Will Antoine Griezmann make it to the 2026 World Cup with France? We analyze statistics, current events, and his role with Les Bleus on their way to the most important tournament on the planet.
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WHICH TEAMS WILL PERFORM BEST ACCORDING TO AI?
Will Brazil lift the trophy again? Will France repeat its dominance? Or will a dark horse pull off a surprise? It's no longer just about intuition or mystique: now, artificial intelligence is entering the field to predict which teams might perform best at the 2026 World Cup. Through models trained on historical data, FIFA rankings, average age, playing style, and even injuries, AI has projected some pretty interesting scenarios… and a few unexpected results. If you're one of those who makes predictions based on gut feeling, this article will make you think twice. Get ready, because here the numbers are also saying "goal."
How AI Predicts Team Performance
Artificial intelligence, in the context of football, is not just a soulless game of algorithms. It involves complex prediction models that analyze millions of data points: from previous results, goals scored and conceded, to details such as average temperature at venues or the performance of key players depending on the type of grass. Everything has an impact.
Data that Feeds the Algorithms
Platforms like Opta, StatsBomb, and SciSports work with neural networks and machine learning to refine predictions. For example, the Elo Football model, widely used by betting houses and universities, has been updated to include 48 teams in 2026, a new feature compared to previous World Cups.
Win and losing streaks in the last 24 months.
FIFA ranking, updated monthly.
Average squad age and number of players in top leagues.
Recent injuries and recovery of key players.
Statistics of possession, passing accuracy, and goal conversions.
The interesting thing is that, according to studies Developed by MIT and Google DeepMind, the AI correctly predicts between 62% and 74% of matches in group stages, and slightly less in knockout stages. But be warned: it doesn't replace the magic of football, it only gives us another perspective to see the game with the eyes of a statistician… and the heart of a fan.
Favorite Teams According to AI Models
The AI-generated rankings for the 2026 World Cup agree on several points, but there are also surprises. Here are the countries that, according to different simulators such as those from The Analyst, FiveThirtyEight, and Google Cloud, have the highest probability of advancing to the decisive stages.
Top 5 Teams with the Best Projection
France – The AI gives them between an 18% and 22% probability of winning. They have a young squad, experience, and depth. Their vertical style makes them lethal.
Brazil – Between 15% and 19% chance. Although in generational transition, their attacking talent and tradition carry a lot of weight.
Argentina – Around 14% probability. With Messi probably in his last World Cup and a consolidated core, they remain among the favorites.
England – With a golden generation reaching maturity, their projection has risen to 13% in some models.
Spain – Although inconsistent, their dominant possession and new talents like Lamine Yamal keep them in the top 5.
And the surprises? Countries like Morocco, Japan, and the United States appear as potential quarterfinalists in up to 30% of the simulations. Mexico, meanwhile, performs better when playing at home: its chances of reaching the round of 16 rise from 55% to 68% according to the Elo model when playing at home.
Fun fact: in Qatar 2022, the models gave Morocco a 3% probability of reaching the semifinals… and they did. So, even though AI knows a lot, football remains that crazy, unpredictable thing we love.
Limitations of AI and Unexpected Predictions
Although artificial intelligence models are becoming increasingly accurate, there are factors they simply cannot measure: last-minute injuries, controversial refereeing decisions, surprising tactical changes, or, of course, grit and heart. That's why there's always room for surprises.
Can AI be wrong?
Absolutely. In 2014, Goldman Sachs' AI predicted Brazil would win with over a 40% probability… and Germany beat them 7-0. In 2022, many models underestimated Croatia and Morocco. In 2010, nobody bet on Spain at the start, and we all know how the story ended in Johannesburg.
AI does not consider the emotional motivation or moods of the squad.
It cannot predict unexpected tactical changes or sudden injuries.
Nor does it measure the pressure of playing at home, which can be positive or negative.
It does not yet integrate the psychological impact of penalties or extra time.
It depends on the data it has: if there is little information about an emerging team, the model can be wrong.
Even Thus, AI becomes a useful tool for understanding trends and objectively comparing teams. For those who enjoy analyzing football beyond the roar of a goal, these models offer a new way to experience the World Cup lead-up. But you know what they say: no matter what the algorithm says… there's always room to dream about the cup.
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