The 2026 World Cup is the biggest in history in several respects. There is the fact that it is being held across an entire continent, of course, meaning fans will even travel further distances between games than in the 2018 World Cup in Russia. But it’s also the biggest in scope, with 48 teams (expanded from 32) and 104 games.
This is also the first AI World Cup, in the sense that consumer-facing AI models are widely available. And as you might expect, there is a steady business in “modeling” the World Cup. X is completely littered with people posting their AI-based predictions for the tournament, and plenty of mainstream media outlets have been publishing AI predictions, too.
Take AI World Cup predictions with a grain of salt
Here’s the thing: these predictions are interesting and useful up to a point, but they are also not going to crack the code of how the World Cup will pan out. It’s not that AI can’t parse out useful insights – it can – but there won’t be much deviation from the World Cup betting odds. By that, we mean AI is going to suddenly pick Uzbekistan or Jordan to win the World Cup, making everyone look foolish in hindsight.
We know that previous World Cups have thrown up surprises. France, as a dominant champion, exited in the Group Stage in 2002. Germany flopped in 2018 after winning the previous tournament. Morocco came from nowhere to reach the semi-finals in 2022 as a 200/1 longshot. The point, as such, is that there are always surprises.
Yet, it is the format of this World Cup that makes it so difficult to model. Forecasters have used AI to look at every game, creating nice and neat scenarios on a pathway to the World Cup Final on July 19th.
A lot of possible outcomes for the knockout brackets
But the World Cup is comprised of 12 groups of four teams, 32 of whom will make the knockout rounds. If a few fancied teams slip up in the group stages, finishing second or third when expected to win, you could end up with a lopsided side of the bracket. FIFA seeds the big teams to keep them apart early on in the tournament, but it falls apart if they don’t form as expected.
Having one side of the draw stronger than the other does two things: First, it makes the path to the final more difficult for fancied teams. Secondly, it opens up the way for less fancied teams on the “good” half of the draw. A typical example of this was Germany in 2002, which benefited from winning its group and some shock results elsewhere. Its route to the Final was Paraguay, the USA, and South Korea – not soccer powerhouses – before losing to Brazil in the showpiece.
Something like this often happens in the World Cup, and because there are more permutations this time around, it is even more difficult to model. Basically, what we are saying is that people have used AI to model what seems like a perfect World Cup, with big teams going over the weaker ones.
Sports simply don’t work like that, and the World Cup, which has added variables such as the heat, player fatigue after the club season, the pressure felt by some teams, and player injuries, is often more chaotic than most. While the big nations usually win in the end, the trophy rarely goes to the pre-tournament betting favorite. It’s hard to predict, whether you are using AI or not, and that’s part of what makes it so enthralling.