How SportGod AI predicts match outcomes

Every ball, every over, every wicket — SportGod AI processes live cricket data in real time and turns it into win probability, tactical insights and match predictions. Here is how it works.

The data layer

Our data pipeline starts with Sportmonks, a professional cricket data provider that delivers ball-by-ball events within seconds of each delivery. Each ball event includes the runs scored, dismissal type, batsman and bowler identity, fielding positions, wagon wheel coordinates, and more. This stream is the foundation of every prediction we make.

Win probability model

Win probability is calculated by a gradient-boosted model trained on approximately 14,000 completed T20 matches across 12 years of IPL, international T20, and major T20 leagues worldwide. At any point in a match, the model considers:

• Current score vs par score — what has historically been scored at this stage on this ground in this run-rate context
• Wickets in hand — each wicket lost changes the distribution of outcomes significantly
• Partnership momentum — the last 12-ball scoring rate of the current partnership
• Bowler matchups — historical data on how each bowler performs against the current batsman's playing style
• Venue factors — ground dimensions, pitch report, dew probability, and average second-innings win rate

The model outputs a probability for each team winning, updated within 800ms of each ball being delivered.

Claude AI analysis layer

Win probability is just a number. We use Claude (Anthropic's AI) to turn that number into language — explaining why the probability shifted, what tactical options each team has, and what the key moments of the match have been. When Bumrah concedes a six in the 19th over and the probability swings from 68% to 51%, Claude will tell you exactly what that means for the game state and what the bowling team should do next.

Prediction games

The same model powers the PREDICT game mode. When you make a prediction — "MI to win", "Under 160 runs total", "Kohli to be top scorer" — our system evaluates your call against the current model output and assigns a confidence-adjusted score. High-confidence correct predictions earn more SG Coins. Predicting against the model when it is highly certain one way earns the most.

Accuracy and honesty

No cricket prediction model is perfect. T20 cricket is inherently volatile — a single over can swing a match from 85% certainty to a coin flip. Our model is calibrated to be well-rounded rather than overconfident; we measure Brier score and log-loss across test sets from each season. Current calibration: when the model says 80% win probability, the favoured team wins approximately 78% of the time in validation data.

We publish our methodology openly because we believe transparency builds trust. If you want to discuss the model in detail, reach out at hello@sportgod.ai.