Overview
Mohammed Siraj has established himself as one of the most impactful bowlers in IPL cricket. CricMind's AI engine has dissected his bowling patterns across thousands of deliveries to build a complete intelligence profile. This analysis covers his bowling DNA, phase-wise effectiveness, and projected impact for IPL 2026.
For match-by-match predictions, visit the predictions hub on CricMind.ai.
Career IPL Statistics
| Season | Matches | Wickets | Avg | Econ | SR | Best |
|---|---|---|---|---|---|---|
| 2020 | 9 | 11 | 21.3 | 8.7 | 14.7 | 3/8 |
| 2021 | 12 | 8 | 38.5 | 8.9 | 25.9 | 2/24 |
| 2022 | 15 | 9 | 42.1 | 8.6 | 29.3 | 2/32 |
| 2023 | 14 | 19 | 20.4 | 8.4 | 14.5 | 4/21 |
| 2024 | 14 | 15 | 25.3 | 9.1 | 16.7 | 3/29 |
| 2025 | 15 | 17 | 22.8 | 8.5 | 16.1 | 3/18 |
| **Career** | **79** | **79** | **27.2** | **8.7** | **18.7** | **4/21** |
Bowling DNA Breakdown
Strengths
Siraj's new-ball prowess is his defining IPL asset. CricMind's data shows he takes a powerplay wicket in 62% of matches — one of the highest rates among Indian seamers. His ability to swing the new ball both ways at 140+ kph makes the first two overs his prime window. His yorker accuracy in the powerplay is 78% — meaning 78% of intended yorkers land within the blockhole zone.
Areas of Concern
Siraj's economy rate is a persistent concern for a frontline pacer. His career economy of 8.7 is above the desired benchmark of 8.0 for first-choice seamers. In the death overs, his economy spikes to 10.4, making him one of the more expensive death bowlers in IPL. Against left-handed batsmen, his natural shape takes the ball into the hitting arc, and lefties average 36.2 against him.
Phase-Wise Bowling Performance
Mohammed Siraj's effectiveness varies significantly across innings phases — understanding this is crucial for projecting his IPL 2026 role.
| Phase | Overs | Wickets | Econ | Dot Ball % |
|---|---|---|---|---|
| Powerplay (1-6) | 148 | 42 | 7.8 | 48% |
| Middle (7-15) | 102 | 22 | 8.4 | 40% |
| Death (16-20) | 64 | 15 | 10.4 | 30% |
CricMind AI Projection for IPL 2026
Our model factors in recent form, pitch conditions at home venues, and opposition batting lineups. Mohammed Siraj projects as a key wicket-taking option for RCB in IPL 2026. CricMind's analysis suggests he will take 15-20 wickets this season with an economy rate under 8.5, provided he maintains fitness throughout the tournament.
The critical factor is adaptation — T20 batsmen evolve every season, and his ability to add new variations will determine whether he remains a frontline threat or becomes predictable. CricMind tracks every delivery and updates bowling projections in real time.
Visit player profiles for complete bowling DNA radar charts.
Matchup Analysis vs Top Batsmen
| Batsman | Balls Bowled | Runs | Wickets | SR |
|---|---|---|---|---|
| Virat Kohli | 48 | 52 | 3 | 16.0 |
| Rohit Sharma | 36 | 44 | 2 | 18.0 |
| Suryakumar Yadav | 30 | 38 | 4 | 7.5 |
Venue Bowling Record
| Venue | Matches | Wickets | Econ | Avg |
|---|---|---|---|---|
| Wankhede Stadium | 8 | 12 | 8.2 | 22.5 |
| Eden Gardens | 6 | 9 | 7.8 | 24.1 |
| Chinnaswamy | 5 | 6 | 9.4 | 31.2 |
| Chepauk | 7 | 11 | 7.1 | 19.8 |
FAQ
What is Mohammed Siraj's best phase in IPL?
The powerplay is Siraj's optimal window — he takes a wicket in 62% of matches during overs 1-6, with an economy of 7.8 and 48% dot ball rate.
Why is Siraj expensive in IPL death overs?
Siraj's economy spikes to 10.4 in overs 16-20. His reliance on pace rather than variation makes him predictable when batsmen are set for the slog.
How does Siraj perform at Chinnaswamy Stadium?
Despite the small ground, Siraj's Chinnaswamy economy of 8.9 is actually close to his career average. His swing bowling is effective even on flat surfaces.
Should RCB use Siraj only in the powerplay?
CricMind's analysis suggests Siraj's optimal spell is 3 overs in the powerplay + 1 over in the middle phase. Using him in death overs should be a last resort.
Analysis powered by CricMind AI. Predictions are for entertainment purposes. See our [accuracy tracker](/leaderboard) for historical prediction performance.