms, as the ones observed in soccer, there is also a high association degree between supporters’ attention and rivalries in these sports. Another analysis was developed to studying sport rivalries in the global media showcase. We first looked at the case of tennis, examining the empirical link between sport performances and the degree of interest generated by the main players. Secondly, we resort to the regression analysis in search of models’ estimations whose functional form were compatible with the hypothesized role of rivalries, even if the adopted empirical approach is actually unable to prove it. In this regard, the significance of the non-linear specification and/or of the effects of the dummy variables attached to winner-take-all elements, are consistent with the hypothesis that global sport rivalries may have a significant ability to call attention from the journalist, fans and the public. Specifically, we examined the ranking of the Top-10 soccer players worldwide. We used regression analysis techniques as the framework in which studying the degree of attention given by soccer followers. As expected, the global media showcase, during the last 8 years, was dominated by Cristiano Ronaldo and Lionel Messi. In this paper, we claim this feature to be closely linked to the existence of winner-take- all effects, stimulated by the long-lasting legendary rivalry found between these giant two stars.

6. References

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