Fantasy tools
Stack Finder: best line and PP1 stacks for Wednesday, Apr 22
Data updated:
Top 10 stacks
Matt Duchene58%, Mikko Rantanen99%, Jason Robertson100%, Miro Heiskanen99%, Wyatt Johnston100%
Matchup factors →Zach Hyman95%, Connor McDavid100%, Matt Savoie36%
Matchup factors →Chris Kreider63%, Troy Terry46%, Leo Carlsson95%
Matchup factors →Alex Killorn5.1%, Mikael Granlund53%, Beckett Sennecke95%
Matchup factors →Matt Duchene58%, Jason Robertson100%, Mavrik Bourque33%
Matchup factors →Christian Dvorak15%, Travis Konecny91%, Porter Martone87%
Matchup factors →Evgeni Malkin86%, Rickard Rakell81%, Tommy Novak39%
Matchup factors →Evgeni Malkin86%, Sidney Crosby100%, Erik Karlsson95%, Bryan Rust84%, Rickard Rakell81%
Matchup factors →Anthony Mantha45%, Elmer Soderblom4.8%, Ben Kindel50%
Matchup factors →Owen Tippett77%, Trevor Zegras83%, Tyson Foerster38%
Matchup factors →
By game
PIT @ PHI
Christian Dvorak15%, Travis Konecny91%, Porter Martone87%
9.3 min/game · 2.63 xGF/60 · P(intact) 82%
- PIT 5v5 xGA/60 +5%
- Together 2 of last 3
- DK correlation .27
Evgeni Malkin86%, Rickard Rakell81%, Tommy Novak39%
7.1 min/game · 3.94 xGF/60 · P(intact) 82%
- PHI 5v5 xGA/60 −10%
- Together 2 of last 3
- DK correlation .28
Evgeni Malkin86%, Sidney Crosby100%, Erik Karlsson95%, Bryan Rust84%, Rickard Rakell81%
3.3 min/game · 7.74 xGF/60 · P(intact) 82%
- PHI shorthanded time −1%
- PHI PK xGA/60 −3%
- Together 2 of last 3
- DK correlation .20
Anthony Mantha45%, Elmer Soderblom4.8%, Ben Kindel50%
8.9 min/game · 2.56 xGF/60 · P(intact) 95%
- PHI 5v5 xGA/60 −10%
- Together 3 of last 3
- DK correlation .27
Owen Tippett77%, Trevor Zegras83%, Tyson Foerster38%
6.9 min/game · 2.82 xGF/60 · P(intact) 82%
- PIT 5v5 xGA/60 +5%
- Together 2 of last 3
- DK correlation .28
Sidney Crosby100%, Bryan Rust84%, Egor Chinakhov50%
8.3 min/game · 2.57 xGF/60 · P(intact) 82%
- PHI 5v5 xGA/60 −10%
- Together 2 of last 3
- DK correlation .28
Sean Couturier8.3%, Luke Glendening0.0%, Garnet Hathaway4.0%
8.1 min/game · 2.21 xGF/60 · P(intact) 82%
- PIT 5v5 xGA/60 +5%
- Together 2 of last 3
- DK correlation .28
Noah Cates15%, Trevor Zegras83%, Jamie Drysdale52%, Tyson Foerster38%, Porter Martone87%
2.2 min/game · 7.76 xGF/60 · P(intact) 82%
- PIT shorthanded time +0%
- PIT PK xGA/60 −7%
- Together 2 of last 3
- DK correlation .18
Noel Acciari4.1%, Connor Dewar4.2%, Blake Lizotte0.2%
6.6 min/game · 2.42 xGF/60 · P(intact) 82%
- PHI 5v5 xGA/60 −10%
- Together 2 of last 3
- DK correlation .29
Noah Cates15%, Denver Barkey14%, Matvei Michkov83%
6.0 min/game · 1.99 xGF/60 · P(intact) 82%
- PIT 5v5 xGA/60 +5%
- Together 2 of last 3
- DK correlation .27
DAL @ MIN
Matt Duchene58%, Mikko Rantanen99%, Jason Robertson100%, Miro Heiskanen99%, Wyatt Johnston100%
5.5 min/game · 9.15 xGF/60 · P(intact) 82%
- MIN shorthanded time +5%
- MIN PK xGA/60 +7%
- Together 2 of last 3
- DK correlation .21
Matt Duchene58%, Jason Robertson100%, Mavrik Bourque33%
10.2 min/game · 3.07 xGF/60 · P(intact) 95%
- MIN 5v5 xGA/60 −3%
- Together 3 of last 3
- DK correlation .28
Marcus Johansson0.5%, Joel Eriksson Ek80%, Matt Boldy100%
7.3 min/game · 2.55 xGF/60 · P(intact) 82%
- DAL 5v5 xGA/60 −1%
