AI-powered sports analytics
Statistical models,
built for the way sports actually behave.
WorldSportsXAI runs a Dixon-Coles bivariate Poisson model plus a 10,000-run Monte Carlo tournament simulator on the 2026 FIFA World Cup — and compares the output live against consensus-market prices. No vibes. Just probabilities, calibration, and the math behind them.
- International matches in training set
- 49,000+
- Monte Carlo tournament runs
- 10,000
- Model Brier skill vs. uniform baseline
- +7.0%
- Coverage of public liquidity markets
- 43 / 48
2026 FIFA World Cup model
Live champion probabilities, group-stage simulation, calibration backtest, and a side-by-side comparison against consensus-market implied odds.
Open model →InsightsEditorial & analysis
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Browse picks →The method, plainly.
We fit a Dixon-Coles bivariate Poisson with exponential time decay over every senior international match since 1872 — 49,000+ games. We then simulate the full World Cup tournament tree 10,000 times to produce stage-by-stage probabilities. Where consensus prediction markets disagree with the model, we flag the gap and explain the recent form behind it.
Read the full methodology →- Identifiability: zero-sum recentered attack/defense ratings make team strengths directly comparable.
- Time decay: ξ = 0.0019 — a match's weight halves every ~365 days, so recent form matters more than 2014 form.
- Low-score correction: the Dixon-Coles τ correction fixes the underestimation of 0-0, 1-0, 0-1, 1-1 scorelines that plain Poisson gets wrong.
- Calibration: backtested on Worlds Cups 2018 + 2022 — 128 real matches — Brier skill of +7.0% over a uniform baseline.