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Spain are the most likely winners of the 2026 FIFA World Cup, according to a new AI-powered prediction model that simulated the tournament 10,000 times.
The model gave Spain a 6.87% chance of lifting the trophy, the highest of any nation in the expanded 48-team tournament. While the figure may appear small, it is more than three times the probability of an evenly distributed field, where each team would have roughly a 2% chance of winning.
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Argentina ranked second with a 2.94% chance, followed closely by France at 2.91%. England came fourth at 1.61%. Portugal rounded out the top five with just 0.64%, creating a significant gap between the leading contenders and the rest of the field.
According to the simulation, the 2026 World Cup remains one of the most open tournaments in history. Even Spain, the favorite, only wins approximately one out of every fifteen simulated tournaments.
The forecast was produced using Maia, an AI system developed by data technology company Matillion. While the prediction itself attracted attention, the speed at which the model was created became an equally important part of the story.
A similar forecasting project ahead of Euro 2020 required months of manual work. Developers had to build dozens of data pipelines, process team statistics, collect historical results, and create custom logic to simulate tournament outcomes.
This time, the forecaster described the objective in plain English through a conversational interface. The AI suggested running thousands of tournament simulations, generated the required code, executed the calculations, and produced detailed reports summarizing the results.
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The foundation of the model is an Elo rating system based on nearly 49,000 international matches dating back to 1872. Elo ratings measure team strength by adjusting scores after every result, rewarding wins against strong opponents and penalizing losses to weaker teams.
The model also incorporates several modern football analytics factors. Home-field advantage was removed because World Cup matches are played on neutral venues. Recent performances carry more weight than older results, and expected goals (xG) data was added to evaluate the quality of scoring chances rather than relying solely on match outcomes.
These adjustments led the model to several notable conclusions. Spain ranked highest because of their ability to consistently create high-quality scoring opportunities. France received a stronger rating than recent results alone would suggest. Brazil, despite their historic World Cup success, were ranked only seventh, reflecting the model's focus on current performance rather than reputation.
Travel and scheduling were also considered. Because the 2026 World Cup is being hosted across the United States, Canada, and Mexico, teams facing longer travel distances and shorter recovery periods received minor penalties.
The simulation's most likely tournament scenario included several surprises. Spain win their group, Austria defeat Argentina during the group stage, Japan eliminate Brazil, and Canada reach the semi-finals on home soil before losing to England.
The model's most likely final predicts Spain defeating England 1-0 to claim the championship.
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For the Golden Boot race, the model identifies Norway striker Erling Haaland as the leading candidate due to his exceptional international scoring rate. However, if Norway are eliminated early, France's Kylian Mbappé and England's Harry Kane could surpass him through additional matches played.
Beyond football predictions, the project demonstrates how AI is reshaping analytical work. Tasks that once required months of specialized effort can now be completed in a matter of hours through natural-language collaboration with AI systems.
The developers noted that six different versions of the model and two complete rebuilds were produced in a single afternoon, compared to a single model development cycle that previously took an entire season.
While Spain remain the favorite, the model also highlights the tournament's unpredictability. A 6.87% winning probability means another nation wins in more than 93% of simulated tournaments.
The full prediction model, including complete team odds and projected knockout brackets, has been published on the Maia blog.
