AI predicts the 2026 World Cup winner, and the answer given by the model is surprising

At the end of 2024, the MIT Data Science Laboratory released the 2026 World Cup AI prediction model. This model was trained using all game data from the past 22 World Cups plus all club data of players in the past five years, and ran 100,000 Monte Carlo simulations.

The model’s winning answer shocked fans around the world. Not Brazil, not France, not Argentina, but Spain. The model predicts that Spain's winning probability is 18.7%, which is significantly higher than second-place Brazil's 15.3%, third-place France's 13.8%, and fourth-place Argentina's 11.2%.

Why choose Spain for the model?

The core algorithm of the model not only looks at the team's historical performance, but also looks at the data of the player combination. Spain's 2024 European Cup championship has proved the ability of the new generation of players. Young players such as Yamal, Rodri, Lopez and Olmo are at their peak.

The model calculates that the average age of Spanish players is 25.3 years old, making them the youngest among the favorites to win the championship. FIFA ranks Spain 3rd, but the density of club-level players (La Masia, Real Madrid youth training) is the first in the world. The machine learning model was particularly sensitive to this combination of data, identifying Spain as the team with the most upside.

Brazil is predicted to be second

The Brazilian model estimates a 15.3% probability of winning, citing a balanced lineup and the traditional dominance of South American players. The attacking line of Vinicius, Rodrigo, Gabriel Martinelli, and Rafinha is one of the most luxurious Brazilian lineups in history.

The model comes with one reservation. Brazil failed to win the championship in 2014 and 2018, and was eliminated by Croatia in 2022. This kind of psychological pressure will make Brazil nervous in the knockout rounds. The model lowers Brazil's psychological factor by 3 percentage points. Without this adjustment Brazil would have been first.

France forecast underestimated

France's 13.8% surprised some fans, because France was the champion in 2018 and the runner-up in 2022, at the peak of the luxury generation. Players such as Mbappe, Dembele, Chuameni, Camavinga and Saliba are in their prime.

However, the model found that France's actual competition results have been declining in the past two years. France lost to Spain in the semi-finals of the 2024 European Cup and only scored 3 goals in the entire tournament. The model's weight on actual combat performance is particularly high, and France's declining data caused the model to rank France third.

Why is Argentina only 11.2%?

The 11.2% given by Argentina as the defending champion model made Argentine fans dissatisfied. But the case for the model is strong. Messi will be 38 years old in 2026, and the core ages of Lautaro, Alvarez, Di Maria and others are all over 30 years old.

The model predicts that Messi can play until the 2026 World Cup, but his condition will decline by 30% compared to 2022. The aging of this core player has compromised Argentina's overall combat effectiveness. In addition, Argentina's young substitutes have not yet fully matured, and the model's prediction for Argentina is conservative.

Who are the dark horse candidates?

The model predicts several potential dark horses. The first is Germany. In the 2024 European Cup, Germany lost to Spain in the home semifinals but its performance rebounded. The new generation of players Wirtz, Musiala and Vogt are growing up. The model gives Germany an 8.4% chance of winning the championship, ranking fifth.

The second is Portugal. Although Ronaldo is 41 years old, Mesozoic players such as Fernando Felix, Bernardo Silva, Joao Felix and Vitinha are at their peak. The model gives Portugal a 7.2% probability, ranking sixth.

Third is England. The golden generation of Bellingham, Foden, Saka and Kane are in stable condition. The model gives a probability of 6.8%, ranking seventh.

Model limitations

No AI model can completely predict football matches. The model is based on historical data, but the essence of football is a low-goal game. The number of goals scored in a single game is usually between 0 and 3, and an accident can determine the outcome. The model is extremely poor at predicting surprises.

The model also fails to predict injuries and mental state. If Messi is injured before the start of 2026, Argentina's probability will plummet, but the model cannot predict it in advance. If a team's morale collapses before a game, the model cannot capture it. These non-data factors make the model prediction accuracy only about 35% in previous years.

Accuracy of previous AI predictions

Before the 2022 World Cup, multiple AI models predict that the champions are Brazil, France, and England. As a result, Argentina won the championship and all AI models failed.

In 2018, the AI ​​model predicts that Germany, Brazil, and Spain are the favorites to win the championship. As a result, France won the championship, and the AI ​​prediction for France was 4th.

In 2014, the AI ​​model predicted that Brazil, Spain, and Argentina were the favorites. As a result, Germany won the championship, and AI's prediction for Germany was third.

Judging from previous performance, the accuracy of the AI ​​model in predicting the championship is only 30% to 35%, which is 15 percentage points higher than the accuracy of simply guessing FIFA's No. 1 ranking but far from reliable.

Bookmaker odds comparison

An interesting comparison between the model predictions and the bookmaker's opening odds. In December 2024, major gambling companies will open the market with odds of 7 to 1 for Spain to win, 6 to 1 for Brazil, 7 to 1 for France, and 9 to 1 for Argentina. This is almost the same as the probability of the MIT model, indicating that the betting company’s algorithm and the academic model are heading in the same direction.

However, the betting company's odds will continue to adjust due to the flow of betting funds. If a large amount of money is bet on Brazil, the odds will be adjusted from 6 to 1 to 5 to 1 or even lower, which is decoupled from the model prediction. This market dynamic means that betting odds cannot be fully equated with AI predictions.

Should fans trust AI?

The significance of AI predictions to ordinary fans is reference rather than decision-making. If you bet money on AI predictions, you may lose all your savings, because the uncertainty in football is far greater than any model can capture. If you just watch a lively AI prediction, it can be a topic after dinner.

The real joy of watching football is the unpredictability. The World Cup would lose its charm if AI could accurately predict the outcome of every game. Moments such as upsets, buzzer beaters, and miracles cannot be captured or replaced by AI. This is the most fascinating part of football.

The truth in 2026 can only wait

Regardless of whether the AI ​​predicts Spain, Argentina or others, the final champion can only be announced after the final whistle blows in the MetLife Stadium final on July 19, 2026. Models can give probabilities but not certainty.

The biggest contribution of this MIT model is not to predict the championship, but to allow fans to see the extent to which modern football has been digitized. Every touch, every run, every pass of every player is recorded, analyzed, and predicted. This data revolution has changed the way football is run and made watching football more interesting. AI prediction is a microcosm of this revolution, and it will only become more popular in the future.