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NHL Stack Finder: Wednesday, Nov 11
Data updated:
Top 10 stacks
Evgeni Malkin84%, Tommy Novak21%, Egor Chinakhov49%
Matchup factors →Leon Draisaitl100%, Connor McDavid100%, Vasily Podkolzin78%
Matchup factors →Sidney Crosby100%, Rickard Rakell82%, Nick Robertson31%
Matchup factors →Vincent Trocheck89%, Nick Schmaltz95%, Clayton Keller100%
Matchup factors →Mika Zibanejad98%, Alexis Lafrenière81%, Gabe Perreault54%
Matchup factors →Anders Lee29%, Dylan Guenther99%, Logan Cooley94%
Matchup factors →Jack Quinn47%, Noah Ostlund26%, Zach Benson56%
Matchup factors →Tomas Hertl84%, Victor Olofsson15%, Trevor Connelly34%
Matchup factors →Mark Stone93%, Ivan Barbashev68%, Jack Eichel99%
Matchup factors →Mason Marchment47%, Will Smith95%, Macklin Celebrini100%
Matchup factors →
By game
TBL @ BUF
Jack Quinn47%, Noah Ostlund26%, Zach Benson56%
12.4 min/game · 3.49 xGF/60 · P(intact) 82%
- TBL 5v5 xGA/60 −6%
- vs Andrei Vasilevskiy .912 (97% to start)
- Vasilevskiy .866 on rebounds
- Together 2 of last 3
- DK correlation .28
Tage Thompson100%, Josh Norris38%, Josh Doan61%
11.8 min/game · 3.20 xGF/60 · P(intact) 82%
- TBL 5v5 xGA/60 −6%
- vs Andrei Vasilevskiy .912 (97% to start)
- Vasilevskiy .866 on rebounds
- Together 2 of last 3
- DK correlation .28
John Carlson99%, Nikita Kucherov100%, Jake Guentzel100%, Brayden Point95%, Brandon Hagel100%
4.7 min/game · 6.73 xGF/60 · P(intact) 82%
- BUF shorthanded time −13%
- BUF PK xGA/60 −1%
- vs Ukko-Pekka Luukkonen .905 (84% to start)
- Luukkonen .867 on rebounds
- Together 2 of last 3
- DK correlation .28
Nikita Kucherov100%, Brayden Point95%, Gage Goncalves11%
10.0 min/game · 3.55 xGF/60 · P(intact) 68%
- BUF 5v5 xGA/60 +0%
- vs Ukko-Pekka Luukkonen .905 (84% to start)
- Luukkonen .867 on rebounds
- Together 1 of last 3
- DK correlation .29
Jake Guentzel100%, Anthony Cirelli51%, Brandon Hagel100%
7.9 min/game · 3.45 xGF/60 · P(intact) 82%
- BUF 5v5 xGA/60 +0%
- vs Ukko-Pekka Luukkonen .905 (84% to start)
- Luukkonen .867 on rebounds
- Together 2 of last 3
- DK correlation .27
Ryan McLeod26%, Peyton Krebs19%, Konsta Helenius40%
8.2 min/game · 3.76 xGF/60 · P(intact) 82%
- TBL 5v5 xGA/60 −6%
- vs Andrei Vasilevskiy .912 (97% to start)
- Vasilevskiy .866 on rebounds
- Together 2 of last 3
- DK correlation .28
Tage Thompson100%, Rasmus Dahlin100%, Jack Quinn47%, Josh Doan61%, Zach Benson56%
2.6 min/game · 8.35 xGF/60 · P(intact) 95%
- TBL shorthanded time +15%
- TBL PK xGA/60 −5%
- vs Andrei Vasilevskiy .912 (97% to start)
- Vasilevskiy .866 on rebounds
- Together 3 of last 3
- DK correlation .20
Sam Carrick0.1%, Beck Malenstyn4.1%, Jiri Kulich25%
5.8 min/game · 1.61 xGF/60 · P(intact) 82%
- TBL 5v5 xGA/60 −6%
- vs Andrei Vasilevskiy .912 (97% to start)
- Vasilevskiy .866 on rebounds
- Together 2 of last 3
- DK correlation .27
