Volume 43, Issue 2 pp. 260-270
ORIGINAL ARTICLE
Open Access

Cristiano of Arabia: Did Ronaldo increase Saudi Pro League attendances?

Dominik Schreyer

Dominik Schreyer

Center for Sports and Management, WHU – Otto Beisheim School of Management, Düsseldorf, Germany

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Carl Singleton

Corresponding Author

Carl Singleton

Economics Division, Stirling Management School, University of Stirling, Stirling, UK

Correspondence

Carl Singleton.

Email: [email protected]

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First published: 14 August 2024

Abstract

In December 2022, Cristiano Ronaldo, five-time Ballon d’Or winner and the most-followed person on Instagram, signed for Al-Nassr in the Kingdom of Saudi Arabia. This marked one of several expensive, recent interventions by the kingdom in global sports markets. We exploit the timing of this event to estimate superstar effects. Ronaldo alone increased stadium attendance demand, even before the influx of further stars in the summer of 2023. On average, Ronaldo filled an additional 20% of the seats in his home team's stadium when he played, 15% in the stadiums he visited, and 3% where he did not even play.

Abbreviations

  • FA
  • English Football Association
  • FC
  • football club
  • FIFA
  • Fédération Internationale de Football Association
  • KSA
  • Kingdom of Saudi Arabia
  • MLS
  • Major League Soccer
  • NBA
  • National Basketball Association
  • PIF
  • Public Investment Fund
  • SPL
  • Saudi Pro League
  • 1 INTRODUCTION

    On December 30, 2022, only a few days after the conclusion of the Fédération Internationale de Football Association (FIFA) World Cup in Qatar, news broke that the Saudi football club (FC) Al-Nassr had signed Portugal's captain and five-time Ballon d’Or winner Cristiano Ronaldo (Reuters, 2022). Signing one of the greatest male football players of all time (FourFourTwo, 2022), and the most followed person on Instagram, marked a pivotal moment for the Saudi Pro League (SPL). Ronaldo's arrival aligns with other ground-shaking moves made by Saudi Arabia in other major sports markets, such as golf (CNBC, 2023a), motor racing (Sky Sports, 2023), and combat sports (AP News, 2023). This activity has been coined as “sportswashing” in the mainstream media (e.g., The Guardian, 2023) and is now being studied as a concept in the social science of sport (e.g., Davis et al., 2023; Fruh et al., 2023; Skey, 2023).

    In the case of football, the SPL executives' evident strategy reflects many past and present attempts elsewhere to exploit superstar externalities, both domestically and internationally, in growing and emerging leagues. In particular, growing domestic interest in the people's game and stadium attendance demand, through such a strategic investment in foreign talent, might help the Kingdom of Saudi Arabia (KSA) persuade FIFA that the country is prepared to host a World Cup, which certainly needs some public support in and out of the stands. In fact, KSA was the only nation to submit a bid for the 2034 FIFA World Cup before October 31, 2023, a mere 10 months after Ronaldo was signed by Al-Nassr, which was one of four Saudi Arabian football clubs taken over by the country's Public Investment Fund (PIF; BBC Sport, 2023). In the meantime, it has been confirmed that Saudi Arabia is set to host the 2034 FIFA World Cup.

    Taking a broader policy perspective, attracting Ronaldo may have laid the groundwork for subsequent player moves, which could elevate the SPL's future competitiveness, not least by motivating local talent in the stands to pursue a football career. The Ronaldo signing, and subsequent player moves, could attract international tourists and foreign investments to the country, help market the TV product abroad, and legitimize KSA's other foreign sports investments, including the 2021 takeover of Newcastle United FC (e.g., BBC, 2021). This latterly may not otherwise have led to sustained enthusiasm among the Kingdom's population, given the evident trade-offs (e.g., reduced public spending on education, healthcare, infrastructure, social services, or even the grassroots of domestic sport activity).

