Per 82 GP	2026-27projection adj	2025-2672 GP	H231 GP	H141 GP	Prev 3178 GP · 3y
TOI	16.04	17.27	17.17	15.93	13.62
PP TOI	0.50	1.78	1.44	2.05	0.70
G	19	26	19	31	17
A	▼15	15	24	8	20
PTS	▼34	41	43	39	37
PPP	2	14	11	16	2
SOG	▼157	196	209	186	141
PIM	65	57	65	51	49
Hits	▼339	386	373	396	367
Blocks	34	34	33	35	31

Sample: 72 GP · 949 5v5 min (2025-26) — how much ice time backs these rates

Positional rankingLeft wing · league-wide (of 281)

39Gabriel Landeskog63

40Trevor Zegras62

41Brad Marchand61

42Kiefer Sherwood60

43Alex Laferriere57

44A.J. Greer55

45Evander Kane53

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): His fantasy value IS the hits (394 per-82 baseline); a bottom-six role cuts both TOI and hit opportunity. Even at x0.72 he stays an elite banger (~284 hits), just off the outlier peak. NOTE: the EV cuts (HITS/G/A/SOG) are a bottom-six MINUTES story (EV TOI 13.99) tangled with a hit-rate outlier regression; candidate to convert to a deploy.ev bet + a smaller residual HITS rate cut in a follow-up. PP role bet already moved to minutes here.

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 down

PP TOI

We’re projecting PP TOI 72% below last season, 1.78 to 0.50.

Above his 3-year rate

PP ixG/60

PP ixG/60 ran 131% above his 3-year rate last season (2.21 against 0.95).

Above his 3-year rate

PP SOG/60

PP SOG/60 ran 86% above his 3-year rate last season (12.61 against 6.76).

Second-half surge

PIMs/60

PIMs/60 finished the year 137% above where it started (1.29 in the first half, 3.07 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 Forward

Closest across all seven categories — match % is the whole-profile fit

Yakov TreninLW,RW · Minnesota Wild87% match
shared: Hits, PIM
Ryan LeonardRW · Washington Capitals86% match
shared: Hits, PIM
Martin PospisilC,RW · Calgary Flames85% match
shared: Hits, PIM
Zachary L'HeureuxLW,RW · Colorado Avalanche84% match
shared: Hits, PIM

Complementary Forward

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

Jack HughesC,LW · New Jersey Devilscovers 4
fills: SOG, PPP, A, G
Artemi PanarinLW · Los Angeles Kingscovers 4
fills: A, PPP, SOG, G
William NylanderRW · Toronto Maple Leafscovers 4
fills: PPP, SOG, G, A
Jack EichelC · Vegas Golden Knightscovers 4
fills: SOG, A, PPP, G

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 (VAN, traded): Ryan Warsofsky SJS · pre-trade → Adam Foote VAN · acquired mid-season (small sample) — in-season change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	16.04	17.27	13.62	+27%
5v5 TOI	12.97	13.18	11.78	+12%
PP TOI	0.50	1.78	0.70	+156%

By quarter — 2025-26 vs 3-yr baseline

GP 22 · 19 · 10 · 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 → 16.04: reverts toward the 3-yr 13.6; Cut PPP/scoring and trim the elite hits rate toward a bottom-six deployment; the banger ceiling was ice-time-driven.
5v5 TOI → 12.97: same coach (Ryan Warsofsky) — carries the elevated finish (2nd half 14.0, Q4 14.6) over the full-year 13.2; Cut PPP/scoring and trim the elite hits rate toward a bottom-six deployment; the banger ceiling was ice-time-driven.
PP TOI → 0.50: PP role already disappeared by Q4 (1.78 -> ~0.5 PP TOI); near-zero PP time expected

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	8.28	8.28	7.50	+10%
G/60	0.88	0.82	0.89	-8%
iSH%	10.64	9.90	11.84	-16%
ixG/60	–	0.88	0.72	+22%
iCF/60	–	17.32	15.11	+15%
iSCF/60	–	8.22	6.81	+21%
iHDCF/60	–	3.73	3.01	+24%

By quarter — 2025-26 vs 3-yr baseline

GP 22 · 19 · 10 · 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)

TailwindGoals projected UP: iSH% cratered to 9.9% vs 11.8% 3-yr while 5v5 ixG/60 0.88 (85th pct league-wide) held/rose — the chances say the finishing rebounds toward 10.6%, lifting the goal rate ~7%.

TailwindShot volume up 10% (5v5 SOG/60 8.28 vs 7.50) — volume is the repeatable half, so this raises the goal ceiling.

TailwindTrajectory: 5v5 ixG/60 climbed 0.80→0.99 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%	9.43	8.99	10.74	-16%
IPP	56.44	52.57	68.00	-23%
1A/60	0.44	0.25	0.69	-64%
2A/60	0.38	0.25	0.43	-42%

By quarter — 2025-26 vs 3-yr baseline

GP 22 · 19 · 10 · 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)

TailwindIPP 52.6% sits below the 68.0% 3-yr mark — participation should rebound, nudging assists up.

TailwindShot-driving up (5v5 iCF/60 17.32 vs 15.11) — real creation underneath, so don't over-regress the helpers.

TailwindHigh-danger setups up (iHDCF/60 3.73 vs 3.01) — the dangerous chances that turn into primary assists are trending up.

Power play

PP opportunity and finishing — modelled separately from 5v5.

Metric	26-27 proj	2025-26	Prev 3	Diff
PP TOI	0.50	1.78	0.70	+156%
PP iSH%	15.04	25.93	7.15	+263%
PP SOG/60	11.15	12.61	6.76	+86%
PP ixG/60	–	2.21	0.95	+131%

By quarter — 2025-26 vs 3-yr baseline

GP 22 · 19 · 10 · 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)

RiskCut PPP/scoring and trim the elite hits rate toward a bottom-six deployment; the banger ceiling was ice-time-driven. · Phil (context note)

RiskPP role projected down: 1.8→0.5 PP TOI/gp (PP role already disappeared by Q4 (1.78 -> ~0.5 PP TOI); near-zero PP time expected) — the biggest PPP lever.

TailwindPP chance quality up (PP ixG/60 2.21 vs 0.95) — 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	2.25	1.77	2.92	-39%
Hits/60	21.11	20.42	22.15	-8%
Blks/60	1.53	1.45	1.66	-13%

By quarter — 2025-26 vs 3-yr baseline

GP 22 · 19 · 10 · 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)

RiskCut PPP/scoring and trim the elite hits rate toward a bottom-six deployment; the banger ceiling was ice-time-driven. · Phil (context note)

TailwindProject Melanson as an elite HITS/PIM specialist for 2026-27 (Sherwood-tier), with negligible G/A/PTS.

TailwindElite hits volume (98th pct) and role-stable — a bankable hits floor (21.11/60 projected).

ContextBlocks role-stable at 1.45/60 (15th pct league-wide) → 1.53 projected.