Counts = projected deployment × projected /60 rate, per 82 GP. Rates regress off the process metric (ixG, shot-driving), not last year's finishing %. PP points = projected PP rate (anchored on the 2nd-half PP1 role, finishing regressed) × projected PP TOI.

Metrics worth highlighting

The charts that move this projection — where he broke from his own 3-year rate, where the season split in half, and where we’re taking the number next year

Below his 3-year rate

iSH%

iSH% ran 71% below his 3-year rate last season (5.69 against 19.48).

Second-half fade

HITS

all5v5

Hits ran at a 271 pace in the second half after 425 in the first, per 82 games.

Second-half surge

PIMs/60

PIMs/60 finished the year 82% above where it started (0.82 in the first half, 1.49 in the second). The projection leans on how the season ended, so the second half counts for more.

Picked automatically from every chart on this card, ranked by how far each number moved. Each claim is measured off the chart drawn beside it.

Similar & complementary players

Similar makeup Forward

Closest across all seven categories — match % is the whole-profile fit

Emil HeinemanLW,RW · New York Islanders91% match
shared: Hits, Blocks
Yakov TreninLW,RW · Minnesota Wild80% match
shared: Hits
Mackie SamoskevichLW,RW · Seattle Kraken79% match
shared: Hits
Lawson CrouseLW,RW · Utah Mammoth78% match
shared: Hits, Blocks

Complementary Forward

Same position, opposite profile — strong where Marc Gatcomb is weak or average, light where he’s strong

Clayton KellerLW · Utah Mammothcovers 4
fills: PPP, A, SOG, G
Jack HughesC,LW · New Jersey Devilscovers 4
fills: SOG, PPP, A, G
Nikita KucherovRW · Tampa Bay Lightningcovers 5
fills: A, PPP, G, SOG
Artemi PanarinLW · Los Angeles Kingscovers 4
fills: A, PPP, SOG, G

Profile shape — per-82 category values vs the league p99 for the position (same scale as the hero bars)

This player

the profile below

vs Similar

similar players hug the shape

vs Complementary

complements fill the gaps

Deployment

Deployment projection — next-year TOI & PP TOI vs the last two years (the role that drives every count)

Coaching

2026-27 · Ryan Craig (VGK) new voice

Last year (NYI, traded): Patrick Roy Q1-Q4 → Peter DeBoer final 4 games · Q4 — in-season change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	10.02	10.09	9.79	+3%
5v5 TOI	9.86	9.98	9.68	+3%
PP TOI	0.03	0.03	0.07	-58%

By quarter — 2025-26 vs 3-yr baseline

GP 1 · 14 · 20 · 14

TOI*

5v5 TOI

PP TOI

*Total TOI by quarter reconstructs 5v5+PP quarterly totals plus a held-flat season PK/GP — NST has no all-strength quarterly export. Level is accurate; quarter-to-quarter movement comes from 5v5+PP.

By season — year over year

TOI

5v5 TOI

PP TOI

TOI → 10.02: holds last year's role
5v5 TOI → 9.86: holds last year's role
PP TOI → 0.03: role tapered late (Q4 0.0 vs 0.0 full-year) — projected toward the softer finish

Shooting — volume & conversion

How much and how well he shoots — volume (SOG), finishing (% vs chance quality), and the individual shot-quality funnel (iCF ⊇ iSCF ⊇ iHDCF).

Metric (5v5)	26-27 proj	2025-26	Prev 3	Diff
SOG/60	6.50	6.50	6.52	-0%
G/60	0.50	0.37	1.27	-71%
iSH%	13.69	5.69	19.48	-71%
ixG/60	–	0.71	0.73	-3%
iCF/60	–	11.29	11.76	-4%
iSCF/60	–	6.01	7.31	-18%
iHDCF/60	–	3.80	4.13	-8%

By quarter — 2025-26 vs 3-yr baseline

GP 1 · 14 · 20 · 14

SOG/60

iSH%

ixG/60

iCF/60

iSCF/60

iHDCF/60

By season — year over year

SOG/60

iSH%

ixG/60

iCF/60

iSCF/60

iHDCF/60

Per-82 count — 3 seasons, 2025-26 halves & 26-27 projection

all5v5

SOG

all5v5

The blue 26-27 point is our projection. The bold line is all situations; the muted line under it is 5v5 alone, so the gap between them is his special-teams production. Full seasons are true per-82 counts; the 2025-26 H1/H2 reconstruct all-strength from the 5v5+PP quarterly exports plus the season's held-flat PK/other. The projected 5v5 point is the engine's even-strength share of the total, converted to 5v5 by his own 5v5-to-even-strength split, so overtime and 4-on-4 scoring stays out of it.

