Overview
@HockeyBangers
Value over replacement, based on 82 games played.
Ideal for H2H 12-team banger category leagues, 16 roster spots.
| Per 82 GP | 2026-27projection adj | 2025-2669 GP | H232 GP | H137 GP | Prev 3212 GP · 3y |
|---|---|---|---|---|---|
| TOI | 16.89 | 16.73 | 17.10 | 15.01 | 17.33 |
| PP TOI | 1.03 | 0.73 | 0.90 | 0.58 | 1.69 |
| G | 20 | 16 | 19 | 13 | 23 |
| A | ▼22 | 23 | 29 | 17 | 26 |
| PTS | ▼42 | 38 | 48 | 29 | 49 |
| PPP | 3 | 1 | 3 | 0 | 7 |
| SOG | 199 | 189 | 231 | 153 | 217 |
| PIM | 14 | 10 | 8 | 11 | 22 |
| Hits | ▼72 | 68 | 91 | 48 | 86 |
| Blocks | 41 | 44 | 36 | 51 | 46 |
Sample: 69 GP · 935 5v5 min (2025-26) — how much ice time backs these rates
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 engine rides Moore's second half: a projected 13.72 5v5 TOI against a 4-season band of 13.07 to 13.61, built on a 14.92 fourth quarter and a 2.41 points per 60 finish against 1.73 for the full season. Fiala's leg fracture moved Moore up alongside Byfield and Laferriere, and the production followed the promotion. Fiala's healthy now, Zuccarello was added, and the projected depth chart puts Moore back on the third line, so that second-half rate is inflated. Assists faded 12%, landing near 42 points, between our rate model and the more conservative external projection. Shots left as projected. Hits trimmed to 72. His per-82 hits ran 84, 91, 83 and 69 across 2022-26, and the engine projects 82, nearer the multi-year average than the recent mark. 72 leans toward last season's 69 while keeping some of the earlier level.
Metrics worth highlighting
Hits ran at a 91 pace in the second half after 48 in the first, per 82 games.
Assists ran at a 29 pace in the second half after 17 in the first, per 82 games.
PP TOI ran 57% below his 3-year rate last season (0.73 against 1.69).
PIMs/60 ran 57% below his 3-year rate last season (0.38 against 0.89).
Similar & complementary players
Deployment
| Metric | 26-27 proj | 2025-26 | Prev 3 | Diff |
|---|---|---|---|---|
| TOI | 16.89 | 16.73 | 17.33 | -3% |
| 5v5 TOI | 13.72 | 13.56 | 13.31 | +2% |
| PP TOI | 1.03 | 0.73 | 1.69 | -57% |
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 | 8.32 | 8.14 | 9.21 | -12% |
| G/60 | 0.73 | 0.64 | 0.87 | -26% |
| iSH% | 8.79 | 7.86 | 9.45 | -17% |
| ixG/60 | – | 0.79 | 0.91 | -13% |
| iCF/60 | – | 15.78 | 16.90 | -7% |
| iSCF/60 | – | 6.99 | 8.04 | -13% |
| iHDCF/60 | – | 3.66 | 3.78 | -3% |
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% | 8.12 | 8.19 | 8.04 | +2% |
| IPP | 73.47 | 74.89 | 71.57 | +5% |
| 1A/60 | 0.55 | 0.58 | 0.55 | +5% |
| 2A/60 | 0.58 | 0.51 | 0.51 | +0% |
Power play
PP opportunity and finishing — modelled separately from 5v5.
| Metric | 26-27 proj | 2025-26 | Prev 3 | Diff |
|---|---|---|---|---|
| PP TOI | 1.03 | 0.73 | 1.69 | -57% |
| PP iSH% | 5.91 | 0.00 | 7.57 | -100% |
| PP SOG/60 | 9.29 | 9.57 | 11.06 | -14% |
| PP ixG/60 | – | 0.95 | 2.25 | -58% |
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 | 0.44 | 0.38 | 0.89 | -57% |
| Hits/60 | 3.90 | 3.33 | 4.51 | -26% |
| Blks/60 | 1.90 | 2.05 | 1.96 | +5% |