Artificial Intelligence Sunbs England, Predicts Winner of 2026 FIFA World Cup
- An AI model has predicted France as early favourites to win the 2026 FIFA World Cup starting later this month
- The system analysed over 1,200 data points across all 48 qualified nations to pick the eventual winner for the tourney
- England, Spain and Argentina are also tipped to reach the semi-finals by AI
The countdown to the 2026 FIFA World Cup is already producing bold predictions, and artificial intelligence has now stepped in with its own verdict on who could lift football’s biggest prize.
With the tournament just days away, a data-driven model has analysed every qualified nation and pointed to a familiar heavyweight as the most likely champion.
Source: Getty Images
According to Opta, the expanded World Cup, which will feature 48 teams across the United States, Mexico and Canada, is expected to be the most unpredictable edition in history.
But according to the AI system, one nation still stands above the rest.
AI model breaks down global contenders
The prediction was generated by The Action Network using an AI model fed with more than 1,200 data points across 25 performance variables per team.
These included squad depth, recent form, tactical efficiency, player output, and historical tournament performance, allowing the system to simulate the entire competition from group stage to final.
The results suggest a semi-final lineup featuring France, Spain, England and Argentina, four of football’s most consistent international forces in recent years.
Argentina, the reigning champions after their 2022 triumph in Qatar, are expected to make another deep run led by Lionel Messi’s successors, while England and Spain continue to build squads packed with elite talent.
Despite the increased unpredictability of a 48-team format, the model still favours established football powers when it comes to the final stages of the competition.
France backed to win repeat of 2022 final
At the centre of the prediction is France, who are tipped to go one step further than their 2022 campaign by defeating Argentina in the final.
The model highlighted several factors behind France’s projected success, including their world number one ranking, squad value estimated at €1.48 billion, and the continued influence of Kylian Mbappe.
Source: Getty Images
France’s tournament experience under Didier Deschamps also plays a major role in the prediction, with the long-serving manager’s consistency in international competitions seen as a key advantage.
A rematch of the 2022 final is expected in this simulation, but this time the outcome swings in France’s favour as they edge Argentina to lift the trophy in New Jersey.
If the prediction proves accurate, it would mark another defining moment for a team that has remained at the top of international football for over a decade.
Norway and Morocco among surprise dark horses
Beyond the favourites, the AI model also identified several nations capable of disrupting the traditional hierarchy.
Norway emerged as the strongest “dark horse” candidate, largely driven by the presence of Erling Haaland and Martin Ødegaard, alongside an impressive qualifying record.
Austria, Bosnia and Herzegovina, Morocco and DR Congo were also listed as teams that could outperform expectations during the tournament.
Morocco, in particular, continues to attract attention following their historic run to the semi-finals in 2022, while DR Congo’s inclusion reflects growing belief in African teams ahead of the expanded World Cup.
With more teams, more matches and more unpredictability than ever before, the 2026 edition is expected to challenge even the most advanced prediction models.
Still, for now, the data points firmly towards one conclusion: France stand as the team to beat.
Kaka predicts 2026 World Cup winner
Earlier, Legit.ng reported that Brazil legend Kaka has made a bold prediction ahead of the 2026 FIFA World Cup.
The 23rd edition of the Mundial will take place in the United States of America, Canada, and Mexico from June 11 to July, 2026.
Source: Legit.ng
