world-cup-2026-prediction

The most complete and actively updated FIFA World Cup 2026 dataset on Kaggle. A clean, authentic, relational dataset covering the entire tournament (June 11 – July 19, 2026) with the first-ever 48-team format. Includes real match results updated daily, 1,248 players across all 48 squads, expected goals (xG), minute-by-minute match events.

AI World Cup: a reproducible benchmark for comparing free LLMs on FIFA World Cup 2026 predictions using standardized prompts, manual model responses, automated scoring, leaderboards, charts, and a GitHub Pages results website.

2026 World Cup predictor: Dixon-Coles + XGBoost + Neural Net + Hierarchical Bayesian (Stan/brms), stacked via meta-learner. R API (plumber) + single-file HTML dashboard with live market odds. Walk-forward, temporal split, isotonic calibration, stacking beats simple average.

Your GitHub stats, turned into a World-Cup-style player card

Monte Carlo engine predicting World Cup 2026 winners via Gradient Boosting ML. 5,000-run simulations trained on 20+ years of football data with advanced knockout variance modeling and modern tactical analysis.

Modelo predictivo en entornos de alta incertidumbre para el Mundial 2026: análisis estocástico que integra variables tácticas y financieras mediante simulaciones de Monte Carlo y modelos de Poisson.

Predicciones para el Mundial 2026 comparativamente con Plataformas de IA

KNN-DesicionTree-RandomForest-XGBoost

Public discovery links for World Cup AI Forecast

ML-powered predictor for FIFA World Cup 2026 match outcomes and title odds using XGBoost and historical data

An independent, verification-first forecasting system for the 2026 World Cup. Built by directing an AI coding agent under a written protocol, with the protocol, the session log, and two rejected experiments committed alongside the code.

Machine learning and statistical modeling project for FIFA World Cup 2026 analysis and prediction.