Vaibhav G Arora

Vaibhav G Arora IPL journey showcases a promising right-arm fast bowler who made waves with his ability to swing the new ball and nail yorkers at the death. Bursting onto the scene with Kolkata Knight Riders, Arora quickly became a vital cog in their pace attack, delivering breakthroughs in the PowerPlay and tightening the screws in the slog overs. His tall frame and high-arm action generate disconcerting bounce, while clever changes of pace keep batters guessing. Under the Eden Gardens lights, Arora has produced memorable spells against top-order heavyweights, demonstrating calm under pressure. Later, representing Punjab Kings, he continued refining his craft, adding subtle variations that make him a reliable option on both pacy and slow Indian tracks. Always eager to learn, the Himachal Pradesh seamer spends hours analysing match-ups and honing skills that translate into clutch overs. With each passing season, Vaibhav G Arora’s IPL contributions underline his growth as a pace-bowling prospect who can swing momentum in a single over, making him a name to watch in future auctions.

Vaibhav G Arora has quietly built a potent four-season IPL résumé as a strike bowler for Kolkata Knight Riders. Since debuting with Punjab Kings in 2022 and moving to KKR the same year, the 6'4" right-arm pacer has featured in 32 innings, rattling 36 wickets at an impressive strike rate of 17.7. His economy of 9.55 shows he is willing to trade a few runs for breakthroughs, and the plan works—Arora has collected three three-wicket hauls, including a best of 3 for 22. In the 2025 season he continues to be Eoin Morgan’s go-to enforcer, bowling 638 balls and conceding 1,016 runs while setting up games in the powerplay and at the death. With the bat Arora remains a rare sight; across nine brief innings he has managed only nine runs from 24 balls without a single boundary. The story is clear: Vaibhav G Arora is a specialist bowler whose wicket-taking knack keeps KKR’s attack among the league’s most feared.

Note: This overview is partially generated using AI and is based on statistical data.