Augmented intelligence for FIFA predictions - Jethuri, K.; Emmadi, S. C.; Samudrala, S.; Natarajan, J.; Ghotkar, P.; Natu, M. (Machine Learning and Data Mining for Sports Analytics. MLSA 2024. Communications in Computer and Information Science, 2025)
In today`s data-centric world, businesses strive to monitor, manage, and optimize their operations efficiently. While data-driven solutions are increasingly popular, they often fall short due to challenges such as limited data availability, poor data quality, or high computational costs. Moreover, relying solely on data overlooks the valuable intuition and expertise of domain experts. To address this gap, we propose augmenting the power of data-driven analysis with human intuition. We demonstrate this approach through our FIFA match prediction engine, which seamlessly integrates data-driven analysis with fan intuition, resulting in a significant boost in accuracy from 65% with traditional data-driven approaches to 81%, effectively adapting to diverse match scenarios.