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 73% below his 3-year rate last season (0.31 against 1.17).

We project it down

all5v5

We’re projecting assists 32% below last season, 19 to 13.

Second-half surge

iSCF/60

iSCF/60 finished the year 70% above where it started (2.04 in the first half, 3.47 in the second). The projection leans on how the season ended, so the second half counts for more.

We project it down

PTS

all5v5

We’re projecting points 27% below last season, 22 to 16.

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 Sabres78% match
Rasmus RistolainenD · Philadelphia Flyers73% match
Vladislav GavrikovD · New York Rangers72% match
Dmitry OrlovD · San Jose Sharks69% match

Complementary Defense

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

Rasmus DahlinD · Buffalo Sabrescovers 3
fills: A, PIM, SOG
Dougie HamiltonD · New Jersey Devilscovers 4
fills: SOG, PIM, A, Hits
Brandon MontourD · Seattle Krakencovers 3
fills: SOG, PIM, Hits
Quinn HughesD · Minnesota Wildcovers 2
fills: A, 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 · Sheldon Keefe (NJD)

Last year (WSH, traded): Spencer Carbery full season — no change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	14.43	13.73	16.84	-19%
5v5 TOI	13.35	13.08	15.02	-13%
PP TOI	0.45	0.31	1.17	-73%

By quarter — 2025-26 vs 3-yr baseline

GP 9 · 6 · 10 · 1

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 → 14.43: reverts toward the 3-yr 16.8
5v5 TOI → 13.35: role tapered late (Q4 12.1 vs 13.1 full-year) — projected toward the softer finish
PP TOI → 0.45: role tapered late (Q4 0.2 vs 0.3 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	3.40	3.35	3.21	+4%
G/60	0.14	0.18	0.08	+116%
iSH%	3.98	5.37	2.60	+107%
ixG/60	–	0.12	0.12	-0%
iCF/60	–	9.00	8.08	+11%
iSCF/60	–	2.65	1.89	+40%
iHDCF/60	–	0.35	0.50	-29%

By quarter — 2025-26 vs 3-yr baseline

GP 9 · 6 · 10 · 1

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 5.4% vs a 2.6% 3-yr mark while 5v5 ixG/60 0.12 (5th pct league-wide) was flat — finishing, not process. Regressing iSH% toward 4.0% pulls the goal rate ~25% down.

TailwindTrajectory: 5v5 ixG/60 climbed 0.10→0.18 across the year — process trending the right way into next season.

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%	9.78	10.87	6.81	+60%
IPP	39.85	43.97	28.70	+53%
1A/60	0.43	0.53	0.29	+85%
2A/60	0.29	0.53	0.16	+229%

By quarter — 2025-26 vs 3-yr baseline

GP 9 · 6 · 10 · 1

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)

RiskAssists projected DOWN: on-ice SH% 10.9% (3-yr 6.8%) AND IPP 44.0% (3-yr 28.7%) both ran hot — team finishing + participation luck stacked. Regressing both trims the assist rate ~12%.

TailwindShot-driving up (5v5 iCF/60 9.00 vs 8.08) — real creation underneath, so don't over-regress the helpers.

RiskAssist gain leans on secondary helpers (2A/60 0.53 vs 3-yr 0.16) — the least repeatable slice; projected back toward baseline.

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	0.45	0.31	1.17	-73%
PP iSH%	–	n/a	19.96
PP SOG/60	1.59	0.00	7.93	-100%
PP ixG/60	–	0.00	0.59	-100%

By quarter — 2025-26 vs 3-yr baseline

GP 9 · 6 · 10 · 1

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: 0.3→0.5 PP TOI/gp (role tapered late (Q4 0.2 vs 0.3 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	0.96	0.71	1.15	-38%
Hits/60	2.05	1.94	1.77	+10%
Blks/60	3.90	3.88	3.91	-1%

By quarter — 2025-26 vs 3-yr baseline

GP 9 · 6 · 10 · 1

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 2.98/60 and 2nd-half 2.98 vs a 1.94 season rate (1.77 3-yr) (24th pct league-wide) — reads as a real role/confidence step, so projected UP to 2.05/60, weighting the finish over the 3-yr baseline.

ContextBlocks role-stable at 3.88/60 (79th pct league-wide) → 3.90 projected.