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

We project it up

HITS

all5v5

We’re projecting hits 46% above last season, 39 to 57.

We project it down

PIM

all5v5

We’re projecting penalty minutes 57% below last season, 21 to 9.

Second-half fade

SOG

all5v5

Shots ran at a 55 pace in the second half after 94 in the first, per 82 games.

Second-half surge

iSCF/60

iSCF/60 finished the year 35% above where it started (2.33 in the first half, 3.14 in the second). The projection leans on how the season ended, so the second half counts for more.

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

Owen PowerD · Buffalo Sabres74% match
Rasmus RistolainenD · Philadelphia Flyers74% match
Vladislav GavrikovD · New York Rangers71% match
Dmitry OrlovD · San Jose Sharks69% match

Complementary Defense

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

Rasmus DahlinD · Buffalo Sabrescovers 4
fills: A, PIM, SOG, PPP
Quinn HughesD · Minnesota Wildcovers 3
fills: A, PPP, SOG
Dougie HamiltonD · New Jersey Devilscovers 4
fills: SOG, PPP, PIM, A
Evan BouchardD · Edmonton Oilerscovers 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 · André Tourigny (UTA)

Last year: André Tourigny full season — no change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	14.23	14.21	14.26	-0%
5v5 TOI	13.66	13.82	13.68	+1%
PP TOI	0.04	0.06	0.02	+270%

By quarter — 2025-26 vs 3-yr baseline

GP 6 · 11 · 18 · 5

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 → 14.23: holds last year's role
5v5 TOI → 13.66: role tapered late (Q4 12.9 vs 13.8 full-year) — projected toward the softer finish
PP TOI → 0.04: role tapered late (Q4 0.0 vs 0.1 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	3.59	3.69	4.14	-11%
G/60	0.21	0.22	0.24	-9%
iSH%	5.90	5.96	5.84	+2%
ixG/60	–	0.22	0.17	+30%
iCF/60	–	8.68	9.42	-8%
iSCF/60	–	2.93	2.76	+6%
iHDCF/60	–	0.65	0.25	+165%

By quarter — 2025-26 vs 3-yr baseline

GP 6 · 11 · 18 · 5

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 0.22 (25th pct league-wide) up on the 3-yr 0.17 — the shot quality is real, so the projected goal rate leans on chances, not a hot %.

RiskShot volume down 11% (5v5 SOG/60 3.69 vs 4.14) — volume is the repeatable half, so this caps the goal ceiling.

ContextTrajectory: 5v5 ixG/60 fell from 0.24 (1st half) to 0.19 (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%	9.40	10.11	7.96	+27%
IPP	35.24	33.46	41.96	-20%
1A/60	0.25	0.22	0.25	-10%
2A/60	0.53	0.43	0.57	-25%

By quarter — 2025-26 vs 3-yr baseline

GP 6 · 11 · 18 · 5

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 10.1% vs a 8.0% 3-yr mark — teammate finishing regresses (~8% is league-normal), so some assists come off.

TailwindHigh-danger setups up (iHDCF/60 0.65 vs 0.25) — 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	0.04	0.06	0.02	+270%
PP iSH%	–	n/a	n/a
PP SOG/60	0.00	0.00	0.00
PP ixG/60	–	0.00	0.00

By quarter — 2025-26 vs 3-yr baseline

GP 6 · 11 · 18 · 5

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: 0.1→0.0 PP TOI/gp (role tapered late (Q4 0.0 vs 0.1 full-year) — projected toward the softer finish) — 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	0.76	1.09	0.33	+233%
Hits/60	2.57	2.06	3.33	-38%
Blks/60	3.67	3.36	3.98	-16%

By quarter — 2025-26 vs 3-yr baseline

GP 6 · 11 · 18 · 5

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 2.06/60 (25th pct league-wide) → 2.57 projected.

TailwindBlocks surging late: Q4 4.66/60 and 2nd-half 3.83 vs a 3.36 season rate (3.98 3-yr) (69th pct league-wide) — reads as a real role/confidence step, so projected UP to 3.67/60, weighting the finish over the 3-yr baseline.