Per 82 GP	2026-27projection	2025-2661 GP	H230 GP	H131 GP	Prev 396 GP · 2y
TOI	17.20	16.80	15.28	17.61	19.41
PP TOI	0.15	1.43	1.04	2.21	1.15
G	5	11	10	12	7
A	14	22	11	32	19
PTS	19	32	20	44	26
PPP	1	9	0	19	9
SOG	89	97	86	107	115
PIM	24	14	8	19	34
Hits	76	74	83	65	97
Blocks	83	79	76	82	102

Sample: 61 GP · 824 5v5 min (2025-26) — how much ice time backs these rates

Positional rankingDefense · league-wide (of 303)

231Matt Grzelcyk-37

232Henri Jokiharju-37

233Jordan Oesterle-37

234Nick Blankenburg-37

235Ben Hutton-38

236Victor Mancini-38

237Jordan Harris-38

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): 7th-D power-play carryover trimmed (1.22 -> 0.15 PP TOI), removing ~8 phantom PP points. He sits 6th on the COL blue line and appears on neither external projection set; the engine was pricing him at a better PP rate than Kadri.

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

Second-half surge

iSH%

iSH% finished the year 150% above where it started (3.30 in the first half, 11.16 in the second). The projection leans on how the season ended, so the second half counts for more.

Second-half fade

all5v5

Assists ran at a 11 pace in the second half after 32 in the first, per 82 games.

We project it down

all5v5

We’re projecting goals 55% below last season, 11 to 5.

Above his 3-year rate

PP SOG/60

PP SOG/60 ran 38% above his 3-year rate last season (8.25 against 6.00).

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

Alexander NikishinD · Carolina Hurricanes84% match
Rasmus RistolainenD · Philadelphia Flyers84% match
Vladislav GavrikovD · New York Rangers81% match
Dmitry OrlovD · San Jose Sharks80% match

Complementary Defense

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

Quinn HughesD · Minnesota Wildcovers 2
fills: A, SOG
Rasmus DahlinD · Buffalo Sabrescovers 3
fills: A, PIM, SOG
Zach WerenskiD · Columbus Blue Jacketscovers 2
fills: SOG, A
Erik KarlssonD · Pittsburgh Penguinscovers 2
fills: A, 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 · Jared Bednar (COL)

Last year (NSH, traded): Jared Bednar COL · pre-trade → Andrew Brunette NSH · acquired mid-season (small sample) — in-season change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	17.20	16.80	19.41	-13%
5v5 TOI	13.42	13.51	15.71	-14%
PP TOI	0.15	1.43	1.15	+25%

By quarter — 2025-26 vs 3-yr baseline

GP 10 · 21 · 18 · 12

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 → 17.20: holds last year's role
5v5 TOI → 13.42: role tapered late (Q4 11.9 vs 13.5 full-year) — projected toward the softer finish
PP TOI → 0.15: phantom power-play carryover, same pattern as the Nicolas Roy fix on this roster. The engine carried 1.22 PP TOI and turned it into 8 PPP - a 4.80 PP pts/60 rate, HIGHER than what we project for Kadri or Nelson - for a defenseman who is 6th on the COL depth chart behind Makar, Toews, Malinski, Burns and Kulak. He does not appear on either external COL roster at all. Colorado's actual PP2 back end is Toews / Burns / Malinski; there is no version of this depth chart where he sees a real unit. Trimmed to spot duty, which removes the phantom PPP.

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	3.79	3.71	4.42	-16%
G/60	0.23	0.29	0.20	+46%
iSH%	6.16	7.82	4.51	+73%
ixG/60	–	0.27	0.25	+6%
iCF/60	–	11.36	10.06	+13%
iSCF/60	–	3.20	3.50	-9%
iHDCF/60	–	0.87	0.87	-0%

By quarter — 2025-26 vs 3-yr baseline

GP 10 · 21 · 18 · 12

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)

TailwindProcess rising: 5v5 ixG/60 0.27 (31st pct league-wide) up on the 3-yr 0.25 — the shot quality is real, so the projected goal rate leans on chances, not a hot %.

RiskShot volume down 16% (5v5 SOG/60 3.71 vs 4.42) — volume is the repeatable half, so this caps the goal ceiling.

TailwindTrajectory: 5v5 ixG/60 climbed 0.26→0.33 across the year — process trending the right way into next season.

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%	7.80	7.74	8.06	-4%
IPP	41.76	46.79	28.17	+66%
1A/60	0.32	0.44	0.20	+121%
2A/60	0.27	0.29	0.24	+20%

By quarter — 2025-26 vs 3-yr baseline

GP 10 · 21 · 18 · 12

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)

RiskIPP spiked to 46.8% vs 28.2% 3-yr — point participation this far above baseline rarely holds; assist share likely gives a little back.

TailwindShot-driving up (5v5 iCF/60 11.36 vs 10.06) — real creation underneath, so don't over-regress the helpers.

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	0.15	1.43	1.15	+25%
PP iSH%	15.15	24.97	9.04	+176%
PP SOG/60	4.77	8.25	6.00	+38%
PP ixG/60	–	1.19	0.52	+128%

By quarter — 2025-26 vs 3-yr baseline

GP 10 · 21 · 18 · 12

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)

RiskPP role projected down: 1.4→0.1 PP TOI/gp (phantom power-play carryover, same pattern as the Nicolas Roy fix on this roster. The engine carried 1.22 PP TOI and turned it into 8 PPP - a 4.80 PP pts/60 rate, HIGHER than what we project for Kadri or Nelson - for a defenseman who is 6th on the COL depth chart behind Makar, Toews, Malinski, Burns and Kulak. He does not appear on either external COL roster at all. Colorado's actual PP2 back end is Toews / Burns / Malinski; there is no version of this depth chart where he sees a real unit. Trimmed to spot duty, which removes the phantom PPP.) — the biggest PPP lever.

TailwindPP chance quality up (PP ixG/60 1.19 vs 0.52) — a real process gain, the kind that sustains PP points.

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	0.56	0.58	1.19	-51%
Hits/60	3.65	3.57	3.78	-6%
Blks/60	3.82	3.79	3.86	-2%

By quarter — 2025-26 vs 3-yr baseline

GP 10 · 21 · 18 · 12

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 3.57/60 (44th pct league-wide) → 3.65 projected.

ContextBlocks role-stable at 3.79/60 (76th pct league-wide) → 3.82 projected.