Per 82 GP	2026-27projection adj	2025-2682 GP	H240 GP	H142 GP	Prev 3236 GP · 3y
TOI	16.20	15.98	14.62	16.56	16.08
PP TOI	2.75	1.96	1.57	2.34	2.09
G	▲28	25	20	29	23
A	▲32	22	15	28	29
PTS	▲60	47	36	58	52
PPP	▲20	5	6	4	10
SOG	162	160	144	175	182
PIM	24	28	20	35	31
Hits	16	16	8	23	26
Blocks	16	19	14	23	15

Sample: 82 GP · 1,117 5v5 min (2025-26) — how much ice time backs these rates

Positional rankingLeft wing · league-wide (of 281)

78Tanner Jeannot24

79Yakov Trenin24

80Anthony Mantha23

81JJ Peterka23

82Viktor Arvidsson22

83Liam O'Brien22

84Jamie Benn21

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): Brain has him as a Bruin (baseline line is his 2025-26 Utah season). If he's still on Utah, revert. New team = real slotting uncertainty, so the up/down PP1 read is a guess (kept in the swing tier).

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

all5v5

We’re projecting assists 45% above last season, 22 to 32.

We project it up

PP TOI

We’re projecting PP TOI 40% above last season, 1.96 to 2.75.

Second-half fade

PP ixG/60

PP ixG/60 finished the year 65% below where it started (1.43 in the first half, 0.50 in the second). The projection leans on how the season ended, so the second half counts for more.

Second-half fade

PTS

all5v5

Points ran at a 36 pace in the second half after 58 in the first, per 82 games.

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

Matt CoronatoRW · Calgary Flames89% match
Will SmithC,RW · San Jose Sharks85% match
shared: PPP
Gavin McKennaLW · Toronto Maple Leafs83% match
shared: PPP
Jackson BlakeRW · Carolina Hurricanes82% match
shared: G

Complementary Forward

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

Michael PezzettaLW,RW · Toronto Maple Leafscovers 2
fills: Hits, PIM
Ross JohnstonLW · St. Louis Bluescovers 2
fills: PIM, Hits
Scott SabourinRW · Tampa Bay Lightningcovers 2
fills: PIM, Hits
Jacob MelansonRW · Seattle Krakencovers 2
fills: Hits, PIM

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 (UTA, traded): André Tourigny full season — no change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	16.20	15.98	16.08	-1%
5v5 TOI	13.18	13.63	13.29	+3%
PP TOI	2.75	1.96	2.09	-6%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 21 · 21 · 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 → 16.20: bigger all-situations role in Boston's top-6
5v5 TOI → 13.18: holds last year's role
PP TOI → 2.75: Raised from 2.10 to a genuine PP1 workload. Both outside sources independently place him on Boston's top unit, and one notes explicitly that a German winger under a German coach could displace E. Lindholm there. 2.75 sits with the rest of Boston's top unit (2.85-3.06) rather than the 2.10 three-year average, which was dragged down by a Utah Q4 that cratered to 1.25.

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	7.25	7.25	7.90	-8%
G/60	0.97	1.07	0.98	+10%
iSH%	13.37	14.76	12.36	+19%
ixG/60	–	0.68	0.78	-13%
iCF/60	–	15.30	15.77	-3%
iSCF/60	–	6.82	7.92	-14%
iHDCF/60	–	2.52	3.18	-21%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 21 · 21 · 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)

TailwindSet a mid-60s point baseline with ~28 goals. · Apples & Ginos Fantasy Hockey

TailwindSupport the existing Boston boost on Peterka, contingent on Pastrnak-line/PP1 deployment. · Apples & Ginos Fantasy Hockey

RiskGoals projected DOWN: iSH% ran hot at 14.8% vs a 12.4% 3-yr mark while 5v5 ixG/60 0.68 (59th pct league-wide) was flat — finishing, not process. Regressing iSH% toward 13.4% pulls the goal rate ~9% down.

TailwindTrajectory: 5v5 ixG/60 climbed 0.60→0.76 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%	10.39	9.82	11.09	-12%
IPP	68.04	76.28	62.54	+22%
1A/60	0.52	0.43	0.63	-32%
2A/60	0.56	0.59	0.50	+19%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 21 · 21 · 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)

RiskIPP spiked to 76.3% vs 62.5% 3-yr — point participation this far above baseline rarely holds; assist share likely gives a little back.

Power play

PP opportunity and finishing — modelled separately from 5v5.

Metric	26-27 proj	2025-26	Prev 3	Diff
PP TOI	2.75	1.96	2.09	-6%
PP iSH%	14.80	16.69	13.42	+24%
PP SOG/60	5.76	6.71	9.99	-33%
PP ixG/60	–	1.16	1.18	-2%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 21 · 21 · 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)

TailwindSupport the existing Boston boost on Peterka, contingent on Pastrnak-line/PP1 deployment. · Apples & Ginos Fantasy Hockey

TailwindPP role projected up: 2.0→2.8 PP TOI/gp (Raised from 2.10 to a genuine PP1 workload. Both outside sources independently place him on Boston's top unit, and one notes explicitly that a German winger under a German coach could displace E. Lindholm there. 2.75 sits with the rest of Boston's top unit (2.85-3.06) rather than the 2.10 three-year average, which was dragged down by a Utah Q4 that cratered to 1.25.) — 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	1.00	1.29	1.23	+5%
Hits/60	0.87	0.86	1.38	-38%
Blks/60	0.81	0.97	0.76	+27%

By quarter — 2025-26 vs 3-yr baseline

GP 21 · 21 · 21 · 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)

RiskHits tailing off: Q4 0.73/60 and 2nd-half 0.47 below the 0.86 season rate — projected DOWN to 0.87/60, weighting the recent decline over the 1.38 3-yr mark.

RiskBlocks tailing off: Q4 0.73/60 and 2nd-half 0.69 below the 0.97 season rate — projected DOWN to 0.81/60, weighting the recent decline over the 0.76 3-yr mark.