Browsing Category: Betting Strategies

Calibration & Reliability

Trust Your Probabilities: Calibration, Brier Decomposition, and Reliability Diagrams

In the world of predictive modeling, calibration is key. It makes sure a model’s predictions match real events. For example, if a model says there’s an 80% chance of rain, it should rain 80% of the time. This is critical in areas like sports betting, finance, and weather forecasting. But, many modern neural networks struggle […]

Copulas & Correlation

Correlation that Costs: Pricing Parlays and Same‑Game Props with Copulas

In sports betting, knowing about same-game parlays (SGPs) is key. Traditional parlay math assumes events are independent. But, SGPs show that events are often linked. For example, if Team A wins, the quarterback likely passes over 275 yards. The game total also tends to be over. This connection makes pricing tricky. Sportsbooks need advanced methods […]

Negative Binomial & ZIP

Beyond Poisson: Modeling Over‑Dispersion and Rare Events

In sports analytics, traditional methods often fail to accurately model count data like goals and strikeouts. The Poisson distribution assumes the mean equals the variance, but this rarely happens in real life. This article explores the Poisson model’s limitations, focusing on over-dispersion and many zeros. We introduce two powerful alternatives: the negative binomial and the […]