    Assessing the merits of the general Saudi strategy prompts us to ask specifically whether domestic stadium attendance demand increased once Ronaldo joined Al-Nassr and the SPL (e.g., see evidence from Major League Soccer [MLS], largely to this effect, in Jewell (2017); Rewilak (2023); Shapiro et al. (2017)). Intriguingly, the public discussion has so far focused mostly on whether and how the Saudi move has changed the global perception of the SPL, including its social media following (e.g., Axios, 2023), as well as the impacts on the global price of football talent (e.g., The Athletic, 2023).

    Superstar externalities in sports, such as effects on league-wide stadium attendance demand (e.g., Humphreys & Johnson, 2020; Kaplan, 2022) or other sources of revenue and value added, are theoretically likely to emerge from an individual's special talent (Rosen, 1981), their popularity (Adler, 1985), or a combination of both. There is evidence that individual footballers have generated significant superstar effects in well-established markets. For instance, van Ours (2022) showed that Johan Cruyff, the greatest ever Dutch footballer and three-time Ballon d’Or winner, helped attract visitors to Feyenoord's home matches in the Dutch Eredivisie, after he moved there for his final professional season from arch-rivals AFC Ajax (a move which was unpopular with partisan fans of both clubs). Similar effects have been found in MLS (e.g., Scarfe et al., 2021), where marquee players, including David Beckham (e.g., Lawson et al., 2008), generated increased demand both at home and even more consistently on the road (Jewell, 2017). DeSchriver (2007) also found significantly stronger demand for MLS stadiums when they were visited by the Ghanaian-born American professional soccer player and wonderkid Fredua Koranteng (Freddy) Adu, who debuted at the age of 14 and was once touted as the next Pelé (ESPN, 2011). Going beyond stadium attendance demand, there is evidence that the presence of superstar players significantly affects TV demand for the elite European football competitions (Bond & Addesa, 2019; Wills et al., 2022).

    Although football is the world's most popular and commercially valuable sport, it is not unique in providing a testbed for superstar economics. For instance, arguably the most infamous evidence on superstar effects and externalities was generated by Michael Jordan's substantial influence within the National Basketball Association (NBA; e.g., Hausman & Leonard, 1997). In contrast with North America and Europe, the determinants of stadium attendance demand in the Middle East are hardly understood (cf., Schreyer & Ansari, 2022), including whether domestic fans value the appearance of a global superstar such as Ronaldo.

    In this article, therefore, we consider the early signs on whether Ronaldo has affected stadium attendance demand in Saudi Arabia, prior to the later arrival of other superstars in the summer of 2023, who could end up saturating the League with stardust (e.g., Rewilak & Watanabe, 2022). In what follows, we first describe our dataset and the context of Cristiano of (in Saudi) Arabia. Second, we present our empirical strategy and stadium attendance model estimates. Third, we discuss our findings, their potential limitations, and some future research avenues.

    2 DATA SET

    Like many European football leagues, a season of the SPL, the highest tier of association football in the Saudi system, runs between August and May. It features promotion and relegation, and it is currently operating on a round-robin system, meaning that each of the clubs plays each of the others twice, once home and away. As such, our sample contains 240 matches played by 16 different clubs during the 2022–2023 season, three of which were just promoted: Al-Adalah, Al-Khaleej and Al-Wehda. Ronaldo debuted in the SPL on January 22, having been delayed after joining his new team by a two-match ban, issued by the English FA at the end of his time with Manchester United FC. He subsequently appeared in 16 SPL matches, seven at home, and nine on the road, only missing his team's final match of the season reportedly due to a muscle strain.

