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Stack Finder: best line and PP1 stacks for Sunday, May 3

Every forward line and first power-play unit on the Sunday, May 3 slate, ranked by expected goals tonight against the opponent's defense, penalty kill and likely goalie. Top stack: TBL PP1 (Kucherov–Guentzel–Point–Raddysh–Hagel) vs MTL.

Data updated:

Stacks with a player who is

Top 10 stacks

  1. #1TBLPP1vs MTL0.80 xG

    Nikita Kucherov100%, Jake Guentzel100%, Brayden Point95%, Darren Raddysh99%, Brandon Hagel100%

    Matchup factors →
  2. #2UTAL1vs VGK0.64 xG

    Nick Schmaltz96%, Lawson Crouse34%, Clayton Keller100%

    Matchup factors →
  3. #3BUFL1vs BOS0.62 xG

    Alex Tuch94%, Tage Thompson100%, Peyton Krebs17%

    Matchup factors →
  4. #4UTAL2vs VGK0.58 xG

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

    Matchup factors →
  5. #5UTAPP1vs VGK0.57 xG

    Nick Schmaltz96%, Clayton Keller100%, Mikhail Sergachev98%, Dylan Guenther100%, Logan Cooley94%

    Matchup factors →
  6. #6BOSL1vs BUF0.57 xG

    David Pastrnak100%, Pavel Zacha74%, Marat Khusnutdinov11%

    Matchup factors →
  7. #7TBLL2vs MTL0.55 xG

    Nikita Kucherov100%, Anthony Cirelli49%, Brandon Hagel100%

    Matchup factors →
  8. #8MTLPP1vs TBL0.54 xG

    Nick Suzuki100%, Cole Caufield100%, Lane Hutson99%, Juraj Slafkovský99%, Ivan Demidov91%

    Matchup factors →
  9. #9BUFL2vs BOS0.53 xG

    Jason Zucker22%, Ryan McLeod24%, Jack Quinn50%

    Matchup factors →
  10. #10LAKL1vs COL0.52 xG

    Trevor Moore8.9%, Quinton Byfield85%, Alex Laferriere67%

    Matchup factors →

By game

BOS @ BUF

MTL @ TBL

LAK @ COL

UTA @ VGK

MIN @ COL

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.