Per 82 GP	2026-27projection	2025-2682 GP	H241 GP	H141 GP	Prev 3thin
TOI	17.00	17.45	17.03	15.68	–
PP TOI	2.70	2.36	2.93	1.80	–
G	25	23	20	26	–
A	42	37	36	38	–
PTS	67	60	56	64	–
PPP	16	13	16	10	–
SOG	217	197	226	168	–
PIM	62	62	60	64	–
Hits	94	97	112	82	–
Blocks	23	24	22	26	–

Sample: 82 GP · 1,143 5v5 min (2025-26) — how much ice time backs these rates

Positional rankingRight wing · league-wide (of 273)

28Kevin Fiala79

29Alex Ovechkin78

30Mark Stone75

31Beckett Sennecke74

32Kirill Marchenko73

33Will Cuylle72

34Drake Batherson72

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): Sophomore hedge on a prolific but young scorer: minutes pulled back to ~17 all / 2.7 PP lands him ~64 pts (from an optimistic 69, +9 riser). Goals held at ~24 on purpose — every 5v5 shot-quality metric climbed every quarter (shots 6.1->8.9, ixG 0.87->1.33, high-danger chances rising into Q4) while his iSH% collapsed 20%->7.9%, so he badly under-finished a rising process. The finishing upside is real; the hedge is on the role, not the talent. Assists kept healthy (~40).

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

PP TOI

PP TOI finished the year 61% above where it started (1.80 in the first half, 2.91 in the second). The projection leans on how the season ended, so the second half counts for more.

Second-half surge

PPP

Power play points ran at a 16 pace in the second half after 10 in the first, per 82 games.

We project it up

all5v5

We’re projecting assists 14% above last season, 37 to 42.

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

Porter MartoneRW · Philadelphia Flyers92% match
shared: PIM, Hits, G
Carter VerhaegheLW · Florida Panthers84% match
shared: SOG, G
Jonathan MarchessaultRW · Nashville Predators84% match
shared: SOG, Hits, G
Jason ZuckerLW,RW · Buffalo Sabres84% match
shared: PIM, Hits

Complementary Forward

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

Aleksander BarkovC · Florida Pantherscovers 2
fills: PPP, Hits
Drake BathersonLW,RW · Ottawa Senatorscovers 2
fills: PPP, Hits
Morgan GeekieC,LW,RW · Boston Bruinscovers 2
fills: Hits, PPP
Tim StützleC,LW · Ottawa Senatorscovers 2
fills: PPP, Hits

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 · Joel Quenneville (ANA)

Last year: Joel Quenneville full season (1st yr) — no change

Metric	26-27 proj	2025-26	Prev 3
TOI	17.00	17.45	n/a
5v5 TOI	14.80	13.94	n/a
PP TOI	2.70	2.36	n/a

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 20 · 22 · 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 → 17.00: Sophomore hedge: the engine grew his role to 18.7 all-TOI off one NHL season; pulling back to ~17 (his actual was 17.5) removes that growth bias in a crowded Anaheim forward group.
5v5 TOI → 14.80: one NHL season — role grown +7% toward a sophomore workload
PP TOI → 2.70: On PP1 in the playoffs (2:34, 5th in line, ahead of Kreider), so nudged up from the 2.5 sophomore hedge — but kept modest since he's still a sophomore who could cede the spot.

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
SOG/60	8.09	7.77	n/a
G/60	1.09	1.05	n/a
iSH%	13.51	13.51	n/a
ixG/60	–	1.02	n/a
iCF/60	–	15.48	n/a
iSCF/60	–	9.03	n/a
iHDCF/60	–	4.67	n/a

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 20 · 22 · 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)

TailwindTrajectory: 5v5 ixG/60 climbed 0.89→1.17 across the year — process trending the right way into next season.

TailwindAge 20 — still on the up-slope of the scoring curve.

TailwindAge 20 on a single NHL season — projected a development step, not a flat repeat: scoring rates +10% and role +7% toward the mid-20s peak (a young riser improves on last year, not repeats it).

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
on-ice SH%	8.92	8.92	n/a
IPP	75.09	75.09	n/a
1A/60	0.58	0.58	n/a
2A/60	0.42	0.42	n/a

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 20 · 22 · 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)

ContextAssist environment looks normal (on-ice SH% 8.9%, IPP 75.1%).

Power play

PP opportunity and finishing — modelled separately from 5v5.

Metric	26-27 proj	2025-26	Prev 3
PP TOI	2.70	2.36	n/a
PP iSH%	3.04	3.04	n/a
PP SOG/60	10.21	10.21	n/a
PP ixG/60	–	2.58	n/a

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 20 · 22 · 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)

TailwindPP role projected up: 2.4→2.7 PP TOI/gp (On PP1 in the playoffs (2:34, 5th in line, ahead of Kreider), so nudged up from the 2.5 sophomore hedge — but kept modest since he's still a sophomore who could cede the spot.) — 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
PIMs/60	2.79	2.73	n/a
Hits/60	4.98	4.98	n/a
Blks/60	1.13	1.15	n/a

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 20 · 22 · 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 4.98/60 (59th pct league-wide) → 4.98 projected.

RiskBlocks tailing off: Q4 0.94/60 and 2nd-half 1.03 below the 1.15 season rate — projected DOWN to 1.13/60, weighting the recent decline over the n/a 3-yr mark.

TailwindStrong PIM rate (2.73/60 (78th pct league-wide)) — a banger-league asset.