Group Stage Wrap: The GNOE Returns
Our nothing-to-do-with-soccer World Cup predictor was, ahem, quite profitable.
Before the World Cup started, we at Foreign Policy joined the likes of Nate Silver and Goldman Sachs by putting together a prediction model for all the matches. But unlike those statistical and financial wizards, we didn't base our model on soccer. That's right, no soccer at all. Instead, we used our own indices of a country's attractiveness for investment and its ability to provide security and basic amenities for its citizens. So how did we do?
Before the World Cup started, we at Foreign Policy joined the likes of Nate Silver and Goldman Sachs by putting together a prediction model for all the matches. But unlike those statistical and financial wizards, we didn’t base our model on soccer. That’s right, no soccer at all. Instead, we used our own indices of a country’s attractiveness for investment and its ability to provide security and basic amenities for its citizens. So how did we do?
Terribly, right? Actually, no. It turns out that the Greatest Nation on Earth Index (GNOE) wasn’t too bad at all at forecasting results, even though its inputs were supposedly unrelated — or at least only distantly related — to the sport in question. Of the 16 teams that advanced from the group stage to the knockout rounds in the World Cup, the GNOE picked 10 correctly. That’s more than Goldman Sachs and FiveThirtyEight, which each came up with nine. Thanks, Spain!
Moreover, a gambler using the GNOE to bet on the matches would have made a handsome return. The GNOE is not completely precise, so where two countries had ratings within 0.1 of each other, we called it a draw; otherwise, the country with the higher GNOE was predicted to win. Using this rule, a $1 bet on each of the 48 group stage matches would have yielded a $13 profit, according to the final odds; that’s a 27 percent bump. (You could use a more sophisticated betting method, of course, but that’s not really our field….)
To be sure, the GNOE picked the correct result in only 26 out of 48 matches, but some of those picks turned out to be quite lucrative. The biggest payoffs came from Spain’s losses to Chile (roughly 9 to 2) and the Netherlands (4 to 1), the draws between Germany and Ghana (9 to 2) and Brazil and Mexico (4 to 1), and the upset of Italy by Costa Rica (11 to 2).
So is the GNOE really onto something, or are these results meaningless? For one thing, we may not do as well in the knockout stages, given that Brazil is still in the tournament. But even if we did, we’d have to use the GNOE as a predictor over the course of multiple World Cups, just to make sure it wasn’t especially lucky this time around. If we still found that the GNOE consistently foretold the outcomes of matches, then we might conclude that well-run countries with good business environments were indeed able to produce better soccer teams.
That’s not a completely counterintuitive conclusion, but it would still be surprising that these nebulous environmental factors could predict results just as well as some very smart people focused on the soccer teams themselves. But maybe that’s just a commentary on the World Cup. Anything can happen, and — at least in the group stage — it usually does.
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