    In Table 1, we present summary statistics from our dataset, including the sources of the variables. In line with most previous research (cf., Schreyer & Ansari, 2022), we proxy domestic stadium attendance demand by exploiting the publicly available information on the number of distributed tickets across home and away supporters, neither differentiating between matchday and season ticket holders, nor addressing any no-show behavior (as this information is not publicly available as far as we are aware). On average, the clubs distributed 9330 tickets per match during the 2022–2023 SPL season, with a minimum reported attendance of 284 (Al-Wehda 0–1 Al-Fayha) and a maximum of 59,892 (Al-Ittihad 2–0 Al-Tai), both in the final round of fixtures. The mean utilization of stadium capacity during the season was 37% across all matches, with a minimum of 1% and a maximum of 99%. Table 1 also demonstrates some of the variance across matches in the numbers of foreign players appearing and the estimated transfer market values of the teams. In terms of the latter, the maximum was observed for Al-Nassr when Ronaldo was playing. Importantly, there was only limited activity in the SPL transfer window of the 2022–2023 season apart from Ronaldo. We do not have comprehensive price data for SPL matches, though Ronaldo's arrival midway through the season may suggest that pricing was largely unaffected. Table 1 also shows that the SPL had a fairly typical degree of expected home advantage for a football competition according to historical odds from OddsPortal.com, and that matches were dispersed over days of the week.

    TABLE 1. Descriptive statistics for all 240 matches.
    Mean/share St. dev. Min. Med. Max.
    Attendance 9330 10,492 284 5663 59,892
    Stadium capacity 26,018 13,059 3646 25,000 68,752
    Percentage of capacity 37 27 1 35 99
    N. of home team foreign players 6 1 1 7 8
    N. of away team foreign players 6 1 1 7 8
    Transfermarkt value of home team (€millions) 16.02 13.91 0.95 9.24 72.63
    Transfermarkt value of away team (€millions) 15.83 14.11 0.98 9.14 72.95
    Transfermarkt value of both teams (€millions) 31.85 19.35 7.51 28.58 102.16
    Home win probability, odds implied 0.424 0.205 0.022 0.407 0.899
    Monday match 0.103
    Tuesday match 0.096
    Wednesday match 0.079
    Thursday match 0.204
    Friday match 0.229
    Saturday match 0.200
    Sunday match 0.088
    • Note: Author calculations. We collected attendance data and stadium capacities from ESPN and crosschecked them with information from Weltfussball.de and, in a few cases, also Wikipedia in early August 2023. We also used these sources to extract match dates, timings, locations, and scorelines. Further, we collected the number of foreign players appearing in a match on each team, either starting or on the bench, and the cumulative transfer market value of those players from Transfermarkt.de.

    In Figure 1, we show the development of average stadium attendance demand over the eight matches within each of the 30 rounds of fixtures in the season 2022–2023, expressed both in terms of the number of seats filled and capacity utilization. The vertical dashed lines indicate when Ronaldo's move was first rumored (e.g., The Guardian, 2022), when it was officially announced two rounds later, and when he started playing in round 14. He then started matches in every round, except for the final round, which he missed due to injury. Although these statistics are noisy from one round to the next, due to the generally alternating nature of teams playing home and away, there is still a clear indication that average attendance demand in the SPL increased, particularly after Ronaldo started playing.

    Details are in the caption following the image

    Mean attendance and percentage of stadium capacity filled by round of matches. Author calculations using data collected from ESPN, Weltfussball.de, and Wikipedia.

    In Figure 2, we also document Google Trends within the Kingdom of Saudi Arabia (KSA) for three relevant search terms Ronaldo, SPL, and Al-Nassr FC, for the whole duration of the season 2022–2023. There appears to have been some additional interest in Al-Nassr FC and the SPL after the first rumors about Ronaldo's move and further details dripped out in the media during the World Cup, followed by an explosion of interest in the player, his new team, and the league when the signing was officially announced at the end of December. Interest in Al-Nassr FC then peaked when Ronaldo started playing. Relatively increased search volumes for all three terms were generally sustained over the second half of the season, before clearly waning after it ended.

