Per 82 GP	2026-27projection adj	2025-2681 GP	H239 GP	H142 GP	Prev 3238 GP · 3y
TOI	20.50	20.88	19.81	20.02	18.95
PP TOI	0.11	0.09	0.11	0.07	0.18
G	5	2	2	2	8
A	18	20	20	21	13
PTS	23	22	22	23	22
PPP	0	0	0	0	0
SOG	108	107	123	92	112
PIM	▲145	154	85	218	117
Hits	200	198	196	201	196
Blocks	▲98	103	79	126	84

Sample: 81 GP · 1,391 5v5 min (2025-26) — how much ice time backs these rates

Positional rankingDefense · league-wide (of 303)

27Shayne Gostisbehere62

28Rasmus Andersson61

29Neal Pionk60

30Nikita Zadorov59

31Noah Dobson57

32Thomas Chabot57

33Brock Faber55

offenseperipheralsvalue over replacement

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.

Context-adjusted (▲/▼ vs the rate-model baseline): Enforcer PIM over-regressed: the engine hedges the majors/fights component hard as noise, dropping him to 122 PIM — below even his 3-yr ~148 pace. But his PIM has held 5.2-5.4/60 (all) for 3 straight years, a durable role. Set 145 (3-yr level, light hedge under last year). Blocks are RISING (2.7->3.85/60) as a shot-blocking role stat, yet projected 89 (below his ~99-101 pace); set 98. Role/style stats persist like HITS — the 3-yr hedge over-reverts them.

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 68% below his 3-year rate last season (2.27 against 7.17).

Second-half fade

PIM

all5v5

Penalty minutes ran at a 85 pace in the second half after 218 in the first, per 82 games.

Second-half surge

SOG/60

SOG/60 finished the year 43% above where it started (3.29 in the first half, 4.70 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 Defense

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

Jeremy LauzonD · Vegas Golden Knights89% match
shared: Hits, PIM
Josh MansonD · Colorado Avalanche89% match
shared: Hits, PIM
Maveric LamoureuxD · Utah Mammoth87% match
shared: PIM, Hits
Brenden DillonD · New Jersey Devils87% match
shared: Hits, PIM

Complementary Defense

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

Cale MakarD · Colorado Avalanchecovers 3
fills: A, PPP, SOG
Zach WerenskiD · Columbus Blue Jacketscovers 3
fills: SOG, A, PPP
Quinn HughesD · Minnesota Wildcovers 3
fills: A, PPP, SOG
Evan BouchardD · Edmonton Oilerscovers 3
fills: A, PPP, SOG

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 · Marco Sturm (BOS)

Last year: Marco Sturm full season (1st yr) — no change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	20.50	20.88	18.95	+10%
5v5 TOI	16.91	17.18	16.22	+6%
PP TOI	0.11	0.09	0.18	-49%

By quarter — 2025-26 vs 3-yr baseline

GP 22 · 20 · 20 · 19

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 → 20.50: holds last year's role
5v5 TOI → 16.91: holds last year's role
PP TOI → 0.11: same coach (Marco Sturm) — carries the elevated finish (2nd half 0.1, Q4 0.1) over the full-year 0.1

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	4.05	3.97	4.50	-12%
G/60	0.12	0.09	0.32	-72%
iSH%	5.70	2.27	7.17	-68%
ixG/60	–	0.14	0.19	-27%
iCF/60	–	9.96	11.22	-11%
iSCF/60	–	2.33	2.97	-22%
iHDCF/60	–	0.17	0.36	-52%

By quarter — 2025-26 vs 3-yr baseline

GP 22 · 20 · 20 · 19

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)

ContextFinishing looks earned: iSH% 2.3% sits near the 7.2% 3-yr mark with 5v5 ixG/60 0.14 (11th pct league-wide) — goals held close to last year.

RiskShot volume down 12% (5v5 SOG/60 3.97 vs 4.50) — volume is the repeatable half, so this caps the goal ceiling.

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%	9.43	9.98	8.47	+18%
IPP	31.66	31.18	32.92	-5%
1A/60	0.34	0.39	0.28	+39%
2A/60	0.30	0.34	0.22	+56%

By quarter — 2025-26 vs 3-yr baseline

GP 22 · 20 · 20 · 19

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% 10.0%, IPP 31.2%).

RiskAssist gain leans on secondary helpers (2A/60 0.34 vs 3-yr 0.22) — the least repeatable slice; projected back toward baseline.

ContextDefenseman — weight transition/PP facilitation over raw 2A; secondary assists read a touch better for D than forwards.

Power play

PP opportunity and finishing — modelled separately from 5v5.

Metric	26-27 proj	2025-26	Prev 3	Diff
PP TOI	0.11	0.09	0.18	-49%
PP iSH%	–	n/a	0.00
PP SOG/60	2.08	0.00	8.31	-100%
PP ixG/60	–	1.09	0.36	+201%

By quarter — 2025-26 vs 3-yr baseline

GP 22 · 20 · 20 · 19

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: 0.1→0.1 PP TOI/gp (same coach (Marco Sturm) — carries the elevated finish (2nd half 0.1, Q4 0.1) over the full-year 0.1) — 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	4.83	6.17	4.87	+27%
Hits/60	7.70	7.46	8.07	-8%
Blks/60	3.11	3.62	3.05	+19%

By quarter — 2025-26 vs 3-yr baseline

GP 22 · 20 · 20 · 19

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)

ContextHits role-stable at 7.46/60 (77th pct league-wide) → 7.70 projected.

RiskBlocks tailing off: Q4 2.80/60 and 2nd-half 2.62 below the 3.62 season rate — projected DOWN to 3.11/60, weighting the recent decline over the 3.05 3-yr mark.

TailwindFights / takes majors (0.22/60) — a real PIM source, valuable in banger and PIM formats.