Vipraj Nigam's raw WAR per match of 0.35 ranks among DC's highest. His batting WAR of 0.22 and bowling WAR of 0.30 combine to make him a genuine two-dimensional contributor. The catch: he has played only 13 T20 matches. His IPL confidence of 0.60 and 301 total T20 balls mean these numbers carry significant regression risk. The model projects him at 0.26 WAR/M after regression, which is still a strong number for a young spinner.

The model deploys Nigam as a New Ball bowler with 3 overs split 1 PP, 1 middle, and 1 death. That three-phase distribution is unusual for a spinner. His bowling role fit of 0.54 is moderate, reflecting raw numbers that show promise but inconsistency.

Bowling: The Death-Overs Edge

Nigam's death-overs bowling is where the model found the strongest signal. His death economy of 6.2 saves 4 runs per over compared to the 10.4 league average. His death dot ball rate of 36 percent and 2 death wickets across a small sample suggest real skill in that phase. His death bowling fit score of 0.83 is his strongest phase fit, higher than his New Ball assignment of 0.54.

The PP bowling numbers are less encouraging. His PP boundary rate of 27 percent is well above the 22 average. That leakage explains why the model limits his PP exposure to 1 over.

Bowling: Middle Overs

His middle-overs role score of 0.38 is his weakest. With Kuldeep and Axar dominating the middle phase, Nigam's 1 middle over is more of a flex option than a primary workload. The model essentially builds the bowling plan around Kuldeep's 3 middle overs and Axar's 2 middle overs, with Nigam filling gaps across all three phases.

His overall dot ball rate of 32 percent is below the 37 league average. His Ecae of 0.19 is marginal. The bowling surplus of 8 is positive but small. His value with the ball comes more from the death-overs specialization than from consistent containment.

Batting Contribution

Nigam's batting WAR of 0.22 is unusually high for a player listed as a bowler. With only 61 batting balls, the sample is tiny. The model regresses this heavily, but even the regressed number adds meaningful lineup value. He bats in a lower-order slot where any batting contribution is a bonus.

Sample Size Warning

Every number in this profile carries an asterisk. 301 T20 balls and 234 bowling balls produce noisy estimates. His raw WAR of 0.52 before IPL confidence adjustment was 0.52, nearly double the regressed figure. That gap tells you how much the model trusts small samples: it cuts the estimate roughly in half.

If Nigam's death bowling holds up across 14 IPL 2026 matches, his projected WAR will climb sharply for 2027. If the death numbers regress toward league average, he becomes a rotation bowler rather than a lineup fixture.

What This Means for IPL 2026

Nigam's three-phase bowling deployment gives Delhi Capitals tactical flexibility that few young spinners provide. His death-overs skill is the calling card. His batting upside is the bonus. His small sample is the risk. The model projects him at 0.26 WAR/M, enough to justify selection in the optimal XII. His xImpact of 44 reflects the uncertainty around a 13 match career. This is a bet on talent with a short track record, and the model thinks the odds favor DC.