    Details are in the caption following the image

    Google Trends in Saudi Arabia (relative search volumes). Author calculations using data extracted from Google Trends for the exact search terms, retrieved August 17, 2023 for the period covering the weeks shown, that is, before the 2023 summer transfer window.

    To further put Ronaldo's arrival on the Arabian Peninsula in perspective, in Figure 3, we plot the minimum, median and maximum home percentage of capacity used for each team in the season 2022–2023, at the stadium where they played most of their matches. Since he joined halfway through the season, Ronaldo only visited 8 teams, starting each match. The teams generally experienced a big attendance range within their home stadiums during the season, such as Al-Ittihad, who both filled their stadium in one round but experienced it two-thirds empty in another. We have also indicated with crosses in Figure 3 the percentages of stadium capacity filled when Ronaldo visited. In all but one case, these matches had either the maximum attendance for the team during the season or were very close to having so. The exception was Al-Nassr's visit to Al-Hilal, which is the most successful team in Asian club football, based on continental cup wins, and plays in the biggest stadium. This was also a midweek game, which could explain Ronaldo not drawing in a crowd much larger than the median home attendance for Al-Hilal.

    Details are in the caption following the image

    Percentage of stadium capacity filled by home stadium in SPL matches (2022–2023). Author calculations using data collected from ESPN, Weltfussball.de, and Wikipedia. 12 teams played all 15 of their home matches in a single stadium. For the others, only the stadiums they played in most of the time are considered: Al-Hilal (14 matches), Al-Khaleej (14 matches), Al-Tai (14 matches), Damac football club (FC) (12 matches). Ronaldo played and started in 8 consecutive away fixtures for Al-Nassr after joining the SPL but missed the final match of the season when Al-Nassr visited Al-Fateh. SPL, Saudi Pro League.

    There is fairly clear descriptive evidence from the patterns in Figures 1-3 that Ronaldo likely increased the interest and attendance demand in the SPL, especially once he started playing. In the next section, we more formally estimate the potentially different average effects that Ronaldo had on stadium attendance demand at Al-Nassr when he played, at other stadiums when he visited, and on the league in general.

    3 ESTIMATION AND RESULTS

    We estimate the following log-linear model for stadium attendance demand (e.g., Reade & Singleton, 2021; Scelles et al., 2013):
    y i j m = θ + β 1 C R 7 H o m e m + β 2 C R 7 A w a y m + β 3 P o s t C R 7 m + h i + a j + ε i j m , ${y}_{ijm}=\theta +{\beta }_{1}{CR7Home}_{m}+{\beta }_{2}{CR7Away}_{m}+{\beta }_{3}{PostCR7}_{m}+{h}_{i}+{a}_{j}+{\varepsilon }_{ijm},$ (1)
    where yijm is either the log attendance or percentage of stadium capacity filled, in match m, between home team i and away team j. CR7Homem and CR7Awaym are dummy variables indicating whether Ronaldo appeared at home or away in the match. PostCR7m is a dummy variable indicating the after-Ronaldo portion of the SPL season. We will consider three different versions of this variable when estimating the model, corresponding to the post-rumor, post-arrival, and post-playing periods (see Figure 1). hi and aj are fixed effects for the home and away teams, addressing the fact that some teams generate greater regular attendance demand than others and the unbalanced nature of the fixtures in SPL either side of the Ronaldo factors. We consider two variants of hi, the first as an effect for each home team, and the second for each home-stadium pair, given that some teams played their home matches at multiple stadiums, where we prefer the more robust second variant. β3 measures any general effect of Ronaldo being associated with the SPL, though we cannot rule out that other coincident factors could have increased demand, such as increased advertising and other investments made by the teams and the League. β1 and β2 measure any additional effects of Ronaldo appearing in a match on stadium attendance demand, home and away. θ is a constant and the remaining heterogeneity is in εijm. We considered several other controls in the model, for scheduling effects (e.g., the day of the week, weekend fixtures, time of the day), value of the players appearing in the starting lineups, the home win probability according to bookmakers, and the numbers of foreign players, but they are statistically insignificant, and our findings are robust to their inclusion. For log attendance, we estimate Equation (1) using linear least squares. For the percentage of stadium capacity filled, we use tobit regression, censoring at 0% and 100%. Our preferred results will be from the latter set of models, given both the large variance in attendance within each stadium during the season (see, again, Figure 3) and the potential for β1, β2, and β3 to be large. We estimate heteroskedasticity-robust standard errors for the coefficients, and we use the delta method to generate average partial effects on the censored percentage of stadium capacity filled.

