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We Asked Our AI Model to Simulate the World Cup 100,000 Times: Here Are the Results

The Sydney Morning Herald

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Date Published
12 June 2026
Priority Score
0
Australian
Yes
Created
12 June 2026, 02:01 am

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Description

There are 48 teams, 104 matches and infinite possibilities at the World Cup. We crunched the numbers to find every team’s probability of success.

Summary

This reporting describes the application of Monte Carlo simulations powered by statistical models to predict outcomes for the 2026 FIFA World Cup. While it showcases the use of AI for complex data analysis involving variables like Elo ratings and expected goals, the analysis is limited to narrow, predictive analytics for sports. The content does not engage with existential or catastrophic AI risks, nor does it discuss frontier AI safety or global governance frameworks. As a result, its contribution to AI safety discourse is negligible, focusing instead on consumer-facing predictive modeling.

Body

AdvertisementAt the beginning of any World Cup, you can find all kinds of predictions and prognostications.But the vast majority rely the viewpoint of one person, one computer or one Paul the Octopus, may he rest in peace.Paul the octopus predicted a German win over England at the 2010 FIFA World Cup.DDPTo kickstart this year’s World Cup, our head of visual stories Mark Stehle used AI, filled with a bunch of cutting-edge statistics, to run what is called a “Monte Carlo simulation” to identify the most likely tournament winner.In basic terms, the Monte Carlo simulation ran through the 48 teams and their data with random probabilities thousands of times and reported which scenarios occurred the most.AdvertisementBasically, Stehle asked the AI to play 100,000 distinct versions of the 104-match 2026 World Cup schedule, and now we can present you with the findings, including breaking the teams into tiers, from the heavyweights to the longshots.Spain topped the simulations with a baseline winning percentage of 16.1 per cent of the time, while the Socceroos finished with only a 0.10 per cent winning percentage, which ranks them 33rd out of 48 teams.Among the numbers used are the dynamic Elo Ratings for each team, advanced stats like expected goals [known as xG], travel and rest degradation and the strength of the group and knockout bracket that each team is in.Spain’s possession-based playing style should allow them to handle the North American heat better than other nations, according to the simulations, while Portugal’s supposedly softer group and bracket paved them a road to victory in several of the simulations.AdvertisementNo matter how many simulations you run, the crazy randomness of the actual World Cup will produce scenarios the AI never dreamt of, but the finding sure make for an interesting guide to how the tournament could play out.As a comparison, here are the predictions of our soccer writers and some other experts.News, results and expert analysis from the weekend of sport sent every Monday. Sign up for our Sport newsletter.AdvertisementGet across our World Cup coverageYour group-by-group guide to the 2026 World CupCan you pick the winners?Quiz: How many World Cups have the Socceroos qualified for?‘World Cup of chaos’: Can the most expensive sporting event deliver?SaveYou have reached your maximum number of saved items.Remove items from your saved list to add more.ShareLicense this articleMore:FIFA World CupSocceroosSpainEnglandPortugalArgentinaFranceAIRoy Ward is a sports writer, live blogger and breaking news journalist. He's been writing for The Age since 2010.Connect via X or email.Mark Stehle heads the Visual Stories Team at The Age, The Sydney Morning Herald, Brisbane Times and WAtoday.Connect via email.AdvertisementAdvertisement