An Olympics of Competing Machines

Dartmouth economics professor Andrew Bernard has come up with a mathematical system to predict the medal standings of the Olympics. He has tested his formula on the Olympic games dating back to 1960, and claims it has an accuracy of 96 percent.

In the formula he equates athletes to complex machines. You need materials to build the machines, which are people, meaning countries with large populations have an edge. Then you need resources, which is a country’s income, to the produce the people into great athletes. The “machines” last a while, so past results are another factor. The final factor is what he calls the “host factor” effect, which may be influenced by the crowd or other intangibles.

For the upcoming Beijing Olympics Bernard predicts that the U.S. will lead all countries in total medals, followed by Russia in second, and China in third. In the gold medal tally he calculates the Chinese will win 37 medals to the U.S.’s 36, but he recognizes that those numbers are too close to be conclusive.

Listen to an NPR interview with Bernard at

Source: NPR

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