AI Backs Spain for 2026 World Cup
As artificial intelligence becomes increasingly influential across industries, it is now drawing attention in an unexpected arena—predicting the winner of the FIFA World Cup.
During the 2022 World Cup, generative AI was still an emerging technology. Few imagined that within four years, AI chatbots would become part of discussions surrounding potential World Cup champions. Ahead of the 2026 tournament, football fans, researchers, and financial institutions are increasingly turning to AI models for predictions.
Recent assessments by technology platforms and research initiatives show that different large language models (LLMs) have reached different conclusions regarding the likely winner of the 2026 FIFA World Cup.
According to several technology-focused analyses, ChatGPT, Claude, and other Western AI models generally identify Spain as the strongest contender for the title, with France emerging as the second-most favored team.
Technology publication Tom’s Guide reportedly posed the same question to Gemini, ChatGPT, and Perplexity, with all three selecting Spain as the most likely champion. Analysts at Bank of America also found that Microsoft Copilot rated Spain and France as nearly equal contenders.
However, Chinese AI platforms have reached different conclusions. Chinese chatbots DeepSeek and Qwen favor defending champions Argentina as the most likely winners. Meanwhile, French AI platform Le Chat places France at the top of its predictions.
The differing forecasts have revived comparisons with Paul the Octopus, the famous octopus that gained international attention for accurately predicting several World Cup matches years ago. In many ways, AI is becoming the modern equivalent of technology-driven football forecasting.
Researchers, however, caution against treating AI predictions as definitive outcomes.
At Ludwig Maximilian University of Munich, researchers are running an initiative called “LLM SoccerArena,” which compares match predictions generated by AI models with actual results.
Researcher Stefan Feuerriegel said that it is important to assess how reliable large language models are in real-world decision-making scenarios. The project therefore evaluates model performance by comparing predictions against actual match outcomes.
Analysts note that AI models do not predict the future in a literal sense. Instead, they generate probability-based assessments using historical data, recent performances, squad depth, injuries, rankings, and publicly available information.
Ultimately, football remains a sport defined by unpredictability. Regardless of what algorithms suggest, the final verdict will be delivered on the pitch.
//DBTech/IH/EK/OR//
