England's squad value ranks second among World Cup teams, trailing only France, according to a machine learning algorithm developed by statisticians. The model, which simulates the tournament 100,000 times, predicts Spain as the overall favourite with a 14.5% chance of winning, followed by England and France at 12.4% each, and Germany at 11.2%.
The algorithm combines four key data sources: retrospective team strength based on matches over the past eight years; prospective strength from bookmaker odds; individual player ratings based on goal contributions; and player market values from Transfermarkt. These are fed into a random forest model trained on major tournament matches since 2006.
Additional factors include team-specific details like FIFA rank and Champions League semifinalists, as well as country-specific socioeconomic factors such as GDP per capita. The model produces probabilistic forecasts for each match, simulating goal outcomes using loaded dice.
Portugal and Argentina also have strong chances at 8.9% and 8.2%, respectively. The United States has a 78% probability of reaching the Round of 32, but only a 1% chance of winning the final at MetLife Stadium on July 19.