Regression read — where next year's /60 rate lands and why (process over finishing)

TailwindGoals projected UP: iSH% cratered to 5.7% vs 19.5% 3-yr while 5v5 ixG/60 0.71 (62nd pct league-wide) held/rose — the chances say the finishing rebounds toward 13.7%, lifting the goal rate ~35%.

Assists — playmaking & on-ice offense

Primary vs secondary helpers, plus the on-ice offense and luck signals underneath them.

Metric (5v5)	26-27 proj	2025-26	Prev 3	Diff
on-ice SH%	7.10	5.64	9.48	-40%
IPP	63.89	63.70	64.13	-1%
1A/60	0.07	0.12	0.00
2A/60	0.23	0.37	0.16	+131%

By quarter — 2025-26 vs 3-yr baseline

GP 1 · 14 · 20 · 14

1A/60

2A/60

By season — year over year

1A/60

2A/60

Per-82 count — 3 seasons, 2025-26 halves & 26-27 projection

all5v5

PTS

all5v5

Regression read — where next year's /60 rate lands and why (process over finishing)

ContextAssist environment looks normal (on-ice SH% 5.6%, IPP 63.7%).

RiskAssist gain leans on secondary helpers (2A/60 0.37 vs 3-yr 0.16) — the least repeatable slice; projected back toward baseline.

Power play

PP opportunity and finishing — modelled separately from 5v5.

Metric	26-27 proj	2025-26	Prev 3	Diff
PP TOI	0.03	0.03	0.07	-58%
PP iSH%	0.00	0.00	n/a
PP SOG/60	56.13	90.00	0.00
PP ixG/60	–	34.08	0.00

By quarter — 2025-26 vs 3-yr baseline

GP 1 · 14 · 20 · 14

PP TOI/GP

PP SOG/60

PP ixG/60

By season — year over year

PP TOI/GP

PP SOG/60

PP ixG/60

Per-82 count — 3 seasons, 2025-26 halves & 26-27 projection

PPP

PPG

PPA

The blue 26-27 point is our projection. PPG and PPA are the 2 halves of the PPP above them, split by the projection's own goal/assist mix. PP-only, so the halves are exact.

Regression read — where next year's /60 rate lands and why (process over finishing)

TailwindPP role projected up: 0.0→0.0 PP TOI/gp (role tapered late (Q4 0.0 vs 0.0 full-year) — projected toward the softer finish) — the biggest PPP lever.

Physical — PIM · hits · blocks

Peripheral counting categories. Noisier and scorer-biased — read as role over the years, not pure talent.

Metric (5v5)	26-27 proj	2025-26	Prev 3	Diff
PIMs/60	1.48	1.23	1.75	-30%
Hits/60	23.00	23.31	23.68	-2%
Blks/60	3.08	2.94	3.66	-20%

By quarter — 2025-26 vs 3-yr baseline

GP 1 · 14 · 20 · 14

PIMs/60

Hits/60

Blks/60

By season — year over year

PIMs/60

Hits/60

Blks/60

Per-82 count — 3 seasons, 2025-26 halves & 26-27 projection

PIM

all5v5

HITS

all5v5

BLK

all5v5

Regression read — where next year's /60 rate lands and why (process over finishing)

RiskHits tailing off: Q4 19.28/60 and 2nd-half 19.80 below the 23.31 season rate — projected DOWN to 23.00/60, weighting the recent decline over the 23.68 3-yr mark.

RiskBlocks tailing off: Q4 1.79/60 and 2nd-half 2.54 below the 2.94 season rate — projected DOWN to 3.08/60, weighting the recent decline over the 3.66 3-yr mark.