    In Table 2, we show our estimation results for the linear model of log attendance. Across all specifications, we find no evidence that on average, the post-Ronaldo period was associated with higher attendances. Further, although the estimated values of β2 are large and positive, there is no significant evidence that Ronaldo visiting tended to increase attendances within a given stadium. However, the estimates suggest that Ronaldo increased attendances when Al-Nassr were playing at home by 0.44–0.52 log points (55%–68%), including when we control for an insignificant quadratic trend over the matchdays (rounds of fixtures) of the SPL season (column (III), Table 2), to address the potential for general trends in SPL attendance that may have coincided with Ronaldo's arrival. In column (VII) of Table 2, we also show estimates of a specification that includes control variables for day of the week fixed effects, the home win probability according to bookmaker odds, and the total valuation of the starting lineups according to Transfermarkt.de. As mentioned earlier, we find that these set of control variables, and others we also considered including in the models, are statistically insignificant and only marginally add to the overall predictive power of the models. The home-stadium and away team fixed effects do a lot of the work in predicting SPL match attendance, and so we prefer not to over-fit the models and thus exclude these statistically insignificant sets of control variables when carrying out inference on the Ronaldo effects.

    TABLE 2. Linear regression estimates for log attendance in SPL matches (2022–2023).
    (I) (II) (III) (IV) (V) (VI) (VII)
    CR7 home (β1) 0.436** 0.457** 0.514*** 0.504** 0.520** 0.435** 0.528**
    (0.192) (0.192) (0.195) (0.195) (0.201) (0.204) (0.248)
    CR7 away (β2) 0.165 0.165 0.253 0.251 0.271 0.175 0.358
    (0.424) (0.424) (0.462) (0.451) (0.455) (0.462) (0.507)
    Matchday (round of SPL) −0.015
    (0.021)
    Matchday squared (×100) 0.039
    (0.067)
    Post CR7—rumor (β3) −0.074
    (0.087)
    Post CR7—arrival (β3) −0.081
    (0.084)
    Post CR7—playing (β3) 0.024
    (0.084)
    Win probability (1 ppt) 0.003
    (0.008)
    Players value (€millions) −0.009
    (0.010)
    Tuesday −0.102
    (0.170)
    Wednesday −0.233
    (0.208)
    Thursday −0.004
    (0.140)
    Friday −0.063
    (0.126)
    Saturday −0.051
    (0.134)
    Sunday −0.113
    (0.174)
    Constant 8.594*** 8.593*** 8.701*** 8.642*** 8.640*** 8.581*** 8.821***
    (0.044) (0.043) (0.130) (0.071) (0.064) (0.061) (0.478)
    Home team FEs Yes No No No No No No
    Home-stadium FEs No Yes Yes Yes Yes Yes Yes
    Away team FEs Yes Yes Yes Yes Yes Yes Yes
    R2 (unadjusted) 0.722 0.728 0.729 0.729 0.729 0.728 0.732
    N. of matches 240 237 237 237 237 237 237
    • Note: Least squares estimates of Equation (1). Columns (II)–(VII) drop singleton home-stadium matches from the estimation sample. ***, **, * indicate significance from zero at 1%, 5%, and 10% levels, respectively, two-sided tests. Robust standard errors in parentheses.
    • Abbreviations: FEs, Fixed Effects; SPL, Saudi Pro League.

