SMAT Watch: Akash Vasisht — All-Rounder With 132 SR and 6.25 Economy in 2 Seasons
Akash Vasisht is a domestic all-rounder with 2 SMAT seasons and zero higher-level experience. His dual-skill profile is what makes him interesting to the model, even though the sample sizes are thin on both sides of the ball.
With the bat, Vasisht has scored 168 runs off 127 balls across 9 innings for a strike rate of 132. The average of 24 is modest. That SR sits below the IPL powerplay average of 152 but within range of the middle-overs mark of 145. He profiles as a middle-order contributor who can maintain tempo without being asked to anchor or blast.
The bowling side is more compelling. Across 118 balls, he has taken 7 wickets at 6 economy. A bowling strike rate of 17 balls per wicket is respectable. The economy sits 3 runs below the IPL 2025 middle-overs benchmark, which is the kind of margin that survives the domestic-to-IPL translation.
Combining both disciplines, the model projects 0.19 WAR/M for 2026 at low confidence with a rising trajectory. Both the batting (127) and bowling (118) samples are below the threshold where the model starts trusting individual estimates over population priors. The wide error bars on this projection mean Vasisht could be anywhere from a genuine IPL contributor to a domestic-only player.
The rising trajectory is the encouraging signal. It means his most recent SMAT output was stronger than his debut season, suggesting active improvement.
Indian all-rounders who can bat in the middle order and contribute 2 to 4 overs of containing bowling are the most roster-flexible players at any IPL auction. They solve the balance equation without consuming an overseas slot. If Vasisht can sustain these dual numbers over a full SMAT campaign, he would become a legitimate target for franchises seeking balance.
The risk is that 2 seasons is barely a signal. The reward is a domestic all-rounder at base price with upside on both sides of the ball.
All numbers from SMAT (Syed Mushtaq Ali Trophy) and domestic T20 career data.