Jeffrey Viel4.0%, Pontus Holmberg0.1%, Conor Geekie20%
1.7 min/game · 3.30 xGF/60 · P(intact) 68%
- BUF 5v5 xGA/60 +0%
- vs Ukko-Pekka Luukkonen .905 (84% to start)
- Luukkonen .867 on rebounds
- Together 1 of last 3
Yanni Gourde4.9%, Zemgus Girgensons3.2%, Nick Paul8.1%
10.0 min/game · 2.10 xGF/60 · P(intact) 12%
- BUF 5v5 xGA/60 +0%
- vs Ukko-Pekka Luukkonen .905 (84% to start)
- Luukkonen .867 on rebounds
- Together 1 of last 3
- DK correlation .29
NYR @ CGY
Mika Zibanejad98%, Alexis Lafrenière81%, Gabe Perreault54%
11.0 min/game · 2.82 xGF/60 · P(intact) 95%
- CGY 5v5 xGA/60 +8%
- vs Dustin Wolf .895 (90% to start)
- Wolf .844 on rebounds
- Together 3 of last 3
- DK correlation .28
Mika Zibanejad98%, J.T. Miller92%, Adam Fox99%, Pavel Dorofeyev93%, Alexis Lafrenière81%
3.8 min/game · 6.75 xGF/60 · P(intact) 95%
- CGY shorthanded time +27%
- CGY PK xGA/60 +3%
- vs Dustin Wolf .895 (90% to start)
- Wolf .844 on rebounds
- Together 3 of last 3
- DK correlation .18
Eeli Tolvanen38%, Will Cuylle64%, Noah Laba11%
7.6 min/game · 2.27 xGF/60 · P(intact) 95%
- CGY 5v5 xGA/60 +8%
- vs Dustin Wolf .895 (90% to start)
- Wolf .844 on rebounds
- Together 3 of last 3
- DK correlation .29
Morgan Frost23%, Joel Farabee11%, Matt Coronato40%, Zayne Parekh68%, Matvei Gridin40%
1.8 min/game · 6.68 xGF/60 · P(intact) 95%
- NYR shorthanded time −3%
- NYR PK xGA/60 +9%
- vs Igor Shesterkin .913 (54% to start)
- Shesterkin .845 on rebounds
- Together 3 of last 3
- DK correlation .20
Martin Pospisil6.4%, Adam Klapka9.8%, Maxim Tsyplakov13%
7.2 min/game · 1.87 xGF/60 · P(intact) 95%
- NYR 5v5 xGA/60 −3%
- vs Igor Shesterkin .913 (54% to start)
- Shesterkin .845 on rebounds
- Together 3 of last 3
- DK correlation .27
J.T. Miller92%, Oliver Bjorkstrand19%, Pavel Dorofeyev93%
7.8 min/game · 3.23 xGF/60 · P(intact) 23%
- CGY 5v5 xGA/60 +8%
- vs Dustin Wolf .895 (90% to start)
- Wolf .844 on rebounds
- Together 2 of last 3
Morgan Frost23%, Matt Coronato40%, Matvei Gridin40%
10.5 min/game · 2.40 xGF/60 · P(intact) 23%
- NYR 5v5 xGA/60 −3%
- vs Igor Shesterkin .913 (54% to start)
- Shesterkin .845 on rebounds
- Together 2 of last 3
- DK correlation .28
Mikael Backlund14%, Joel Farabee11%, Samuel Honzek14%
8.3 min/game · 2.66 xGF/60 · P(intact) 23%
- NYR 5v5 xGA/60 −3%
- vs Igor Shesterkin .913 (54% to start)
- Shesterkin .845 on rebounds
- Together 2 of last 3
- DK correlation .27
Ryan Strome4.0%, Yegor Sharangovich7.8%, Connor Zary10%
10.9 min/game · 2.45 xGF/60 · P(intact) 12%
- NYR 5v5 xGA/60 −3%
- vs Igor Shesterkin .913 (54% to start)
- Shesterkin .845 on rebounds
- Together 1 of last 3
- DK correlation .27
Joseph Veleno4.9%, Tye Kartye7.2%, Jaroslav Chmelar0.1%
5.3 min/game · 1.87 xGF/60 · P(intact) 23%
- CGY 5v5 xGA/60 +8%
- vs Dustin Wolf .895 (90% to start)
- Wolf .844 on rebounds
- Together 2 of last 3
PHI @ EDM
