Haas Newsroom


Researchers Can Now Predict the Outcome of the Olympic Games


August 13, 2004


Berkeley – Long before the 2004 Olympics even began, researchers Meghan Busse of Berkeley and Andrew Bernard of Dartmouth already knew who will win this year’s games and how many medals participating countries will take home.


Busse, a visiting assistant professor of economics at the University of California’s Haas School of Business, and Andrew Bernard, professor of international economics at Dartmouth University’s Tuck School of Business, use a combination of economics, statistics, and history to forecast overall medal totals and gold medal totals by country.


The winner will once again be the United States, with 93 medals overall and 37 gold medals, write the authors. However, the Olympic riches will be more widely distributed than ever before as the number of medals going to the top countries declines.


In an article recently published in the Review of Economics and Statistics, the authors describe the details of their medal prediction method. They show that over the last 40 years, national Olympic medal totals have been driven by four distinct factors: population, per capita income, past performance, and a host effect.


Countries such as the US and Germany win large numbers of medals because they have both large populations and high per capita income (Gross Domestic Product per capita). The researchers explain that population matters because it gives a country more chances to have an athlete with the extraordinary natural ability that is necessary to become an Olympic champion.


Past performance is another powerful, yet not perfect, predictor of Olympic success. Countries with above average performances in Sydney are likely to continue to take home medals in the Athens games.


“This bodes well for Australia, China, Russia, and the United Kingdom,” the authors say, “all of whom did well in the Sydney Games.”


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For more information on this study, please contact Ute Frey at the Haas School of Business at 510-642-0342 or at frey@haas.berkeley.edu.