Per 82 GP	2026-27projection adj	2025-2679 GP	H241 GP	H138 GP	Prev 3212 GP · 3y
TOI	17.99	18.45	17.65	17.74	16.13
PP TOI	3.14	3.22	3.54	2.88	2.25
G	▲29	33	25	42	20
A	25	27	27	27	26
PTS	▲54	60	52	69	46
PPP	19	22	12	32	14
SOG	169	170	162	179	154
PIM	44	44	40	47	51
Hits	70	57	44	71	82
Blocks	32	25	23	27	36

Sample: 79 GP · 1,142 5v5 min (2025-26) — how much ice time backs these rates

Positional rankingLeft wing · league-wide (of 281)

49Vasily Podkolzin47

50Jake DeBrusk45

51Jack McBain45

52Tyler Bertuzzi44

53Eeli Tolvanen42

54Pavol Regenda42

55Brayden Schenn42

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): The 32-goal season does not repeat, but the projected 27 over-faded it by treating his power-play finishing as the same fluke as his even-strength finishing. His PP shooting was actually BELOW what his chance quality implied, which is what a net-front specialist looks like when the role is real. Small lift to ~29, matching an independent outside read. Low conviction, deliberately small.

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 fade

PPP

Power play points ran at a 12 pace in the second half after 32 in the first, per 82 games.

Above his 3-year rate

iSH%

iSH% ran 81% above his 3-year rate last season (17.86 against 9.87).

Above his 3-year rate

PP TOI

PP TOI ran 43% above his 3-year rate last season (3.22 against 2.25).

Second-half fade

all5v5

Goals ran at a 25 pace in the second half after 42 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

Jason ZuckerLW,RW · Buffalo Sabres88% match
shared: PIM, PPP
Logan CooleyC · Utah Mammoth84% match
Chris KreiderLW · Anaheim Ducks84% match
shared: G, PPP
Mason McTavishC · St. Louis Blues83% match
shared: PIM

Complementary Forward

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

Aleksander BarkovC · Florida Pantherscovers 3
fills: A, SOG, Hits
Jesper BrattRW · New Jersey Devilscovers 2
fills: A, SOG
Dylan HollowayLW · St. Louis Bluescovers 3
fills: Hits, A, SOG
Ivan BarbashevLW · Vegas Golden Knightscovers 2
fills: Hits, 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 · Jeff Blashill (CHI)

Last year: Jeff Blashill full season (1st yr) — no change

Metric	26-27 proj	2025-26	Prev 3	Diff
TOI	17.99	18.45	16.13	+14%
5v5 TOI	14.15	14.46	13.37	+8%
PP TOI	3.14	3.22	2.25	+43%

By quarter — 2025-26 vs 3-yr baseline

GP 17 · 21 · 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 → 17.99: holds last year's role
5v5 TOI → 14.15: holds last year's role
PP TOI → 3.14: same coach (Jeff Blashill) — carries the elevated finish (2nd half 3.5, Q4 3.4) over the full-year 3.2

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	5.88	5.88	6.46	-9%
G/60	0.87	1.05	0.64	+65%
iSH%	14.82	17.86	9.87	+81%
ixG/60	–	0.81	0.80	+1%
iCF/60	–	10.72	12.05	-11%
iSCF/60	–	7.36	7.11	+3%
iHDCF/60	–	3.84	3.90	-1%

By quarter — 2025-26 vs 3-yr baseline

GP 17 · 21 · 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)

RiskGoals projected DOWN: iSH% ran hot at 17.9% vs a 9.9% 3-yr mark while 5v5 ixG/60 0.81 (78th pct league-wide) was flat — finishing, not process. Regressing iSH% toward 14.8% pulls the goal rate ~17% 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%	10.19	11.64	9.22	+26%
IPP	61.26	61.54	60.93	+1%
1A/60	0.47	0.42	0.61	-32%
2A/60	0.36	0.37	0.40	-8%

By quarter — 2025-26 vs 3-yr baseline

GP 17 · 21 · 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)

RiskOn-ice SH% hot at 11.6% vs a 9.2% 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	3.14	3.22	2.25	+43%
PP iSH%	24.30	22.88	25.33	-10%
PP SOG/60	11.11	11.32	9.45	+20%
PP ixG/60	–	3.05	2.16	+41%

By quarter — 2025-26 vs 3-yr baseline

GP 17 · 21 · 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)

ContextPP role steady at ~3.1 PP TOI/gp.

TailwindPP chance quality up (PP ixG/60 3.05 vs 2.16) — 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	1.50	1.68	1.84	-9%
Hits/60	3.24	2.57	4.24	-39%
Blks/60	1.44	1.21	1.93	-37%

By quarter — 2025-26 vs 3-yr baseline

GP 17 · 21 · 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 2.57/60 (32nd pct league-wide) → 3.24 projected.

RiskBlocks tailing off: Q4 0.88/60 and 2nd-half 1.13 below the 1.21 season rate — projected DOWN to 1.44/60, weighting the recent decline over the 1.93 3-yr mark.