NBA Analysis
Data-driven win probability analysis for every NBA game. See which factors impact outcomes and understand the reasoning behind the numbers.
The NBA model is built around pace-adjusted efficiency: offensive and defensive ratings per 100 possessions capture team quality better than raw points. Beyond that, back-to-back fatigue is the NBA's most underpriced factor — teams on the second night of a back-to-back win roughly 8 percentage points less often than expected. The model also accounts for rest-day asymmetry, travel distance and direction, net rating trends over the last 10 games, and starting lineup changes from injury reports. During the playoffs, seeding and home-court advantage receive extra weight because crowd effects are amplified in elimination settings. Probabilities are updated when lineups are confirmed (usually 90 minutes before tip-off).
Today's Games
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82 games. Hundreds of variables. We break down what matters: rest days, efficiency, injuries.
Key Factors in NBA Analysis
What our model considers for predictions
Offensive & Defensive Efficiency
Points per 100 possessions, pace, and net rating measuring team performance
Rest Days & Schedule
Teams on back-to-backs face significant disadvantages
Injury Impact
Key player availability impacts win probability
Home Field Advantage
Playing at home provides a measurable advantage
Head-to-Head History
Historical matchup results between teams