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 | 2025-26thin | H22 GP | H125-26 | Prev 3thin |
|---|---|---|---|---|---|
| TOI | 15.50 | – | – | – | – |
| PP TOI | 1.60 | – | – | – | – |
| G | 15 | – | – | – | – |
| A | 31 | – | – | – | – |
| PTS | 46 | – | – | – | – |
| PPP | 12 | – | – | – | – |
| SOG | 145 | – | – | – | – |
| PIM | 23 | – | – | – | – |
| Hits | 35 | – | – | – | – |
| Blocks | 20 | – | – | – | – |
Sample: 2 GP · 29 5v5 min (2025-26) — how much ice time backs these rates
Manual baseline: no usable NHL sample to regress, so the line is set from a prospect projection (role, upside comparable, multi-year ceiling) blended with any 2025-26 NHL data. Not an engine regression; edit in adjustments.json.
Context-adjusted (▲/▼ vs the rate-model baseline): [LOW-CONF - 2 NHL GP; mostly a role-based estimate] Rookie baseline: projected role (makes the team, playmaking C; one day could become someone like Jack Hughes) blended with 2025-26 NHL (2 GP) at w=0.05. Per-82 line; GP/availability is separate. SOG raised 128 -> 145: he is a high-volume shooter (10th in NCAA scoring as a sophomore) and the outside read is 164, so this splits the difference rather than adopting it. He is on the manual-baseline path, so deploy bets and PP-tier placement are both inert for him — these set values ARE the projection. Tune here.
The projection above leans on a small NHL sample plus a role-based estimate. Trend and per-category charts are hidden until there's a fuller season to chart.