    In Table 3, we show our preferred estimation results for the censored models of percentage of stadium capacity filled. Column (I) shows results from a model with home-team fixed effects and no Post-CR7 dummy variables, giving average partial effects of Ronaldo playing at home of 19% points of capacity, but no significant effect of him playing away. Column (II) uses instead home-stadium fixed effects, addressing the possibility that teams may have switched to a bigger stadium because they knew Ronaldo was coming to play. In this case, the estimated average effect of Ronaldo playing at home is 20% points of capacity, and the average effect of him playing away is 15% points, significantly different from zero at the 10% level (two-sided test). This is robust to adding a quadratic in the matchday (round of fixtures) into the model in column (III). These findings are qualitatively unchanged in columns (IV) and (V), when we respectively add the indicator variables for post-rumor and post-arrival to the model, both of which are insignificant. Column (VI) suggests that the post-Ronaldo-playing period of the season 2022–2023 was associated with generally higher attendance demand across all matches, by 3% points of stadium capacity, significantly different from zero at the 10% level (two-sided test), with a further significant 17% point effect when he played at Al-Nassr's home. Taken together, these two effects combine to recover approximately the average marginal effect of Ronaldo on Al-Nassr home attendances in column (II). In column (VI), conditional on the league-wide Ronaldo effect, the additional average partial effect from Ronaldo appearing at an away stadium in this period was 12 log points, but we cannot reject a null hypothesis of no effect. The final column (VII) of Table 3 shows that the main results are robust to including control variables for day of the week fixed effects, the home win probability according to bookmaker odds, and the total valuation of the starting lineups according to Transfermarkt.de.

    TABLE 3. Censored regression estimates for percentage of stadium capacity filled [0, 100].
    (I) (II) (III) (IV) (V) (VI) (VII)
    CR7 home (β1) 20.149*** 20.702*** 20.489*** 20.545*** 20.424*** 18.082** 22.564**
    (6.771) (6.771) (7.132) (6.960) (7.012) (7.064) (7.309)
    CR7 away (β2) 9.744 14.996* 14.363* 14.825* 14.681* 11.941 15.666*
    (8.132) (7.930) 8.153 (7.986) (8.141) (8.129) (8.737)
    Matchday (round of SPL) 0.062
    (0.098)
    Matchday squared 0.010
    (0.013)
    Post CR7—rumor (β3) 0.249
    (1.786)
    Post CR7—arrival (β3) 0.354
    (1.736)
    Post CR7—playing (β3) 2.884*
    (1.688)
    Constant 11.050** 12.059*** 11.272** 11.882** 11.829** 10.384** 14.785*
    (4.826) (4.590) (4.661) (4.788) (4.785) (4.744) (8.338)
    Home team FEs Yes No No No No No No
    Home-stadium FEs No Yes Yes Yes Yes Yes Yes
    Away team FEs Yes Yes Yes Yes Yes Yes Yes
    Extra controls No No No No No No Yes
    Pseudo R2 0.132 0.165 0.165 0.165 0.165 0.166 0.166
    N. of matches 240 237 237 237 237 237 237
    Marginal effects:
    CR7 home 19.433*** 20.084*** 19.869*** 19.925*** 19.803*** 17.441** 21.463***
    (6.657) (6.785) (7.022) (6.859) (6.915) (6.943) (6.916)
    CR7 away 9.471 14.551* 13.918* 14.381* 14.239* 11.523 14.977*
    (8.032) (7.887) (8.099) (7.942) (8.096) (8.051) (8.533)
    Post CR7 … 0.231 0.328 2.670*
    (1.653) (1.606) (1.559)
    • Note: Maximum likelihood estimates of Equation (1) using censored tobit regression. Columns (II)–(VII) drop singleton home-stadium matches from the estimation sample. ***, **, * indicate significance from zero at 1%, 5% and 10% levels, respectively, two-sided tests. Robust standard errors for coefficients in parentheses. Expected marginal effects, E[dy*/dx | y ϵ (0, 100)], and their standard errors in parentheses, are estimated using the delta method. “Ronaldo played at home” average marginal effects are estimated at “Ronaldo played away” equal to zero and the home (stadium) team fixed effect at Al-Nassr (KSU Stadium). “Ronaldo played away” average marginal effects estimated at “Ronaldo played home” equal to zero and the away team fixed effect at Al-Nassr. “Extra Controls” refers to the additional control variables shown in column (VII) of Table 2, and the marginal effects here in column (VII) are then evaluated at the sample means for these variables.
    • Abbreviation: FEs, Fixed Effects.

