Per 82 GP	2026-27projection	2025-2660 GP	H235 GP	H125 GP	Prev 3208 GP · 3y
TOI	18.50	18.10	18.41	16.81	20.67
PP TOI	0.13	0.09	0.12	0.06	0.93
G	3	4	0	10	5
A	22	22	21	22	26
PTS	25	26	21	32	31
PPP	0	0	0	0	4
SOG	85	56	40	78	113
PIM	21	31	49	6	16
Hits	47	29	25	34	80
Blocks	109	79	78	81	123

Sample: 60 GP · 1,003 5v5 min (2025-26) — how much ice time backs these rates

Positional rankingDefense · league-wide (of 303)

219Zach Bogosian-33

220Ty Emberson-33

221Cam Fowler-33

222Samuel Girard-33

223Henry Thrun-34

224Dmitri Simashev-34

225Brett Kulak-34

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.

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 fade

SOG/60

SOG/60 finished the year 54% below where it started (3.31 in the first half, 1.52 in the second). The projection leans on how the season ended, so the second half counts for more.

Second-half fade

Hits/60

Hits/60 finished the year 56% below where it started (1.98 in the first half, 0.86 in the second). The projection leans on how the season ended, so the second half counts for more.

We project it up

BLK

all5v5

We’re projecting blocks 38% above last season, 79 to 109.

Below his 3-year rate

1A/60

1A/60 ran 23% below his 3-year rate last season (0.30 against 0.39).

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

Rasmus RistolainenD · Philadelphia Flyers84% match
Owen PowerD · Buffalo Sabres81% match
Vladislav GavrikovD · New York Rangers78% match
Dmitry OrlovD · San Jose Sharks76% match

Complementary Defense

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

Rasmus DahlinD · Buffalo Sabrescovers 3
fills: PIM, SOG, PPP
Quinn HughesD · Minnesota Wildcovers 2
fills: PPP, SOG
Dougie HamiltonD · New Jersey Devilscovers 3
fills: SOG, PPP, PIM
Brandon MontourD · Seattle Krakencovers 2
fills: SOG, PIM

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 · Dan Muse (PIT)

Last year (PIT, traded): Jared Bednar COL · pre-trade → Dan Muse PIT · acquired mid-season (small sample) — in-season change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	18.50	18.10	20.67	-12%
5v5 TOI	17.30	16.72	17.53	-5%
PP TOI	0.13	0.09	0.93	-90%

By quarter — 2025-26 vs 3-yr baseline

GP 5 · 20 · 22 · 13

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 → 18.50: holds last year's role
5v5 TOI → 17.30: same coach (Dan Muse) — carries the elevated finish (2nd half 17.5, Q4 18.1) over the full-year 16.7
PP TOI → 0.13: same coach (Dan Muse) — 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	1.87	2.33	4.31	-46%
G/60	0.13	0.18	0.11	+60%
iSH%	4.15	7.73	2.61	+196%
ixG/60	–	0.12	0.17	-29%
iCF/60	–	8.43	10.38	-19%
iSCF/60	–	1.97	2.81	-30%
iHDCF/60	–	0.24	0.33	-27%

By quarter — 2025-26 vs 3-yr baseline

GP 5 · 20 · 22 · 13

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)

RiskGoals projected DOWN: iSH% ran hot at 7.7% vs a 2.6% 3-yr mark while 5v5 ixG/60 0.12 (7th pct league-wide) was flat — finishing, not process. Regressing iSH% toward 4.1% pulls the goal rate ~28% down.

RiskShot volume down 46% (5v5 SOG/60 2.33 vs 4.31) — volume is the repeatable half, so this caps the goal ceiling.

ContextTrajectory: 5v5 ixG/60 fell from 0.15 (1st half) to 0.10 (2nd).

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%	9.61	11.51	8.34	+38%
IPP	33.13	31.00	36.59	-15%
1A/60	0.35	0.30	0.39	-23%
2A/60	0.46	0.54	0.46	+17%

By quarter — 2025-26 vs 3-yr baseline

GP 5 · 20 · 22 · 13

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)

RiskOn-ice SH% hot at 11.5% vs a 8.3% 3-yr mark — teammate finishing regresses (~8% is league-normal), so some assists come off.

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	0.13	0.09	0.93	-90%
PP iSH%	–	n/a	9.94
PP SOG/60	0.62	0.00	3.09	-100%
PP ixG/60	–	0.00	0.44	-100%

By quarter — 2025-26 vs 3-yr baseline

GP 5 · 20 · 22 · 13

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 (Dan Muse) — 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	1.40	1.38	0.59	+133%
Hits/60	1.46	1.08	2.96	-64%
Blks/60	3.50	2.93	4.35	-33%

By quarter — 2025-26 vs 3-yr baseline

GP 5 · 20 · 22 · 13

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 0.76/60 and 2nd-half 0.86 below the 1.08 season rate — projected DOWN to 1.46/60, weighting the recent decline over the 2.96 3-yr mark.

ContextBlocks role-stable at 2.93/60 (61st pct league-wide) → 3.50 projected.

TailwindFights / takes majors (0.06/60) — a real PIM source, valuable in banger and PIM formats.