Per 82 GP	2026-27projection	2025-2641 GP	H216 GP	H125 GP	Prev 3194 GP · 3y
TOI	18.12	17.80	18.04	16.66	19.26
PP TOI	0.44	0.61	0.21	0.91	0.29
G	4	4	10	-0	4
A	16	26	36	16	14
PTS	20	30	46	16	18
PPP	1	4	0	8	0
SOG	88	80	91	66	94
PIM	26	28	21	23	29
Hits	74	54	71	47	86
Blocks	83	74	84	78	89

Sample: 41 GP · 651 5v5 min (2025-26) — how much ice time backs these rates

Positional rankingDefense · league-wide (of 303)

229Scott Morrow-36

230Maxim Strbak-37

231Matt Grzelcyk-37

232Henri Jokiharju-37

233Jordan Oesterle-37

234Nick Blankenburg-37

235Ben Hutton-38

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 surge

all5v5

Assists ran at a 36 pace in the second half after 16 in the first, per 82 games.

Second-half surge

HITS

all5v5

Hits ran at a 71 pace in the second half after 47 in the first, per 82 games.

Above his 3-year rate

iSH%

iSH% ran 52% above his 3-year rate last season (5.92 against 3.89).

We project it down

PTS

all5v5

We’re projecting points 33% below last season, 30 to 20.

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

Rasmus RistolainenD · Philadelphia Flyers82% match
Dmitry OrlovD · San Jose Sharks78% match
Vladislav GavrikovD · New York Rangers77% match
Owen PowerD · Buffalo Sabres76% match

Complementary Defense

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

Quinn HughesD · Minnesota Wildcovers 3
fills: A, PPP, SOG
Zach WerenskiD · Columbus Blue Jacketscovers 3
fills: SOG, A, PPP
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 · Marco Sturm (BOS)

Last year: Marco Sturm full season (1st yr) — no change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	18.12	17.80	19.26	-8%
5v5 TOI	16.29	15.88	17.20	-8%
PP TOI	0.44	0.61	0.29	+111%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 4 · 10 · 6

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 → 18.12: holds last year's role
5v5 TOI → 16.29: holds last year's role
PP TOI → 0.44: role tapered late (Q4 0.0 vs 0.6 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	3.26	3.04	3.65	-17%
G/60	0.16	0.18	0.14	+27%
iSH%	4.91	5.92	3.89	+52%
ixG/60	–	0.15	0.13	+15%
iCF/60	–	8.84	8.74	+1%
iSCF/60	–	2.03	2.09	-3%
iHDCF/60	–	0.09	0.20	-55%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 4 · 10 · 6

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 0.15 (13th pct league-wide) up on the 3-yr 0.13 — the shot quality is real, so the projected goal rate leans on chances, not a hot %.

RiskShot volume down 17% (5v5 SOG/60 3.04 vs 3.65) — volume is the repeatable half, so this caps the goal ceiling.

TailwindTrajectory: 5v5 ixG/60 climbed 0.13→0.20 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%	11.23	11.81	10.04	+18%
IPP	32.08	36.14	23.84	+52%
1A/60	0.42	0.55	0.25	+118%
2A/60	0.32	0.46	0.29	+60%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 4 · 10 · 6

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% 11.8% (3-yr 10.0%) AND IPP 36.1% (3-yr 23.8%) both ran hot — team finishing + participation luck stacked. Regressing both trims the assist rate ~11%.

RiskAssist gain leans on secondary helpers (2A/60 0.46 vs 3-yr 0.29) — 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	0.44	0.61	0.29	+111%
PP iSH%	0.00	0.00	0.00
PP SOG/60	11.47	11.97	4.27	+181%
PP ixG/60	–	0.54	0.30	+79%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 4 · 10 · 6

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: 0.6→0.4 PP TOI/gp (role tapered late (Q4 0.0 vs 0.6 full-year) — projected toward the softer finish) — the biggest PPP lever.

TailwindPP chance quality up (PP ixG/60 0.54 vs 0.30) — 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	1.24	1.29	1.22	+6%
Hits/60	2.80	2.30	3.40	-32%
Blks/60	3.06	2.86	3.36	-15%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 4 · 10 · 6

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 3.13/60 and 2nd-half 2.94 vs a 2.30 season rate (3.40 3-yr) (28th pct league-wide) — reads as a real role/confidence step, so projected UP to 2.80/60, weighting the finish over the 3-yr baseline.

ContextBlocks role-stable at 2.86/60 (59th pct league-wide) → 3.06 projected.