How we predict a T20 match
Match prediction in T20 cricket is a probabilistic exercise, not a deterministic one. We give each match a win probability for each team, expressed as a percentage between 0 and 100. The probability is calculated from five inputs: venue history, recent form, head-to-head, dew rating, and toss outcome. Each input is weighted based on how predictive it has been historically.
Venue history gets the highest weight at 30% because IPL grounds are different enough that the same team performs very differently at each. Wankhede favors chasing teams. Chepauk favors batting first teams in the first half of the season and chasing teams in the second half due to dew. Chinnaswamy is a batting paradise that slightly favors the team batting first.
Recent form gets 25% weight. The last 5 matches of each team are evaluated for win-loss record, net run rate, batting depth, and bowling variety. A team that has won 4 of its last 5 with strong NRR is in form. A team that has won 2 of its last 5 with weak NRR is not.
Why venue beats head-to-head
Head-to-head history is tempting to use heavily because it's easy to look up. But in T20 cricket, head-to-head is the least predictive of the five inputs. Teams change their squads, their captains, their coaches, and their playing styles every auction. A head-to-head record from 2022 has very little bearing on a match in 2026.
Venue history is more predictive because the venue doesn't change. The pitch behavior at Chepauk in July 2026 will be similar to the pitch behavior at Chepauk in July 2024 and July 2022. The outfield dimensions, the dew pattern, the wind direction — these are stable inputs. We weight venue heavily because venue is the most stable input.
The exception is when a venue has been relaid. The Wankhede outfield was relaid in 2023 and the pitch behavior changed. Chepauk's pitch was changed to a different soil composition in 2024. We track these changes and adjust the venue weight accordingly.
The toss and dew
Dew rating is the most underrated input. A 7+ dew rating shifts the win probability by 8-12 percentage points.
The toss and dew
Toss outcome gets 10% weight, but only after the toss happens. Before the toss, we calculate two predictions: one assuming the team bats first, one assuming the team bats second. After the toss, we lock in the prediction based on the actual outcome.
Dew is a major factor in night matches. A heavy dew makes the ball slippery, which favors the team batting second because the ball comes onto the bat better. A dry pitch with no dew favors the team batting first because the ball grips and turns. We rate dew on a 0-10 scale based on meteorological data, ground reports, and historical patterns.
In July 2026, the dew rating for most night matches is 7-9. That strongly favors the team batting second. Our model adjusts the win probability by 8-12 percentage points based on dew. If the toss winner chooses to bat first on a high-dew night, our model gives them a lower win probability than the market expects.
Reading the prediction card
The prediction card shows the win probability for each team, plus the key inputs that drove the prediction. The card has three sections: the headline probability, the inputs breakdown, and the key risks.
The headline probability is shown as a horizontal bar split between the two teams. The bar is color-coded — the team with the higher probability is shown in mint green, the lower in ink. Below the bar is the actual percentage for each team, rounded to the nearest whole number.
The inputs breakdown shows the five inputs and their values for each team. For example, CSK at Chepauk might have a venue history of 65% wins, recent form of 60% wins, head-to-head of 55%, dew advantage of 40% (because they bat second), and toss probability of 50%. The model combines these into the headline probability.
When the model gets it wrong
T20 matches have inherent variance. Even a 75-25 favorite loses 1 in 4 matches. That's not a flaw in the model — that's the nature of the sport. A wet outfield, a brilliant individual innings, a freak catch — these things happen. We accept that our model will be wrong about 30-35% of the time.
The model is most accurate when the prediction is between 55-45 and 70-30. Outside that range, the model gets less accurate because the smaller sample of similar matches makes the probability estimate less reliable. A 90-10 prediction is often wrong because the 10% team has won before.
We don't recommend betting based on our predictions alone. We use the model for fantasy cricket decisions — captain picks, differential picks, lineup choices — where small probability shifts matter. For actual betting decisions, use a dedicated betting model with form, injury, and odds data.
Predictions for tonight's matches
Tonight we have two matches: CSK vs MI at Chepauk (7:30 PM) and RCB vs DC at Chinnaswamy (7:30 PM). The prediction for CSK vs MI is 54-46 in favor of CSK, with the model leaning on venue history (CSK has won 7 of their last 10 at Chepauk) and dew rating (high dew favors CSK's spin-heavy bowling if they bat second).
The prediction for RCB vs DC is 58-42 in favor of RCB, with the model leaning on recent form (RCB has won 4 of their last 5) and head-to-head (RCB has won 6 of their last 8 against DC at Chinnaswamy). The venue is slightly less predictive here because Chinnaswamy is a more neutral ground.
The predictions update after the toss. If CSK wins the toss and chooses to bat first on a high-dew night, our model shifts the prediction to 51-49 in favor of MI because MI's batting depth is better suited to a chase. If RCB wins the toss and chooses to bat first, our model shifts the prediction to 62-38 in favor of RCB because Chinnaswamy slightly favors the team batting first.
How to use predictions in your fantasy team
Predictions are useful for fantasy decisions because they tell you which team is likely to win. If CSK is favored 54-46, you should pick more CSK players than MI players in your lineup. The simplest application is the 60-40 rule: in a 5-5 split between two teams, weight your picks 3-2 in favor of the favored team.
Predictions are less useful for captain pick decisions. Captain pick is about which individual player will score the most fantasy points, not which team will win. A bowler from the losing team can still outscore a batter from the winning team if they take 4 wickets. Use predictions for team-level decisions and captain pick model for captain-level decisions.
Predictions update after the toss. If you have time to make lineup changes after the toss, check the updated prediction before you lock in your team. A 5-percentage-point shift in prediction after the toss is significant — it's worth a quick swap.