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Stack Finder: best line and PP1 stacks for Sunday, Apr 12

Every forward line and first power-play unit on the Sunday, Apr 12 slate, ranked by expected goals tonight against the opponent's defense, penalty kill and likely goalie. Top stack: NYI PP1 (Schenn–Horvat–Barzal–Ritchie–Schaefer) vs MTL.

Data updated:

Stacks with a player who is

Top 10 stacks

  1. #1NYIPP1vs MTL0.64 xG

    Brayden Schenn31%, Bo Horvat90%, Mathew Barzal82%, Calum Ritchie31%, Matthew Schaefer100%

    Matchup factors →
  2. #2UTAL1vs CGY0.64 xG

    Kailer Yamamoto0.2%, Dylan Guenther100%, Logan Cooley94%

    Matchup factors →
  3. #3MTLPP1vs NYI0.63 xG

    Nick Suzuki100%, Cole Caufield100%, Lane Hutson99%, Juraj Slafkovský98%, Ivan Demidov91%

    Matchup factors →
  4. #4BOSL1vs CBJ0.61 xG

    Elias Lindholm43%, David Pastrnak100%, Morgan Geekie95%

    Matchup factors →
  5. #5NJDL1vs OTT0.61 xG

    Connor Brown5.8%, Jesper Bratt95%, Jack Hughes100%

    Matchup factors →
  6. #6UTAL2vs CGY0.55 xG

    Nick Schmaltz96%, Lawson Crouse34%, Clayton Keller100%

    Matchup factors →
  7. #7NJDL2vs OTT0.54 xG

    Timo Meier80%, Nico Hischier96%, Dawson Mercer23%

    Matchup factors →
  8. #8CBJPP1vs BOS0.52 xG

    Charlie Coyle49%, Zach Werenski100%, Mason Marchment46%, Kirill Marchenko99%, Adam Fantilli92%

    Matchup factors →
  9. #9OTTL1vs NJD0.49 xG

    Brady Tkachuk100%, Dylan Cozens89%, Ridly Greig15%

    Matchup factors →
  10. #10MTLL1vs NYI0.49 xG

    Nick Suzuki100%, Cole Caufield100%, Juraj Slafkovský98%

    Matchup factors →

By game

PIT @ WSH

MTL @ NYI

BOS @ CBJ

OTT @ NJD

VAN @ ANA

UTA @ CGY

How it works

  1. Lines and PP1 come from each team's last three games of shift data: the forward trio with the most 5-on-5 time together, and the power-play five with the most time together.
  2. Unit strength is expected goals for per 60 minutes, recent games plus the season, shrunk toward league average so a hot two-game sample does not dominate.
  3. Matchup: the opponent's 5-on-5 expected goals against per 60 (for lines) or its penalty-kill rate and shorthanded minutes (for PP1), relative to the league.
  4. Goalie: the likely opposing starter from our goalie start model, weighted by probability, with his save % shrunk toward league average; shot-class save % when available.
  5. Stack score = rate × minutes × P(unit intact) × matchup × goalie, in expected goals for tonight, so lines and power plays rank on one scale.

Methodology: How we detect lines · Expected goals · Goalie shot classes · Goalie start model

Frequently asked questions

What is a stack in fantasy hockey?

A stack is a group of teammates who play together, usually a forward line or the first power-play unit, so one goal pays several of your players at once. It is the main strategy in daily fantasy hockey.

How are stacks ranked?

Each unit gets an expected-goals number for tonight: how many chances it creates per 60 minutes (recent games plus season, shrunk toward league average), how many minutes it plays, how likely it is to stay together, how leaky the opponent is at 5-on-5 or shorthanded, and how good the likely opposing goalie is.

Where do the lines come from?

From the NHL shift charts of each team's last three games: the three forwards who share the most 5-on-5 ice time form a line, and the five skaters with the most power-play time together form PP1.

Why does it say "shot-based"?

While a season is being reprocessed with our expected-goals model, unit rates fall back to shots on goal times a league-average 0.075 xG per shot. The ranking logic is the same.