    4 CONCLUSION

    Since Cristiano Ronaldo's move to KSA, the media and public's attention has almost entirely been drawn to the potential externalities abroad (e.g., international audiences' perception of the country and the SPL's relative quality and market power). In this short article, we focus on whether externalities occurred within the Kingdom, specifically whether stadium attendance demand increased in the second half of the season 2022–2023. Mirroring the results from previous research (e.g., Humphreys & Johnson, 2020; Jewell, 2017; Lawson et al., 2008), we find a considerable superstar effect, mainly for the signing club's home matches featuring Ronaldo. This shows that, for both emerging sports clubs and their leagues, attracting extraordinary talent, even past its peak, can be an effective way of growing the domestic market, at least temporarily. It is not surprising then that this strategy has been employed—and currently is—in all parts of the world, including the United States.

    While our results corroborate previous conclusions on superstar externalities, but in an as yet mostly ignored part of the world, providing initial evidence that an emerging (sports) market can rely on foreign talent to grow domestically, naturally, there are some notable limitations and caveats. We hope all of these can be addressed in future research. For instance, due to the relatively small sample size of matches in our study, we cannot robustly address whether the Ronaldo effects wane over time as the role any novelty factor wears off (e.g., Shapiro et al., 2017). Similarly, given the relatively modest sporting success associated with the player's move (Al-Nassr were leading the SPL when Ronaldo arrived, but finished the 2022–2023 season in second place), future research might center around a more nuanced differentiation of the mechanisms at play, distinguishing between exceptional talent (Rosen, 1981) and popularity (Adler, 1985)—see Scarfe et al. (2021) for such an attempt regarding MLS production. Given the influx of talent to the SPL in the summer of 2023, a natural follow-up question is whether the League's perceived increase in attractiveness around the globe emerges from the abundance of (super) stars or any consequential increase in the quality of football. Alternatively, future research might want to: (1) explore potential saturation effects from (too many) stars overshadowing (domestic) talent (e.g., see Jedelhauser et al. (2022) on the German Bundesliga); (2) differentiate between variations in the demand of different spectator groups (e.g., Allan and Roy (2008) on the Scottish Premier League); (3) add more control variables to the stadium attendance model (e.g., ticket price data); (4) test whether extreme salary inequality within the SPL and its clubs affects the production of football performances (e.g., Coates et al., 2016; Di Domizio et al., 2022; Franck & Nüesch, 2011; Levine, 1991); and (5) further test for extreme superstar effects in other markets, most obviously by exploring whether Lionel Messi's arrival in MLS attracted at least as big crowds to North American stadiums as his predecessors who moved across the Atlantic, including David Beckham (e.g., Jewell, 2017), and Ronaldo in KSA.

    ACKNOWLEDGMENTS

    Our research did not receive any specific funding from agencies in the public, commercial, or not-for-profit sectors.

      CONFLICT OF INTEREST STATEMENT

      The authors declare no conflicts of interest.

