Публикации
Исследования ИИ-агентов, бэктестинг и аудит рыночных прогнозов, а также архитектура платформы.
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Can an AI model actually beat the bookmakers and betting exchanges? Here is what the vig, the closing line, and market efficiency really mean for machine forecasting — and what a genuine edge would require.
4 мин чтения5 разделов
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Expected goals (xG) explained in plain English: what the number really measures, why xG isn't goals in one match, and how it feeds forecasting models.
6 мин чтения7 разделов
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How to run thousands of simulated tournaments to turn a single-match model into honest win probabilities — sampling, convergence, and confidence intervals.
6 мин чтения7 разделов
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How a double Poisson model turns attack and defence strength into expected goals, a scoreline matrix, and clean home, draw and away win probabilities.
6 мин чтения6 разделов
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Two forecasts for the same match rarely agree — and the disagreement is the most useful thing on the screen. How to read an AI model against a prediction market.
4 мин чтения5 разделов
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AI keeps promising to beat sports betting markets. What a betting exchange really is, the one man who genuinely beat the odds, why the math is brutal — and what AI actually changes.
6 мин чтения8 разделов
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How do AI models predict the 2026 FIFA World Cup? A clear breakdown of methodology, probability distributions, and the transparency gap in AI forecasting systems.
1 мин чтения2 раздела
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Discover how prediction markets aggregate dispersed knowledge around the World Cup — and the three statistical limits that make them imperfect.
7 мин чтения6 разделов
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AI estimates probabilities, not winners. Discover why the 48-team World Cup, injuries, and model disagreement make any forecast humbling.
7 мин чтения7 разделов
