This is the first in a series of posts that The Monkey Cage will run on politics, political science and the World Cup. Some of our posts, including this one, will use soccer (or football) as a kind of laboratory to better understand competitive behavior. For example, one of the authors of this post, Sebastian Saiegh, has previously written on how exposure to civil war violence is correlated with more violent behavior on the soccer pitch. Other posts will use soccer as a lens for understanding culture and politics in an individual country. For example, we will read about a traveling soccer team that functioned as the national team for the Algerian independence movement and the difficulties and opportunities that immigration offers for fielding strong national soccer teams in Germany, France and elsewhere. Many of our authors have written extensively on these issues. Enjoy!
Questions regarding the costs and benefits of diversity for organizational performance affect debates over immigration, university admissions and business hiring decisions. While almost all interlocutors recognize the benefits of diverse talents, perspectives and experiences, there are legitimate questions about the costs that can arise when working groups must negotiate multiple language and cultural roadblocks.
Previous work on the subject has generated starkly different conclusions. In a recent paper, written in collaboration with Keith Ingersoll, we explore the question of diversity in a unique setting that allows us to address all of these problems. We examine how teams from the top five European soccer leagues (England, France, Germany, Italy and Spain) fared in the Union of European Football Associations (UEFA) Champions League tournament between 2003 and 2012 to study the effect of group diversity on performance.
The world of professional soccer provides an ideal testing ground that allows us to sidestep many of the aforementioned problems. First, soccer teams are engaged in the same pursuit — to score goals and win games. The benefits of a diverse talent pool will have the same theorized benefit for every team. This differs dramatically from business analyses that must compare widely diverse sectors where talent and creativity are employed very differently in the production cycle.
Second, the market for professional players provides a clear indication of the relative talent of individual players — their transfer price and salary. Wage is related directly to productivity and is not obscured by seniority or other non-market influences. This allows us to statistically separate the effect of talent from diversity.
Third and most importantly, the UEFA Champions League tournament setting addresses many of the empirical problems that have plagued other work. Only the best teams from each league play, meaning that wealth and prestige are essentially held constant.
Unlike teams in other professional sports, high-flying European soccer teams are truly global: players from almost 50 different nationalities play in them. In 1995, the “Bosman ruling” (which removed restrictions on internal migration of players within Europe) enabled European soccer teams to acquire talent from virtually every nation in the world. Therefore, managers can effectively affect their team’s performance by choosing players from a broader talent pool.
But even soccer teams that are composed of equally talented players may accrue additional benefits when their players differ in the way they interpret problems and use their skills to solve them. This variation likely stems from their exposure to different training methods and styles of play. Indeed, country of origin captures in soccer more attributes (e.g., nation-specific traits) about a player than just his nationality.
Styles of play (e.g. attacking versus counterattacking), defensive tactics (e.g. man-to-man, pure zone), strategies for set pieces (free kicks/corner kicks), and even the organization of players on the field differ remarkably across countries. The benefits of diversity notwithstanding, there are obviously costs associated with hiring players from multiple countries. For example, a multinational soccer team can lead to increasing communication errors on the pitch. In addition, players’ cultural and political differences may impose considerable integration costs on the team, both on and off the pitch.
In our paper, we employ “linguistic distance” as our core measure of team heterogeneity. Besides the obvious aspect of ease of communication, this measure captures the broader notion that some skills and knowledge sets are culture specific. The Automated Similarity Judgment Program (ASJP) calculates the similarity of languages (on scale of 0-100 using a set of commonly used words) and produces a single score for every pair of languages. Under the assumption that each player’s native language is the native language of his home country, we match the score generated by ASJP to every teammate pair combination on each team.
Because most soccer games are very low-scoring and close, focusing on winning percentage can be too blunt. Indeed, the difference between win, loss or draw may have been caused by one astounding play or minor error that is the soccer equivalent of a coin flip. Drawing precise statistical lessons from such data can thus be dangerous. To allow for more precision, we employ the goal differential (goals scored minus goals conceded) as our main indicator of team performance.
A bivariate correlation indicates that a strong and positive relationship between diversity and team performance exists. To ensure that our analysis is not at risk of omitted variable bias, we account for teams’ financial prowess (using players’ market value). It is not unusual for these elite teams to include a few very talented foreign players (maybe even just one or two). These players can drive up the total value of a team’s roster by themselves. Therefore, we divide the total value of a team by the number of players on its roster.
Figure 1 below shows the estimated relationship between performance (measured as goal differential) and team diversity, once the impact of players’ market value is accounted for. In our model, we also include league and team fixed effects. The years that each team played in the league are represented by the area of the circles. Label colors depict the league that a team plays in.
The results are clear and straightforward: There is a positive relationship between diversity and performance that is visible even among the very best teams in the world. Teams that eschew international talent to cultivate solely homegrown are likely to come up short on the world’s biggest stage. A structural equation model (SEM), where diversity and player quality (proxied by transfer values) are endogenized, reinforces these findings. Surprisingly, we find no evidence of diminishing returns to diversity. It almost always helps to enhance the pool of styles available on the field.
So what are some possible implications of our study for the impending World Cup in Brazil? Obviously, all national teams possess very little linguistic/cultural diversity, because they are composed of their country’s citizens. FIFA rules allow naturalized foreign nationals to play for their adopted nations; but these players usually have strong linguistic/cultural ties to the latter countries (for example, these are players who were born in a foreign country, but were raised in their adopted one).
It is possible, though, that players who compete in national leagues with more culturally diverse teams may benefit from diversity’s spillover effects. If this is the case, then the German national team may have an edge in the competition, as their national league, the Bundesliga, is currently soccer’s most diverse. Another option is that national teams composed of players currently situated in diverse leagues around the world may also get the same benefit of diversity, as their core players are introduced to strategies and styles from around the globe.
Brazil and Argentina are the most well-known beneficiaries of this arrangement, with national team starters in all of the top five world leagues. Other teams to watch, if we are right, are Belgium and France, which also will start a number of players with diverse international experience.
Edmund J Malesky is an Associate Professor in the Political Science Department at Duke University. Sebastian M. Saiegh is an Associate Professor in the Political Science Department at the University of California, San Diego.