Per 82 GP	2026-27projection	2025-2682 GP	H241 GP	H141 GP	Prev 3228 GP · 3y
TOI	21.15	21.03	20.55	20.40	21.97
PP TOI	0.08	0.06	0.03	0.08	0.35
G	5	7	9	5	4
A	15	16	18	14	13
PTS	20	23	27	19	18
PPP	0	0	0	0	0
SOG	93	94	94	94	97
PIM	40	35	46	24	41
Hits	136	138	119	157	145
Blocks	148	149	134	164	167

Sample: 82 GP · 1,396 5v5 min (2025-26) — how much ice time backs these rates

Positional rankingDefense · league-wide (of 303)

93Emil Lilleberg7

94Erik Cernak7

95Brady Skjei7

96Mario Ferraro6

97Cole Hutson6

98Zach Whitecloud6

99Brayden Pachal6

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

iSH%

iSH% finished the year 100% above where it started (4.68 in the first half, 9.35 in the second). The projection leans on how the season ended, so the second half counts for more.

Second-half surge

PIM

all5v5

Penalty minutes ran at a 46 pace in the second half after 24 in the first, per 82 games.

We project it down

PTS

all5v5

We’re projecting points 13% below last season, 23 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

Adam LarssonD · Seattle Kraken91% match
shared: Hits, Blocks
Martin FehervaryD · Washington Capitals91% match
shared: Hits, Blocks
Brayden McNabbD · Vegas Golden Knights88% match
shared: Hits, Blocks
Nick SeelerD · Philadelphia Flyers88% match
shared: Hits, Blocks

Complementary Defense

Same position, opposite profile — strong where Mario Ferraro 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
Cale MakarD · Colorado Avalanchecovers 3
fills: A, PPP, SOG
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 · Scott Arniel (WPG)

Last year (SJS, traded): Ryan Warsofsky full season — no change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	21.15	21.03	21.97	-4%
5v5 TOI	17.31	17.03	18.03	-6%
PP TOI	0.08	0.06	0.35	-84%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 20 · 20 · 21

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 → 21.15: holds last year's role
5v5 TOI → 17.31: holds last year's role
PP TOI → 0.08: 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	3.78	3.78	3.59	+5%
G/60	0.19	0.26	0.13	+98%
iSH%	4.62	6.88	3.65	+88%
ixG/60	–	0.14	0.18	-24%
iCF/60	–	8.51	8.50	+0%
iSCF/60	–	1.98	2.61	-24%
iHDCF/60	–	0.39	0.56	-30%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 20 · 20 · 21

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 6.9% vs a 3.6% 3-yr mark while 5v5 ixG/60 0.14 (11th pct league-wide) was flat — finishing, not process. Regressing iSH% toward 4.6% pulls the goal rate ~28% down.

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%	9.10	9.65	7.98	+21%
IPP	33.28	35.68	28.39	+26%
1A/60	0.33	0.39	0.23	+66%
2A/60	0.22	0.21	0.25	-15%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 20 · 20 · 21

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% 9.7% (3-yr 8.0%) AND IPP 35.7% (3-yr 28.4%) both ran hot — team finishing + participation luck stacked. Regressing both trims the assist rate ~6%.

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	0.08	0.06	0.35	-84%
PP iSH%	–	n/a	0.00
PP SOG/60	0.91	0.00	4.55	-100%
PP ixG/60	–	0.91	0.31	+195%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 20 · 20 · 21

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: 0.1→0.1 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	1.50	1.50	1.50	-0%
Hits/60	5.15	5.29	5.30	-0%
Blks/60	4.44	4.51	4.54	-1%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 20 · 20 · 21

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 4.38/60 and 2nd-half 4.45 below the 5.29 season rate — projected DOWN to 5.15/60, weighting the recent decline over the 5.30 3-yr mark.

RiskBlocks tailing off: Q4 3.90/60 and 2nd-half 3.84 below the 4.51 season rate — projected DOWN to 4.44/60, weighting the recent decline over the 4.54 3-yr mark.