Show HN: Reasoning-driven World Cup betting that returned 202% (121 bets) (github.com)

A personal research project has successfully explored the potential of a frontier model to enhance football match betting strategies for the upcoming 2026 World Cup. The approach involves constructing a detailed factual dossier for each match and utilizing an advanced model to independently estimate game probabilities without being influenced by existing market odds. By placing bets only when discrepancies arise between the model's predictions and market prices, the researchers achieved a remarkable 202% return on investment over 121 bets, escalating their bankroll from $255 to $771. This project is significant for the AI/ML community as it showcases the practical application of advanced reasoning models in financial decision-making, highlighting the importance of disciplined betting and pricing strategies over mere accuracy in predictions. Key technical details include the use of a calibrated reasoning model that factors in various game contexts and player statistics, the implementation of a quarter-Kelly betting strategy to manage risk, and a kill-switch mechanism to halt betting if the predicted edge diminishes. By combining data gathering, independent reasoning, and market analysis, this innovative approach sets a new precedent for applying AI in betting markets while emphasizing transparency and responsible practices.