      ENDNOTES

      • 1 A salient example of Ronaldo's global superstardom came in 2019 during his then Italian club's (Juventus FC) pre-season tour of South Korea. Ronaldo was left on the bench for the duration of a match, leading courts to order the local organizer to compensate fans, not only for the cost of the ticket but also for “mental anguish” (BBC Sport, 2020).
      • 2 As of August 20, 2023, Ronaldo was the most followed person on Instagram with 601.41 million followers, 24% more than the next highest-followed person, Lionel Messi. After these two footballers, the next highest-followed sportsperson is the Indian cricketer Virat Kohli, with 256.84 million followers, and the next highest-followed footballer is Neymar, who has also just transferred to the SPL in August 2023 with 212.78 million followers.
      • 3 See also i Newspaper (2023), for a recent account of how Saudi Arabia is growing its sportswashing empire.
      • 4 For instance, David Beckham in 2007, Thierry Henry in 2010, Kaka in 2014, Frank Lampard and Steven Gerrard both in 2015, Wayne Rooney in 2018, and Lionel Messi in 2023, all moving to North American Major League Soccer (MLS); Brazilian internationals Ramires and Oscar to the Chinese Super League (CSL) in 2016–2017; Alessandro Del Piero moving to the Australian A-League in 2012; Alessandro Del Piero, Robert Pires and David Trezeguet to the Indian Super League in 2014; and Andres Iniesta to the Japanese J1 League in 2018 before playing in the United Arab Emirates in 2023. All these players have won the highest honors in football before making these moves, such as World Cups, European Championships, and the Champions League, and in their prime were regarded as the stars and cult heroes of the domestic leagues in Europe. Somewhat similarly, though significantly earlier, Pelé (in 1975) and Franz Beckenbauer (in 1977 and 1983) both moved to New York Cosmos, helping to grow “soccer” in the United States (cf., ESPN, 2022).
      • 5 After Ronaldo's inaugural season, superstars such as Benzema (Al-Ittihad), Neymar (Al-Hilal), Fabinho (Al-Ittihad), Riyad Mahrez (Al-Ahli), and Sadio Mané (Al-Nassr), all transferred to the SPL, among (many) others.
      • 6 According to the authors' conversations with a Saudi football official, after Ronaldo's signing “more than 125 countries secured the rights to broadcast the SPL (36).”
      • 7 From the beginning of the season 2023–2024, 18 teams will compete in the SPL, raising the number of matches played to 306.
      • 8 According to Transfermarkt.de, the next highest value player transferred in this period was Matheus Pereira (€7 million), leaving the SPL. Ronaldo's own Transfermarkt.de value at this time was €15 million, despite his age of 37 and recent evidence at his previous club of performances declining sharply (Forbes, 2022).
      • 9 Although there has been recent evidence of price-gouging (by as much as 1700%) in MLS to attend matches where Lionel Messi is expected to play (CNBC, 2023b), we found that season ticket prices, to attend all of Al Nassr's home matches, are currently starting at around a seemingly reasonable SAR685 or €170 for a Category Five seat (behind the goal; cf., Time Out Riyadh, 2023).
      • 10 In practice, the second case leads to the estimation of sixteen home-stadium fixed effects instead of 15 home team effects, and an estimation sample reduced to 237 matches as singletons are dropped, that is, where home teams played at a particular stadium only once during the season (see notes to Figure 3). In fact, the estimation sample only then has one team playing at multiple stadiums, Darmac FC, who played three matches at a much smaller stadium (3646 capacity, instead of 20,000). Al-Nassr and Ronaldo played away against Darmac FC in February 2023 at their regular larger stadium, and Al-Nassr played all their home matches at the same stadium. Thus, we would anticipate the slightly more robust and preferred home-stadium fixed effects specification to have almost quantitatively identical estimates to the home team fixed effects specification, which is what we find in practice (see columns (I) and (II) of Tables 2 and 3).

      DATA AVAILABILITY STATEMENT

      The data that support the findings of this study are openly available in OPENIPCSR at https://doi.org/10.3886/E207743V1, Schreyer and Singleton (2024).

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