Mohit Sharma
Mohit Sharma - Bowling By Season
Bowling Summary
- Wickets134
- Best In Match5
- Strike Rate17.93
- Economy8.77
Wickets Per Season
| Season | Inn | Wickets | Balls | Runs | SR | Eco | 3W | 4W | 5W |
|---|---|---|---|---|---|---|---|---|---|
| 2025 | 8 | 2 | 150 | 257 | 75 | 10.2800 | 0 | 0 | 0 |
| 2024 | 11 | 13 | 234 | 425 | 18 | 10.8974 | 2 | 0 | 0 |
| 2023 | 14 | 27 | 265 | 361 | 9 | 8.1736 | 1 | 2 | 1 |
| 2020 | 1 | 1 | 24 | 45 | 24 | 11.2500 | 0 | 0 | 0 |
| 2019 | 1 | 1 | 18 | 27 | 18 | 9.0000 | 0 | 0 | 0 |
| 2018 | 9 | 7 | 178 | 322 | 25 | 10.8539 | 0 | 0 | 0 |
| 2017 | 14 | 13 | 274 | 410 | 21 | 8.9781 | 0 | 0 | 0 |
| 2016 | 14 | 13 | 291 | 407 | 22 | 8.3918 | 3 | 0 | 0 |
| 2015 | 16 | 14 | 342 | 481 | 24 | 8.4386 | 1 | 0 | 0 |
| 2014 | 16 | 23 | 323 | 452 | 14 | 8.3963 | 3 | 1 | 0 |
| 2013 | 15 | 20 | 304 | 326 | 15 | 6.4342 | 2 | 0 | 0 |
Mohit Sharma - Batting By Season
Batting Summary
- Runs125
- Highest Score21
- Fifties0
- Hundreds0
- Fours8
- Sixes4
- Strike Rate91
Runs Per Season
| Season | Inn | Runs | Highest | SR | 4s | 6s | 50s | 100s |
|---|---|---|---|---|---|---|---|---|
| 2025 | 2 | 1 | 1 | 33 | 0 | 0 | 0 | 0 |
| 2024 | 2 | 2 | 2 | 13 | 0 | 0 | 0 | 0 |
| 2023 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2019 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2018 | 4 | 10 | 4 | 76 | 1 | 0 | 0 | 0 |
| 2017 | 7 | 51 | 13 | 102 | 3 | 1 | 0 | 0 |
| 2016 | 5 | 32 | 15 | 123 | 3 | 1 | 0 | 0 |
| 2015 | 5 | 28 | 21 | 155 | 1 | 2 | 0 | 0 |
| 2014 | 1 | 1 | 1 | 33 | 0 | 0 | 0 | 0 |
| 2013 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Mohit Sharma - IPL Career Overview
Mohit Sharma IPL career summary Fast-medium bowler Mohit Sharma became an IPL household name through his uncanny control over cutters and deceptive slower balls. Rising with Chennai Super Kings, he showcased remarkable death-over composure, often turning matches in the final overs. Later, when he moved to Kings XI Punjab, he continued to trouble batters with disciplined lines and subtle changes of pace. A brief but influential return to CSK reinforced his reputation as a reliable pressure bowler. Across seasons, Mohit has been entrusted to defend tight totals and break partnerships, roles he has fulfilled with calm assurance. His knack for reading pitches and altering lengths on the fly has made him a go-to option in crunch situations. Fantasy managers and fans value him for consistent wicket-taking bursts and economy in high-scoring games. Whether operating in the powerplay or the slog overs, Mohit Sharma remains one of the IPL’s most respected pace strategists.
Mohit Sharma has been one of the IPL’s canniest pace operators for over a decade, and the numbers behind his 134-wicket haul tell a tale of sustained mastery. Operating in 119 bowling innings across 11 seasons, the Haryana seamer has attacked the stumps at a rapid strike-rate of 17.93 balls per wicket, while keeping a tight leash on batters with an economy of 8.77. His standout show includes 15 three-wicket bursts and one five-for, the best being a 5-wicket demolition job that underlined his knack for breaking partnerships at will. From his breakout year with Chennai Super Kings in 2013 to his recent return to Delhi Capitals for IPL 2025, Mohit’s journey maps the evolution of a bowler who adapts and endures. After CSK, he spun his web for Kings XI Punjab, returned to CSK, then donned the Delhi jersey in 2020 before a two-season revival at Gujarat Titans in 2023-24. Each shift brought new challenges; each challenge saw him refine the back-of-the-length cutters and knuckle balls that once made him MS Dhoni’s go-to Powerplay enforcer. With 2,403 balls and 3,513 runs conceded, his ledger shows both volume and value, proving that containment and strike power can indeed coexist. While his batting remains a cameo option—125 runs at a strike-rate of 91—his primary currency is wickets, and he’s spent 11 seasons cashing in. As IPL 2025 dawns in Delhi colours once again, expect Mohit Sharma to keep the middle overs quiet and the scoreboard moving in the only way he knows: one wicket at a time.
Note: This overview is partially generated using AI and is based on statistical data.