Per 82 GP	2026-27projection adj	2025-2672 GP	H239 GP	H133 GP	Prev 3233 GP · 3y
TOI	22.99	22.39	21.27	21.51	21.82
PP TOI	0.90	0.98	0.73	1.28	0.57
G	▲11	9	12	6	8
A	▲31	33	32	34	27
PTS	▲42	42	44	40	35
PPP	1	3	0	7	2
SOG	130	140	140	140	112
PIM	42	64	44	87	38
Hits	134	115	109	122	147
Blocks	113	90	87	93	113

Sample: 72 GP · 1,331 5v5 min (2025-26) — how much ice time backs these rates

Positional rankingDefense · league-wide (of 303)

49Justin Faulk30

50Kaiden Guhle30

51Jake Walman30

52K'Andre Miller30

53Luke Hughes27

54Thomas Harley26

55Connor Clifton26

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): Value is 5v5-driven (OZ-start jump, PDO regression -> G/A x1.12), not PP: his PP scoring rate collapsed to zero after Q1 and Nikishin took the PP2 QB minutes. PP TOI corrected 1.5 -> 0.9 (was a Q1 mirage). Stock-watch pegs a realistic 35-40 pt ceiling; ~1/3 of last year's growth was PIM-driven and the non-5v5 (3-on-3, empty-net) production is hard to replicate. Lands ~40.

Context brain — deployment, role, coaching & injury signals (why the line should move)

TailwindPositive luck regression plus offensive deployment; raise defenseman baseline.

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

PP TOI

PP TOI finished the year 46% below where it started (1.39 in the first half, 0.75 in the second). The projection leans on how the season ended, so the second half counts for more.

Second-half fade

PIM

all5v5

Penalty minutes ran at a 44 pace in the second half after 87 in the first, per 82 games.

We project it up

BLK

all5v5

We’re projecting blocks 26% above last season, 90 to 113.

We project it up

all5v5

We’re projecting goals 22% above last season, 9 to 11.

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

Kris LetangD · Pittsburgh Penguins87% match
shared: Hits, A
Bowen ByramD · Chicago Blackhawks87% match
shared: A, G
Aaron EkbladD · Florida Panthers86% match
shared: Hits
Alexander NikishinD · Carolina Hurricanes84% match
shared: Hits, G

Complementary Defense

Same position, opposite profile — strong where K'Andre Miller is weak or average, light where he’s strong

Cale MakarD · Colorado Avalanchecovers 2
fills: PPP, SOG
Zach WerenskiD · Columbus Blue Jacketscovers 2
fills: SOG, PPP
Quinn HughesD · Minnesota Wildcovers 2
fills: PPP, SOG
Evan BouchardD · Edmonton Oilerscovers 2
fills: 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 · Rod Brind'Amour (CAR)

Last year: Rod Brind'Amour full season — no change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	22.99	22.39	21.82	+3%
5v5 TOI	19.00	18.49	18.29	+1%
PP TOI	0.90	0.98	0.57	+73%

By quarter — 2025-26 vs 3-yr baseline

GP 14 · 19 · 22 · 17

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 → 22.99: holds last year's role; Positive luck regression plus offensive deployment; raise defenseman baseline.
5v5 TOI → 19.00: holds last year's role; Positive luck regression plus offensive deployment; raise defenseman baseline.
PP TOI → 0.90: PP2 timeshare behind Nikishin, not a real PP option. The 0.98 season mark was a Q1 mirage (2.08 PP TOI in Q1, then 0.69/0.62/0.88 with ZERO PP points/60 in Q2-Q4). Nikishin ascended into the PP2 QB role in H2 (1.63->1.77->1.89). Set to 0.9 - just above Miller's ~0.72 H2 with a nod to his 1:35 playoff look, but clearly the junior partner (playoff bounce 1:35 vs Nikishin 1:12).

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	4.91	4.91	3.90	+26%
G/60	0.32	0.27	0.30	-9%
iSH%	6.55	5.50	7.59	-28%
ixG/60	–	0.21	0.19	+10%
iCF/60	–	12.39	9.18	+35%
iSCF/60	–	3.20	2.84	+12%
iHDCF/60	–	0.59	0.48	+24%

By quarter — 2025-26 vs 3-yr baseline

GP 14 · 19 · 22 · 17

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 5.5% vs 7.6% 3-yr while 5v5 ixG/60 0.21 (23rd pct league-wide) held/rose — the chances say the finishing rebounds toward 6.5%, lifting the goal rate ~19%.

TailwindShot volume up 26% (5v5 SOG/60 4.91 vs 3.90) — volume is the repeatable half, so this raises the goal ceiling.

ContextTrajectory: 5v5 ixG/60 fell from 0.26 (1st half) to 0.18 (2nd) even though shot volume held — a chance-quality dip, not a volume one.

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%	8.65	8.53	9.01	-5%
IPP	38.75	38.52	39.46	-2%
1A/60	0.36	0.36	0.32	+11%
2A/60	0.35	0.41	0.41	+1%

By quarter — 2025-26 vs 3-yr baseline

GP 14 · 19 · 22 · 17

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% 8.5%, IPP 38.5%).

TailwindShot-driving up (5v5 iCF/60 12.39 vs 9.18) — real creation underneath, so don't over-regress the helpers.

TailwindHigh-danger setups up (iHDCF/60 0.59 vs 0.48) — 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	0.90	0.98	0.57	+73%
PP iSH%	4.91	11.15	0.00
PP SOG/60	5.60	7.62	6.81	+12%
PP ixG/60	–	0.59	0.36	+64%

By quarter — 2025-26 vs 3-yr baseline

GP 14 · 19 · 22 · 17

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: 1.0→0.9 PP TOI/gp (PP2 timeshare behind Nikishin, not a real PP option. The 0.98 season mark was a Q1 mirage (2.08 PP TOI in Q1, then 0.69/0.62/0.88 with ZERO PP points/60 in Q2-Q4). Nikishin ascended into the PP2 QB role in H2 (1.63->1.77->1.89). Set to 0.9 - just above Miller's ~0.72 H2 with a nod to his 1:35 playoff look, but clearly the junior partner (playoff bounce 1:35 vs Nikishin 1:12).) — the biggest PPP lever.

TailwindPP chance quality up (PP ixG/60 0.59 vs 0.36) — 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	1.74	2.25	1.38	+63%
Hits/60	4.67	4.10	5.52	-26%
Blks/60	3.17	2.93	3.50	-16%

By quarter — 2025-26 vs 3-yr baseline

GP 14 · 19 · 22 · 17

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)

ContextTemper the aggressive Miller boost; treat 35-40 points as the realistic upside, not 45-50, and do not over-credit PIM-driven value. · Fantasy hockey defenseman analysis

ContextHits role-stable at 4.10/60 (50th pct league-wide) → 4.67 projected.

TailwindBlocks surging late: Q4 3.86/60 and 2nd-half 2.94 vs a 2.93 season rate (3.50 3-yr) (61st pct league-wide) — reads as a real role/confidence step, so projected UP to 3.17/60, weighting the finish over the 3-yr baseline.