Per 82 GP	2026-27projection adj	2025-2668 GP	H233 GP	H135 GP	Prev 3211 GP · 3y
TOI	16.96	17.37	16.98	16.73	15.35
PP TOI	2.76	2.30	2.67	1.95	1.64
G	23	23	25	21	22
A	▲32	31	38	24	29
PTS	▲55	54	63	46	51
PPP	▲15	8	5	12	10
SOG	156	143	149	138	168
PIM	63	67	49	84	73
Hits	106	101	105	97	107
Blocks	36	34	38	29	36

Sample: 68 GP · 987 5v5 min (2025-26) — how much ice time backs these rates

Positional rankingLeft wing · league-wide (of 281)

43Alex Laferriere57

44A.J. Greer55

45Evander Kane53

46Mason Marchment52

47Patrik Laine51

48Jared McCann49

49Vasily Podkolzin47

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.

Context-adjusted (▲/▼ vs the rate-model baseline): Deployment-contingent (needs the Celebrini line + PP1); held small. Same SJS logjam that squeezes Sherwood.

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

PPP

We’re projecting power play points 88% above last season, 8 to 15.

Second-half surge

1A/60

1A/60 finished the year 70% above where it started (0.59 in the first half, 1.00 in the second). The projection leans on how the season ended, so the second half counts for more.

Second-half surge

all5v5

Assists ran at a 38 pace in the second half after 24 in the first, per 82 games.

Below his 3-year rate

PP ixG/60

PP ixG/60 ran 66% below his 3-year rate last season (0.94 against 2.74).

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

Jamie BennLW · Dallas Stars88% match
shared: PIM, Hits
Mason McTavishC · St. Louis Blues88% match
shared: PIM, Hits
Ryan LeonardRW · Washington Capitals86% match
shared: PIM, Hits
Jason ZuckerLW,RW · Buffalo Sabres85% match
shared: PIM, Hits, PPP

Complementary Forward

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

Jack HughesC,LW · New Jersey Devilscovers 3
fills: SOG, A, G
Kyle ConnorLW · Winnipeg Jetscovers 3
fills: SOG, G, A
Jack EichelC · Vegas Golden Knightscovers 3
fills: SOG, A, G
Cole CaufieldLW · Montreal Canadienscovers 3
fills: G, SOG, A

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 · Ryan Warsofsky (SJS)

Last year (SEA, traded): Rick Bowness CBJ · pre-trade → Lane Lambert SEA · acquired mid-season (small sample) — in-season change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	16.96	17.37	15.35	+13%
5v5 TOI	14.09	14.53	13.30	+9%
PP TOI	2.76	2.30	1.64	+40%

By quarter — 2025-26 vs 3-yr baseline

GP 19 · 16 · 14 · 19

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 → 16.96: holds last year's role
5v5 TOI → 14.09: holds last year's role
PP TOI → 2.76: top-50 multi-cat upside with consistent PP1 minutes — bet on the PP minutes (deployment-contingent)

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	5.71	5.71	7.42	-23%
G/60	0.76	0.85	0.79	+7%
iSH%	13.28	14.89	10.66	+40%
ixG/60	–	0.78	0.76	+2%
iCF/60	–	12.82	13.70	-6%
iSCF/60	–	7.29	8.53	-15%
iHDCF/60	–	3.28	3.16	+4%

By quarter — 2025-26 vs 3-yr baseline

GP 19 · 16 · 14 · 19

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 14.9% vs a 10.7% 3-yr mark while 5v5 ixG/60 0.78 (73rd pct league-wide) was flat — finishing, not process. Regressing iSH% toward 13.3% pulls the goal rate ~11% down.

RiskShot volume down 23% (5v5 SOG/60 5.71 vs 7.42) — volume is the repeatable half, so this caps the goal ceiling.

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%	9.99	11.18	9.05	+24%
IPP	72.33	72.95	71.48	+2%
1A/60	0.81	0.79	0.77	+3%
2A/60	0.39	0.49	0.36	+35%

By quarter — 2025-26 vs 3-yr baseline

GP 19 · 16 · 14 · 19

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 11.2% vs a 9.0% 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	2.76	2.30	1.64	+40%
PP iSH%	18.16	15.78	18.84	-16%
PP SOG/60	6.89	7.29	11.94	-39%
PP ixG/60	–	0.94	2.74	-66%

By quarter — 2025-26 vs 3-yr baseline

GP 19 · 16 · 14 · 19

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)

TailwindBoost toward a top-six/PP1 line if paired with Celebrini. · Fantasy hockey transition analysis

TailwindPP role projected up: 2.3→2.8 PP TOI/gp (top-50 multi-cat upside with consistent PP1 minutes — bet on the PP minutes (deployment-contingent)) — 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	2.57	2.92	3.23	-10%
Hits/60	5.02	4.68	5.52	-15%
Blks/60	1.83	1.64	1.88	-13%

By quarter — 2025-26 vs 3-yr baseline

GP 19 · 16 · 14 · 19

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 4.68/60 (57th pct league-wide) → 5.02 projected.

TailwindBlocks surging late: Q4 2.32/60 and 2nd-half 1.86 vs a 1.64 season rate (1.88 3-yr) (21st pct league-wide) — reads as a real role/confidence step, so projected UP to 1.83/60, weighting the finish over the 3-yr baseline.

TailwindStrong PIM rate (2.92/60 (81st pct league-wide)) — a banger-league asset.