The Cost of Segregation: Using Transfermarkt Values to Model Counterfactual Outcomes in Soccer
Using Transfermarkt valuations and counterfactual modeling, this study demonstrates that racially exclusive selection strategies would significantly reduce the England men's national soccer team's performance, highlighting that the primary benefit of diversity in elite sports stems from access to a larger talent pool rather than diversity itself driving productivity.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
In the world of professional sports, the goal is always the same: to assemble the best possible team to win. This requires finding the most skilled players available, regardless of where they come from or what they look like. Economists have long studied how groups perform together, wondering if mixing people from different backgrounds helps a team succeed or if it causes friction. In soccer, a sport where individual talent is often measured by how much a player is worth on the transfer market, this question takes on a sharper edge. The sport has a history of racial imbalance, where players of color are common on the field but rare in coaching and leadership roles. This raises a difficult question: if a team were forced to ignore race when picking its players, would it get better or worse? To answer this, researchers do not need to wait for history to unfold; they can use data to build a picture of what might have happened if the rules of selection were different.
A team of researchers set out to measure the cost of racial segregation in English soccer by looking at the national men's team. They used a method called counterfactual modeling, which is essentially a way of asking "what if" using hard numbers. Instead of guessing, they relied on Transfermarkt, a widely used website that assigns a monetary value to every professional soccer player based on their skill, age, and performance. These values act as a reliable proxy for how good a player is. The researchers gathered data on every match played by the England national team between 2016 and 2024. They first built a model to prove that these player values could accurately predict match results, comparing their predictions against the odds set by professional bookmakers. They found that the market values were just as good at forecasting wins and losses as the experts who set the betting lines.
Once they were confident their model worked, the researchers created two imaginary versions of the England team to see how they would have performed. In the first scenario, they removed every Black player from the squad and replaced them with the highest-valued non-Black English players available for that specific position, ensuring the replacements had the same preferred foot and were not injured. In the second scenario, they did the opposite, creating a team made up entirely of Black players and replacing any non-Black starters with the best available Black alternatives. These were not proposals for how the team should be run, but rather stress tests to see what happens when you limit the pool of talent based on race.
The results were clear and consistent. When the researchers simulated a team without Black players, the total value of the squad dropped by 22.9 percent, and the team's chance of winning a match fell by 2.7 percentage points. When they simulated a team made only of Black players, the squad value dropped even further, by 25.8 percent, with a corresponding 3.3 percentage point decrease in the probability of winning. The analysis showed that the loss of value was not spread evenly; it was concentrated in key positions, particularly in attack and goalkeeping, where the most highly valued players happened to be Black. The study found that the diversity of the team itself did not change the outcome once the actual skill level of the players was accounted for. Instead, the primary benefit of diversity was simply that it allowed the selectors to choose from a larger pool of talent. By excluding a significant portion of that pool based on race, the team inevitably became weaker.
The authors emphasize that these findings illustrate a fundamental economic principle: restricting access to the best available talent always comes with a cost. In a high-stakes environment like international soccer, where small differences in skill can determine whether a team wins a championship or goes home early, excluding players based on race is not just an issue of fairness. It is also a matter of efficiency. The study suggests that the underrepresentation of Black players in coaching and leadership roles in English soccer is a separate issue from the players themselves, but the data on the players makes it clear that the talent pool is deep and diverse. When the selection process is open to everyone, the team is stronger. When it is narrowed by artificial barriers, the team suffers, and the cost is measured in lost victories.
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