If you had one chance to predict the winner of this summer’s World Cup, which team would you choose? Defending champions Germany, perennial favorites Brazil, or former champions Spain?
Most fans would likely plump for one of those three. But that’s just not quantitative enough for investment banks.
With the start of the World Cup in Russia less than a month away, UBS deployed a team of 18 analysts and editors, and ran a computer simulation of the tournament 10,000 times, in an effort to predict the likely winner of the tournament.
It’s a familiar game for UBS and other banks, many of which run competing models to predict the quadrennial World Cup. While the simulations might sound impressive, they’re not always accurate: In 2014 UBS said hosts Brazil would prevail, only to see the team humiliated in a 7-1 semifinal loss to Germany, the eventual winner.
This year’s UBS model comes wrapped in a comprehensive 17-page research note. As well as colorful facts about the tournament host – did you know Russia has 11 different time zones, though World Cup matches will only take place in four? – the bank includes plenty of advice for investors seeking growth potential in Russia.
But the headline is that tournament model, which UBS dubs the World Football Elo Rating. It turns up a few surprises, for sure: long-term underachievers England are ranked fourth, with an 8.5 percent chance of winning the World Cup and a 66.2 percent chance of making it through to the quarter-finals. That’s the third-highest probability of any team in the tournament.
Highly ranked European teams France and Belgium finish below England in the prediction league, coming in fifth and sixth.
Which leaves the top three. So, what did those 10,000 simulations and 18 analysts conclude about the likely winner of the World Cup?
It’s Germany, by some distance, with Brazil and Spain coming in behind.
Who’d have thought it, the computers agreeing with everyone else?
