Cricket Projections

Statz is an AI cricket prediction engine, not a tipster and not a chatbot guess. For each fixture the model plays the match out thousands of times from real ball-by-ball data, running two scenarios - one where the home side bats first, one where they chase - and averaging them into a single view until the toss is known. Out of that come the numbers on every card above: each team's win probability, the projected match total and first-innings score, projected sixes and fours, and the top projected players with their Dream11 points. Projections refresh through the day as team news and the toss are confirmed, so the picture you see is the current one, not a number written days ago.

The cricket stats behind our predictions

The predictions are only as good as the cricket stats feeding them, so the model leans on first-party data rather than opinion. Ground factors capture how each pitch actually plays - its recent first-innings average, how much it favours batting first, and how freely sixes and fours are hit - with recent matches weighted more heavily than old ones. On top of that sits each player's current form, their record at that specific venue, and the strength of the opposition attack they are up against. Rain-shortened and Duckworth-Lewis games are filtered out so a freak low score never drags an average down.

Who will win today's match?

Each card answers who will win today's match with a probability for both teams rather than a flat yes or no - plus the chance of a tie or no result where it applies. A side shown at 62% is the model's favourite, but the 38% underdog still wins roughly two times in five, which is exactly why a probability is more honest than a bald "banker" call. Read it as an edge, not a certainty. For tournament run-ins, our league probability simulator extends the same idea to who reaches the playoffs and lifts the trophy.

Cricket toss prediction

A true toss prediction is impossible - the coin has no memory - but the far more useful question is what the winning captain should do with it. That is where the venue data earns its keep: at grounds with dew or a used pitch, chasing wins far more often than batting first, and the bat-first win percentage on each fixture tells you how strong that bias is. Once the toss is called and the batting order is locked, the card stops averaging the two scenarios and shows only the one that is actually happening, so the win probability and projected totals sharpen up.

How accurate are our cricket predictions?

Straight answer: across 587 settled matches, the team our model favours before the toss has gone on to win 57.9% of the time, and our projected match totals typically land within about 40 runs of the real score. That is a genuine, measured edge - not the "100% sure" or "sure win" you will see promised elsewhere, which no honest cricket model can deliver. We would rather show you a real, measured number than a fake one. Every projection is checked against the actual result once the match finishes, and these figures update automatically as more matches settle.