Per 82 GP	2026-27projection	2025-2678 GP	H235 GP	H143 GP	Prev 3220 GP · 3y
TOI	22.14	22.01	20.22	21.92	22.66
PP TOI	1.81	1.94	1.78	2.06	2.11
G	9	17	13	20	6
A	27	25	29	22	35
PTS	36	42	42	43	42
PPP	8	9	5	13	11
SOG	153	156	152	159	168
PIM	38	44	30	55	38
Hits	79	74	81	68	102
Blocks	125	139	116	158	122

Sample: 78 GP · 1,382 5v5 min (2025-26) — how much ice time backs these rates

Positional rankingDefense · league-wide (of 303)

46Morgan Rielly32

47Aaron Ekblad32

48Alexander Romanov31

49Justin Faulk30

50Kaiden Guhle30

51Jake Walman30

52K'Andre Miller30

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

PPP

Power play points ran at a 5 pace in the second half after 13 in the first, per 82 games.

We project it down

all5v5

We’re projecting goals 47% below last season, 17 to 9.

Second-half fade

PIM

all5v5

Penalty minutes ran at a 30 pace in the second half after 55 in the first, per 82 games.

Below his 3-year rate

1A/60

1A/60 ran 29% below his 3-year rate last season (0.30 against 0.42).

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

Thomas ChabotD · Ottawa Senators87% match
shared: SOG, Blocks, G
Mike MathesonD · Montreal Canadiens87% match
shared: Blocks, G
Kris LetangD · Pittsburgh Penguins87% match
shared: SOG
Sean DurziD · New York Rangers84% match

Complementary Defense

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

Quinn HughesD · Minnesota Wildcovers 3
fills: A, PPP, SOG
Cale MakarD · Colorado Avalanchecovers 3
fills: A, PPP, SOG
Evan BouchardD · Edmonton Oilerscovers 3
fills: A, PPP, SOG
Erik KarlssonD · Pittsburgh Penguinscovers 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 · Todd McLellan (DET)

Last year (STL, traded): Todd McLellan DET · pre-trade → Jim Montgomery STL · acquired mid-season (small sample) — in-season change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	22.14	22.01	22.66	-3%
5v5 TOI	17.67	17.72	18.00	-2%
PP TOI	1.81	1.94	2.11	-8%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 22 · 19 · 16

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 → 22.14: holds last year's role
5v5 TOI → 17.67: established top role held near 17.7 — the late dip (Q4 17.2) reads mostly as rest / season wear, not lost usage
PP TOI → 1.81: role tapered late (Q4 1.1 vs 1.9 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	4.55	4.69	5.14	-9%
G/60	0.40	0.56	0.15	+265%
iSH%	7.46	11.94	2.98	+300%
ixG/60	–	0.24	0.23	+4%
iCF/60	–	10.42	10.54	-1%
iSCF/60	–	2.43	3.06	-21%
iHDCF/60	–	0.69	0.58	+19%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 22 · 19 · 16

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 0.24 (28th pct league-wide) up on the 3-yr 0.23 — the shot quality is real, so the projected goal rate leans on chances, not a hot %.

TailwindTrajectory: 5v5 ixG/60 climbed 0.22→0.27 across the year — process trending the right way into next season.

RiskAge 34 — modest past-prime drag on scoring rates.

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%	8.93	9.27	8.35	+11%
IPP	43.69	44.86	41.66	+8%
1A/60	0.31	0.30	0.42	-29%
2A/60	0.31	0.22	0.41	-46%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 22 · 19 · 16

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% 9.3%, IPP 44.9%).

TailwindHigh-danger setups up (iHDCF/60 0.69 vs 0.58) — the dangerous chances that turn into primary assists are trending up.

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	1.81	1.94	2.11	-8%
PP iSH%	6.28	7.96	5.75	+38%
PP SOG/60	9.58	9.93	9.06	+10%
PP ixG/60	–	0.91	0.94	-4%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 22 · 19 · 16

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)

ContextPP role steady at ~1.8 PP TOI/gp.

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	1.27	1.48	1.38	+7%
Hits/60	3.10	2.86	3.87	-26%
Blks/60	4.65	5.03	4.15	+21%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 22 · 19 · 16

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)

TailwindHits surging late: Q4 3.27/60 and 2nd-half 3.24 vs a 2.86 season rate (3.87 3-yr) (37th pct league-wide) — reads as a real role/confidence step, so projected UP to 3.10/60, weighting the finish over the 3-yr baseline.

RiskBlocks tailing off: Q4 4.80/60 and 2nd-half 4.29 below the 5.03 season rate — projected DOWN to 4.65/60, weighting the recent decline over the 4.15 3-yr mark.