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Model Documentation
Soccer Models
Deep-dive into the methodology, edge detection, and operational details for our EPL prediction models powered by expected goals (xG) analytics.
Available Models
Soccer Totals
Over/Under goal predictions using expected goals (xG) and Poisson modeling.
Key Features
- xG-based team ratings from Understat
- Poisson distribution for goal probabilities
- Multi-line analysis (1.5, 2.5, 3.5, 4.5)
- Expected value edge detection
Asian Handicap
Spread predictions using Skellam distribution for margin modeling.
Key Features
- Skellam distribution for margin projections
- Quarter and half line support
- Edge detection across multiple books
- CLV tracking and performance analytics
Soccer Model Overview
Our soccer models are built on expected goals (xG) analytics, leveraging historical shot quality data to project match outcomes. Key principles include:
- 1.xG-based ratings - Team attack and defense ratings derived from expected goals for and against, providing a more stable signal than actual goals.
- 2.Poisson/Skellam distributions - Goals follow Poisson distributions. We use this to calculate precise over/under probabilities and margin distributions.
- 3.Time-weighted ratings - Recent matches weighted more heavily than early-season games to capture current form while maintaining sample size stability.
- 4.EV-based filtering - Every pick must have positive expected value (EV) based on our model probability versus the implied book probability.