Leon Draisaitl100%, Connor McDavid100%, Vasily Podkolzin78%
13.2 min/game · 4.18 xGF/60 · P(intact) 82%
- PHI 5v5 xGA/60 −8%
- vs Joseph Woll .901 (52% to start)
- Woll .883 on rebounds
- Together 2 of last 3
- DK correlation .28
Leon Draisaitl100%, Kasperi Kapanen12%, Connor McDavid100%, Evan Bouchard100%, Vasily Podkolzin78%
3.5 min/game · 8.43 xGF/60 · P(intact) 82%
- PHI shorthanded time +1%
- PHI PK xGA/60 +1%
- vs Joseph Woll .901 (52% to start)
- Woll .883 on rebounds
- Together 2 of last 3
- DK correlation .21
Travis Konecny92%, Trevor Zegras86%, Jamie Drysdale55%, Tyson Foerster41%, Matvei Michkov86%
3.5 min/game · 7.25 xGF/60 · P(intact) 68%
- EDM shorthanded time −20%
- EDM PK xGA/60 +12%
- vs Tristan Jarry .878 (46% to start)
- Jarry .833 on rebounds
- Together 1 of last 3
- DK correlation .19
Trent Frederic4.0%, Isaac Howard30%, Josh Samanski3.2%
5.3 min/game · 3.23 xGF/60 · P(intact) 82%
- PHI 5v5 xGA/60 −8%
- vs Joseph Woll .901 (52% to start)
- Woll .883 on rebounds
- Together 2 of last 3
- DK correlation .27
Mathieu Joseph3.2%, Alex Formenton9.7%, Owen Michaels5.7%
10.1 min/game · 1.65 xGF/60 · P(intact) 82%
- PHI 5v5 xGA/60 −8%
- vs Joseph Woll .901 (52% to start)
- Woll .883 on rebounds
- Together 2 of last 3
Kasperi Kapanen12%, Max Jones0.1%, Colton Dach11%
8.0 min/game · 1.34 xGF/60 · P(intact) 82%
- PHI 5v5 xGA/60 −8%
- vs Joseph Woll .901 (52% to start)
- Woll .883 on rebounds
- Together 2 of last 3
Sean Couturier9.2%, Noel Acciari3.3%, Carl Grundstrom0.1%
6.3 min/game · 1.91 xGF/60 · P(intact) 23%
- EDM 5v5 xGA/60 +2%
- vs Tristan Jarry .878 (46% to start)
- Jarry .833 on rebounds
- Together 2 of last 3
- DK correlation .29
Noah Cates18%, Tyson Foerster41%, Matvei Michkov86%
7.9 min/game · 2.82 xGF/60 · P(intact) 12%
- EDM 5v5 xGA/60 +2%
- vs Tristan Jarry .878 (46% to start)
- Jarry .833 on rebounds
- Together 1 of last 3
- DK correlation .28
Christian Dvorak16%, Travis Konecny92%, Porter Martone89%
6.6 min/game · 2.50 xGF/60 · P(intact) 12%
- EDM 5v5 xGA/60 +2%
- vs Tristan Jarry .878 (46% to start)
- Jarry .833 on rebounds
- Together 1 of last 3
- DK correlation .27
Owen Tippett78%, Trevor Zegras86%, Alex Bump15%
4.7 min/game · 1.83 xGF/60 · P(intact) 12%
- EDM 5v5 xGA/60 +2%
- vs Tristan Jarry .878 (46% to start)
- Jarry .833 on rebounds
- Together 1 of last 3
- DK correlation .28
UTA @ VGK
Vincent Trocheck89%, Nick Schmaltz95%, Clayton Keller100%
10.9 min/game · 3.40 xGF/60 · P(intact) 95%
- VGK 5v5 xGA/60 −12%
- vs Carter Hart .889 (50% to start)
- Hart .880 on other shots
- Together 3 of last 3
- DK correlation .29
Anders Lee29%, Dylan Guenther99%, Logan Cooley94%
9.6 min/game · 3.52 xGF/60 · P(intact) 95%
- VGK 5v5 xGA/60 −12%
- vs Carter Hart .889 (50% to start)
- Hart .880 on other shots
- Together 3 of last 3
- DK correlation .28
Tomas Hertl84%, Victor Olofsson15%, Trevor Connelly34%
