Behind the Predictions
Football Methodology
Data Sources: We use API-Football.com as our primary data source (1,180+ leagues worldwide), with Understat as a fallback for xG data in major European leagues. All data is validated and processed through our statistical pipeline.
Model: Poisson-based probability modeling with Dixon–Coles correlation for low-scoring matches, opponent‑adjusted strength ratings, and a recency‑weighted blend (exponential decay).
Coverage: Teams from any league with sufficient recent match data (typically 15–20 matches) can be analyzed. The system automatically spans multiple seasons to gather historical data.
Data Quality: We prioritize Expected Goals (xG) when available, falling back to observed goals for leagues without xG coverage. Recent matches are weighted more heavily than older ones.
Basketball Methodology
🎯 Four-Layer Stack
Season baseline with prior merge, SRS-lite opponent adjustment, recency blend (last K games), and venue/splits adjustments. Optional enrichment when lineup/injury data is available.
📊 6 Core Markets
Win/Loss, Total Points O/U, First/Second Half O/U, and Team Totals—no draws in basketball.
📈 Full Transparency
Technical Notes show each layer's contribution. Data Sources disclose APIs, sample sizes, and caveats. AI Analysis provides insights on-demand.