Daniel Johnson makes remarkably accurate Olympic medal predictions. But he doesn’t look at individual athletes or their events. The Colorado College economics professor considers just a handful of economic variables to come up with his prognostications.
The result: Over the past five Olympics, from the 2000 Summer Games in Sydney through the 2008 Summer Games in Beijing, Johnson’s model demonstrated 94% accuracy between predicted and actual national medal counts. For gold medal wins, the correlation is 87%.
His forecast model predicts a country’s Olympic performance using per-capita income (the economic output per person), the nation’s population, its political structure, its climate and the home-field advantage for hosting the Games or living nearby. “It’s just pure economics,” Johnson says. “I know nothing about the athletes. And even if I did, I didn’t include it.”
– Forbes, see also Daniel Johnson’s own website
Which countries tend to do best in the Winter Olympics? The ones with large populations, cold winters, and wealth. Nothing surprising there.
And yet, the strength of these connections and the accuracy of Johnson’s predictions is impressive. And it is perhaps surprising that this accuracy is achieved free from any data on the athletes.
This hints at a revolution still in its infancy, and one with with great promise: Uncover surprising, far from intuitive and yet important connections, using statistics, vasts amount of date, and modest computer power.