7.3 min/game · 4.39 xGF/60 · P(intact) 95%
- UTA 5v5 xGA/60 −3%
- vs Karel Vejmelka .897 (96% to start)
- Vejmelka .735 on rebounds
- Together 3 of last 3
Mark Stone93%, Ivan Barbashev68%, Jack Eichel99%
9.5 min/game · 3.36 xGF/60 · P(intact) 95%
- UTA 5v5 xGA/60 −3%
- vs Karel Vejmelka .897 (96% to start)
- Vejmelka .735 on rebounds
- Together 3 of last 3
- DK correlation .28
Mark Stone93%, Tomas Hertl84%, Shea Theodore92%, Jack Eichel99%, Mitch Marner99%
3.4 min/game · 7.83 xGF/60 · P(intact) 95%
- UTA shorthanded time −6%
- UTA PK xGA/60 +0%
- vs Karel Vejmelka .897 (96% to start)
- Vejmelka .735 on rebounds
- Together 3 of last 3
- DK correlation .18
Lawson Crouse36%, Barrett Hayton10%, Jack McBain17%
8.7 min/game · 3.23 xGF/60 · P(intact) 95%
- VGK 5v5 xGA/60 −12%
- vs Carter Hart .889 (50% to start)
- Hart .880 on other shots
- Together 3 of last 3
- DK correlation .28
William Karlsson24%, Mitch Marner99%, Brett Howden16%
9.6 min/game · 2.48 xGF/60 · P(intact) 95%
- UTA 5v5 xGA/60 −3%
- vs Karel Vejmelka .897 (96% to start)
- Vejmelka .735 on rebounds
- Together 3 of last 3
- DK correlation .27
Kevin Stenlund0.1%, Michael Carcone6.6%, Daniil But21%
7.9 min/game · 2.67 xGF/60 · P(intact) 95%
- VGK 5v5 xGA/60 −12%
- vs Carter Hart .889 (50% to start)
- Hart .880 on other shots
- Together 3 of last 3
- DK correlation .28
Nick Schmaltz95%, Clayton Keller100%, Mikhail Sergachev98%, Dylan Guenther99%, Logan Cooley94%
2.1 min/game · 9.64 xGF/60 · P(intact) 95%
- VGK shorthanded time +1%
- VGK PK xGA/60 −14%
- vs Carter Hart .889 (50% to start)
- Hart .880 on other shots
- Together 3 of last 3
- DK correlation .21
Nic Dowd3.2%, Marc Gatcomb5.7%, Braeden Bowman16%
5.7 min/game · 2.16 xGF/60 · P(intact) 95%
- UTA 5v5 xGA/60 −3%
- vs Karel Vejmelka .897 (96% to start)
- Vejmelka .735 on rebounds
- Together 3 of last 3
NSH @ ANA
A.J. Greer7.6%, Cutter Gauthier98%, Leo Carlsson94%
9.7 min/game · 3.08 xGF/60 · P(intact) 82%
- NSH 5v5 xGA/60 +9%
- vs Justus Annunen .907 (40% to start)
- Annunen .821 on rebounds
- Together 2 of last 3
- DK correlation .27
Alex Killorn5.1%, Mikael Granlund52%, Beckett Sennecke94%
8.7 min/game · 2.77 xGF/60 · P(intact) 95%
- NSH 5v5 xGA/60 +9%
- vs Justus Annunen .907 (40% to start)
- Annunen .821 on rebounds
- Together 3 of last 3
- DK correlation .28
Filip Forsberg99%, Nils Hoglander4.0%, Matthew Wood31%
5.9 min/game · 2.97 xGF/60 · P(intact) 95%
- ANA 5v5 xGA/60 +2%
- vs Lukas Dostal .889 (90% to start)
- Dostal .878 on cycle shots
- Together 2 of last 2
- DK correlation .28
Steven Stamkos94%, Ryan O'Reilly84%, Alexander Kerfoot3.2%
6.3 min/game · 2.75 xGF/60 · P(intact) 95%
- ANA 5v5 xGA/60 +2%
- vs Lukas Dostal .889 (90% to start)
- Dostal .878 on cycle shots
- Together 2 of last 2
- DK correlation .30
Steven Stamkos94%, Roman Josi98%, Ryan O'Reilly84%, Filip Forsberg99%, Matthew Wood31%
