Daniel Johnson of Colorado College predicts Olympic medal counts.
The model is based only on non-athletic factors. Johnson’s semi-technical summary of the model gives the formula used. The variables used in the prediction are as follows:
- the total number of medals available
- per capita income
- whether the Olympics are being held in that country this year, or in the near future or near past, or in a neighboring nation
- a “nation-specific effect”
I’m not entirely sure what the “nation-specific effect” means, but I suspect it’s an adjustment for countries that consistently overperform or underperform the targets given by the rest of the model. I remember hearing in 2008 that it was quite strange that India, for example, did so poorly at the Olympics. (The explanation I heard a lot was that the Olympics don’t have cricket.) Australia, on the other hand, consistenly punches above its weight.
A working paper from 2002 suggests that previous iterations of the model also had climate-related variables; the press release says that it doesn’t any more, as those no longer seem to be significant. Presumably they are in the Winter Games and we’ll see them again in 2014.
For 2012, the predicted leaders in gold medals are the USA, China, Russia, Great Britain, and Germany; the predicted leaders in overall medals are the same, with Great Britain (the host country) and Germany reversed.
But is this overkill? Roger Pielke points out at freakonomics and at his own blog that the “naive” prediction that a country will do as well this year as it did four years ago has smaller errors than Johnson’s model. Johnson replies in a comment to Pielke that his model isn’t intended for predicting what each country will do, it’s intended to show which factors are important for Olympic success. In other words, he’s interested in the coefficients of his model and how they change over time, not what you get when you plug in values for any specific country.