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POV: Can Economics Predict This Year’s World Cup Winner?

Maybe yes, and maybe no

2

With the 2018 World Cup under way, fans are gripped by football fever. Questions abound. Will Russia be able to organize a successful tournament? How will the teams handle the long distance between venues? Will the World Cup be the same without Italy and the Netherlands? Without the USA? And most important of all, who will raise the trophy on July 15?

It seems that everybody is in the business of making World Cup predictions: psychic cephalopods and mathematicians, investment bankers and firms using artificial intelligence. And of course pundits. And more pundits.

Today, it is not enough to simply name an expected winner. You want a probabilistic forecast that assigns to each team a probability of winning the whole thing. Many of the predictions described above are based on a simple structure: assign to each team a rating, based on some combination of historical results, quality of the players on the squad, quality of the club teams represented on the squad, and maybe other factors (home field advantage, home continent advantage, age of the players, distance traveled, or other personal hunches); use a mathematical formula to transform the ratings into a probability that a match ends with a given outcome (1-0, 2-1, 7-1, …); and then simulate these matches many times to obtain predicted probabilities of the final tournament outcomes.

But what if we didn’t know anything about international football? What if we didn’t know about Messi and Ronaldo, that Neymar is coming off an injury, that Spain sacked its coach on the eve of its World Cup debut, that an England goalkeeper will find a way to embarrass himself, or that football is a game with 22 players and in the end Germany wins? Could we still make an accurate World Cup prediction? What if we tried to apply economic theory to predict the World Cup winner?

Welcome to the economic model for predicting the World Cup. The model is extremely simple. It is based on the observation that a country’s soccer prowess can be predicted by just a few variables: population, GDP per capita, and the FIFA confederation to which a country is affiliated. The logic is quite straightforward. The larger a country’s population, the deeper its talent pool. Higher GDP per capita means better facilities, infrastructure, health, and the ability to pay good coaches (contrary to popular belief, the best soccer players didn’t hone their skills by playing with a ball of rags on the street, with jumpers for goalposts; they played in organized leagues, with goals, uniforms, referees, and shouting parents on the sidelines). Including a country’s confederation in the model is a simple way to capture the fact that passion for soccer is not the same everywhere. One could add other variables (a country’s age distribution, measures of health, investment in sports as a share of GDP), but it is instructive to see how far this simple model can go.

Below is a figure showing the economic model’s prediction for the group stage. For comparison, the figure also shows the probabilities based on a more traditional rating system that takes only historical results into account.

Bar chart showing the probability of teams A-D qualifying to the second round of the 2018 World Cup.

Bar chart showing the probability of teams E-H qualifying to the second round of the 2018 World Cup.

Source: Daniele Paserman

For many countries, the economic model’s predictions and the traditional predictions are remarkably similar. The economic model recognizes Germany’s economic might and Brazil’s large population and rates them as strong favorites to advance from their group. But there are also some interesting discrepancies. Russia, Egypt, and Nigeria are expected to do quite well, based on their economic fundamentals. On the other hand, the economic model doesn’t think much of tiny Uruguay and Iceland (given the effects of the financial crisis on the Icelandic economy, the feeling is probably mutual).

And what about the original question: who will win the World Cup? Looking just at the teams with more than a 2 percent probability of winning, we get the following:

Bar chart based on statistic model showing the probability of teams winning the 2018 World Cup.

Source: Daniele Paserman

According to economics, the favorites to win the World Cup are Russia, closely followed by Brazil. Hmm… Given the dismal state of the Russian national team, maybe economics is not that much better at predicting sporting events than the state of the world economy? (Or maybe economics knows something that we don’t?)

There is only one way to find out. Watch the games and enjoy.

M. Daniele Paserman is a College of Arts & Sciences professor of economics. The chance of his favorite team, Italy, winning the World Cup is exactly 0.0 percent. He can be reached at paserman@bu.edu.

“POV” is an opinion page that provides timely commentaries from students, faculty, and staff on a variety of issues: on-campus, local, state, national, or international. Anyone interested in submitting a piece, which should be about 700 words long, should contact Rich Barlow at barlowr@bu.edu. BU Today reserves the right to reject or edit submissions. The views expressed are solely those of the author and are not intended to represent the views of Boston University.

2 Comments

2 Comments on POV: Can Economics Predict This Year’s World Cup Winner?

  • MoD On The Beat on 06.19.2018 at 5:43 am

    Great scoop homeboy. Dunno if u considered any additional macro indicators to improve the predicting power of ur model; would probably make the model less simple and perhaps less elegant but it’s just a thought.

  • Yubo Dong on 06.19.2018 at 7:19 pm

    As a Chinese student, I really wish this model is true. China has the largest population and second GDP in the world. If the model is a direct predictor for soccer level, China would have one of the best soccer teams.

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