- Together 2 of last 3
- DK correlation .27
Mikko Rantanen99%, Sam Steel5.7%, Wyatt Johnston100%
10.0 min/game · 2.92 xGF/60 · P(intact) 23%
- MIN 5v5 xGA/60 −3%
- Together 2 of last 3
- DK correlation .29
Mats Zuccarello47%, Joel Eriksson Ek80%, Kirill Kaprizov98%, Quinn Hughes100%, Matt Boldy100%
4.7 min/game · 10.37 xGF/60 · P(intact) 12%
- DAL shorthanded time +8%
- DAL PK xGA/60 −6%
- Together 1 of last 3
- DK correlation .18
Vladimir Tarasenko8.5%, Bobby Brink14%, Danila Yurov33%
12.8 min/game · 3.10 xGF/60 · P(intact) 12%
- DAL 5v5 xGA/60 −1%
- Together 1 of last 3
- DK correlation .28
Mats Zuccarello47%, Ryan Hartman36%, Kirill Kaprizov98%
11.2 min/game · 3.40 xGF/60 · P(intact) 12%
- DAL 5v5 xGA/60 −1%
- Together 1 of last 3
- DK correlation .27
Jamie Benn20%, Michael Bunting4.4%, Justin Hryckowian18%
8.2 min/game · 2.77 xGF/60 · P(intact) 12%
- MIN 5v5 xGA/60 −3%
- Together 1 of last 3
- DK correlation .28
Radek Faksa0.1%, Adam Erne0.0%, Oskar Bäck0.2%
8.6 min/game · 2.31 xGF/60 · P(intact) 12%
- MIN 5v5 xGA/60 −3%
- Together 1 of last 3
- DK correlation .29
Michael McCarron8.2%, Yakov Trenin19%, Nico Sturm0.1%
8.9 min/game · 1.88 xGF/60 · P(intact) 12%
- DAL 5v5 xGA/60 −1%
- Together 1 of last 3
- DK correlation .27
ANA @ EDM
Zach Hyman95%, Connor McDavid100%, Matt Savoie36%
10.8 min/game · 3.40 xGF/60 · P(intact) 82%
- ANA 5v5 xGA/60 +10%
- Together 2 of last 3
- DK correlation .27
Chris Kreider63%, Troy Terry46%, Leo Carlsson95%
10.8 min/game · 3.42 xGF/60 · P(intact) 82%
- EDM 5v5 xGA/60 −1%
- Together 2 of last 3
- DK correlation .28
Alex Killorn5.1%, Mikael Granlund53%, Beckett Sennecke95%
10.0 min/game · 3.15 xGF/60 · P(intact) 95%
- EDM 5v5 xGA/60 −1%
- Together 3 of last 3
- DK correlation .28
Alex Killorn5.1%, Ryan Poehling6.7%, Jackson LaCombe97%, Mason McTavish51%, Cutter Gauthier98%
1.9 min/game · 8.15 xGF/60 · P(intact) 95%
- EDM shorthanded time −14%
- EDM PK xGA/60 +6%
- Together 3 of last 3
- DK correlation .20
Ryan Poehling6.7%, Mason McTavish51%, Cutter Gauthier98%
7.3 min/game · 2.07 xGF/60 · P(intact) 95%
- EDM 5v5 xGA/60 −1%
- Together 3 of last 3
- DK correlation .27
Trent Frederic4.9%, Colton Dach10%, Josh Samanski3.2%
9.8 min/game · 2.91 xGF/60 · P(intact) 23%
- ANA 5v5 xGA/60 +10%
- Together 2 of last 3
- DK correlation .28
Ryan Nugent-Hopkins75%, Connor McDavid100%, Jack Roslovic33%, Evan Bouchard100%, Vasily Podkolzin83%
4.3 min/game · 11.02 xGF/60 · P(intact) 12%
- ANA shorthanded time +4%
- ANA PK xGA/60 +4%
- Together 1 of last 3
- DK correlation .21
Ryan Nugent-Hopkins75%, Jack Roslovic33%, Vasily Podkolzin83%
11.5 min/game · 3.36 xGF/60 · P(intact) 12%
- ANA 5v5 xGA/60 +10%
- Together 1 of last 3
- DK correlation .28
Adam Henrique0.4%, Curtis Lazar0.0%, Kasperi Kapanen16%
7.6 min/game · 1.70 xGF/60 · P(intact) 23%
- ANA 5v5 xGA/60 +10%
- Together 2 of last 3
- DK correlation .28
How it works
- 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.
- 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.
- 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.
- 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.
- 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.