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

Below his 3-year rate

PP TOI

PP TOI ran 64% below his 3-year rate last season (0.52 against 1.47).

Second-half fade

Hits/60

Hits/60 finished the year 39% below where it started (1.69 in the first half, 1.03 in the second). The projection leans on how the season ended, so the second half counts for more.

Above his 3-year rate

iSH%

iSH% ran 40% above his 3-year rate last season (13.67 against 9.76).

Second-half fade

BLK

all5v5

Blocks ran at a 36 pace in the second half after 53 in the first, per 82 games.

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 Forward

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

Cole PerfettiLW,RW · Winnipeg Jets82% match
Igor ChernyshovLW · San Jose Sharks79% match
Matty BeniersC · Seattle Kraken77% match
Connor McMichaelC,LW · St. Louis Blues77% match

Complementary Forward

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

Ross JohnstonLW · St. Louis Bluescovers 2
fills: PIM, Hits
Scott SabourinRW · Tampa Bay Lightningcovers 2
fills: PIM, Hits
Michael PezzettaLW,RW · Toronto Maple Leafscovers 2
fills: Hits, PIM
Jonah GadjovichLW,RW · Florida Pantherscovers 2
fills: PIM, Hits

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 (VAN, traded): Marco Sturm BOS · pre-trade → Jeff Blashill CHI · pre-trade → Adam Foote VAN · acquired mid-season (small sample) — in-season change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	12.51	12.45	13.46	-8%
5v5 TOI	11.53	11.51	11.43	+1%
PP TOI	0.66	0.52	1.47	-64%

By quarter — 2025-26 vs 3-yr baseline

GP 18 · 1 · 0 · 10

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 → 12.51: holds last year's role
5v5 TOI → 11.53: holds last year's role
PP TOI → 0.66: same coach (Marco Sturm) — carries the elevated finish (2nd half 0.8, Q4 0.8) over the full-year 0.5

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	3.95	3.95	5.45	-28%
G/60	0.48	0.54	0.53	+1%
iSH%	12.18	13.67	9.76	+40%
ixG/60	–	0.54	0.53	+1%
iCF/60	–	8.45	8.54	-1%
iSCF/60	–	6.11	5.32	+15%
iHDCF/60	–	2.52	2.66	-5%

By quarter — 2025-26 vs 3-yr baseline

GP 18 · 1 · 0 · 10

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 13.7% vs a 9.8% 3-yr mark while 5v5 ixG/60 0.54 (42nd pct league-wide) was flat — finishing, not process. Regressing iSH% toward 12.2% pulls the goal rate ~11% down.

RiskShot volume down 28% (5v5 SOG/60 3.95 vs 5.45) — volume is the repeatable half, so this caps the goal ceiling.

ContextTrajectory: 5v5 ixG/60 fell from 0.62 (1st half) to 0.43 (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%	9.77	13.72	6.99	+96%
IPP	56.72	44.58	77.26	-42%
1A/60	0.53	0.54	0.53	+2%
2A/60	0.35	0.36	0.30	+21%

By quarter — 2025-26 vs 3-yr baseline

GP 18 · 1 · 0 · 10

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 13.7% vs a 7.0% 3-yr mark — teammate finishing regresses (~8% is league-normal), so some assists come off.

Power play

PP opportunity and finishing — modelled separately from 5v5.

Metric	26-27 proj	2025-26	Prev 3	Diff
PP TOI	0.66	0.52	1.47	-64%
PP iSH%	5.59	0.00	7.17	-100%
PP SOG/60	3.70	3.94	7.22	-45%
PP ixG/60	–	0.76	1.20	-37%

By quarter — 2025-26 vs 3-yr baseline

GP 18 · 1 · 0 · 10

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: 0.5→0.7 PP TOI/gp (same coach (Marco Sturm) — carries the elevated finish (2nd half 0.8, Q4 0.8) over the full-year 0.5) — 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	0.81	1.08	1.00	+8%
Hits/60	1.54	1.44	1.89	-24%
Blks/60	2.36	2.70	2.13	+27%

By quarter — 2025-26 vs 3-yr baseline

GP 18 · 1 · 0 · 10

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 1.03/60 and 2nd-half 1.03 below the 1.44 season rate — projected DOWN to 1.54/60, weighting the recent decline over the 1.89 3-yr mark.

RiskBlocks tailing off: Q4 2.07/60 and 2nd-half 2.07 below the 2.70 season rate — projected DOWN to 2.36/60, weighting the recent decline over the 2.13 3-yr mark.