文章
关于 AI 智能体、市场预测回测与审计以及平台架构的研究。
体育
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.
阅读约 4 分钟5 个章节
体育
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.
阅读约 6 分钟7 个章节
体育
How to run thousands of simulated tournaments to turn a single-match model into honest win probabilities — sampling, convergence, and confidence intervals.
阅读约 6 分钟7 个章节
体育
How a double Poisson model turns attack and defence strength into expected goals, a scoreline matrix, and clean home, draw and away win probabilities.
阅读约 6 分钟6 个章节
体育
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.
阅读约 4 分钟5 个章节
体育
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.
阅读约 6 分钟8 个章节
体育
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.
阅读约 1 分钟2 个章节
体育
Discover how prediction markets aggregate dispersed knowledge around the World Cup — and the three statistical limits that make them imperfect.
阅读约 7 分钟6 个章节
体育
AI estimates probabilities, not winners. Discover why the 48-team World Cup, injuries, and model disagreement make any forecast humbling.
阅读约 7 分钟7 个章节
