Building an ML football forecaster in R The post Can Machine Learning Predict the World Cup? appeared first on Towards Data Science .
A single model hands you a single answer and no sense of how much it hinges on the dozens of choices buried inside it. The post I Built 11 Models to Predict the 2026 World Cup.
Building a forecast from Elo, Poisson, and 10,000 simulations The post Who Will Win the 2026 Soccer World Cup? appeared first on Towards Data Science .
arXiv:2607. 18084v1 Announce Type: new Abstract: Predicting a football match before kickoff requires more than knowing past results: a model must use changing information and make a clear prediction before the answer is available.
Predicting a football match before kickoff requires more than knowing past results: a model must use changing information and make a clear prediction before the answer is available. We present WorldCupArena, a dynamic benchmark for language models and deep-research agents.
arXiv:2608. 03416v1 Announce Type: new Abstract: Large language models (LLMs) are now regularly asked to forecast real-world events, but comparisons are often difficult because models receive different information, use different tools, and are evaluated under different rules.
arXiv:2606. 28795v1 Announce Type: new Abstract: Machine Learning (ML) algorithms, such as k-Nearest Neighbours (kNN) or random forest, eschew the ideal of true data models in favour of predictive performance.
arXiv:2606. 07572v1 Announce Type: cross Abstract: Despite Japan being one of the world's largest advanced democracies, the development of election forecasting models for its national elections remains limited.
arXiv:2607. 24573v1 Announce Type: new Abstract: Large language models (LLMs) increasingly support decisions about uncertain future events, yet evaluating their ability to forecast real-world outcomes remains difficult.
arXiv:2606. 13959v1 Announce Type: new Abstract: Sierra Leone's agriculture operates with almost no data-driven decision support, and no published machine learning study has examined the country's crop yields.
arXiv:2607. 19054v1 Announce Type: new Abstract: In this work, we incorporate first principle physics into the construction of data-driven methods by considering a model that accounts for the different sources of energy losses during vehicle operations.
How should we ensemble time-series forecasts better? The post Information Theory and Ensemble Models appeared first on Towards Data Science .
arXiv:2601. 20771v2 Announce Type: replace-cross Abstract: Accurate forecasting of infectious disease incidence is critical for public health planning and timely intervention.