3.2 min/game · 5.17 xGF/60 · P(intact) 95%
- ANA shorthanded time −2%
- ANA PK xGA/60 −2%
- vs Lukas Dostal .889 (90% to start)
- Dostal .878 on cycle shots
- Together 2 of last 2
- DK correlation .21
Mikael Granlund52%, Jackson LaCombe97%, Cutter Gauthier98%, Leo Carlsson94%, Beckett Sennecke94%
2.6 min/game · 5.93 xGF/60 · P(intact) 82%
- NSH shorthanded time +1%
- NSH PK xGA/60 −3%
- vs Justus Annunen .907 (40% to start)
- Annunen .821 on rebounds
- Together 2 of last 3
- DK correlation .20
Jonathan Marchessault24%, Ross Colton8.1%, Mavrik Bourque34%
8.0 min/game · 1.48 xGF/60 · P(intact) 95%
- ANA 5v5 xGA/60 +2%
- vs Lukas Dostal .889 (90% to start)
- Dostal .878 on cycle shots
- Together 2 of last 2
Judd Caulfield, Jeff Malott3.2%, Tim Washe4.8%
7.6 min/game · 1.42 xGF/60 · P(intact) 82%
- NSH 5v5 xGA/60 +9%
- vs Justus Annunen .907 (40% to start)
- Annunen .821 on rebounds
- Together 2 of last 3
Jack Drury4.8%, Adam Edstrom0.0%, Reid Schaefer7.2%
7.5 min/game · 2.28 xGF/60 · P(intact) 18%
- ANA 5v5 xGA/60 +2%
- vs Lukas Dostal .889 (90% to start)
- Dostal .878 on cycle shots
- Together 1 of last 2
Frank Vatrano6.4%, Ryan Poehling6.7%, Nikita Nesterenko4.0%
7.8 min/game · 2.86 xGF/60 · P(intact) 12%
- NSH 5v5 xGA/60 +9%
- vs Justus Annunen .907 (40% to start)
- Annunen .821 on rebounds
- Together 1 of last 3
- DK correlation .28
PIT @ SJS
Evgeni Malkin84%, Tommy Novak21%, Egor Chinakhov49%
10.6 min/game · 3.63 xGF/60 · P(intact) 95%
- SJS 5v5 xGA/60 +7%
- vs Yaroslav Askarov .884 (73% to start)
- Askarov .831 on rebounds
- Together 3 of last 3
- DK correlation .27
Sidney Crosby100%, Rickard Rakell82%, Nick Robertson31%
10.6 min/game · 3.55 xGF/60 · P(intact) 82%
- SJS 5v5 xGA/60 +7%
- vs Yaroslav Askarov .884 (73% to start)
- Askarov .831 on rebounds
- Together 2 of last 3
- DK correlation .27
Mason Marchment47%, Will Smith95%, Macklin Celebrini100%
12.1 min/game · 2.08 xGF/60 · P(intact) 95%
- PIT 5v5 xGA/60 +4%
- vs Arturs Silovs .888 (97% to start)
- Silovs .767 on rebounds
- Together 2 of last 2
- DK correlation .30
Alexander Wennberg24%, Luca Cagnoni64%, Will Smith95%, Macklin Celebrini100%, Igor Chernyshov53%
2.9 min/game · 9.47 xGF/60 · P(intact) 95%
- PIT shorthanded time −3%
- PIT PK xGA/60 −8%
- vs Arturs Silovs .888 (97% to start)
- Silovs .767 on rebounds
- Together 2 of last 2
- DK correlation .28
Tyler Toffoli38%, Igor Chernyshov53%, Michael Misa59%
9.0 min/game · 2.11 xGF/60 · P(intact) 95%
- PIT 5v5 xGA/60 +4%
- vs Arturs Silovs .888 (97% to start)
- Silovs .767 on rebounds
- Together 2 of last 2
- DK correlation .28
Alexander Wennberg24%, Collin Graf28%, Ivar Stenberg82%
10.5 min/game · 1.52 xGF/60 · P(intact) 95%
- PIT 5v5 xGA/60 +4%
- vs Arturs Silovs .888 (97% to start)
- Silovs .767 on rebounds
- Together 2 of last 2
- DK correlation .28
Barclay Goodrow0.1%, Kiefer Sherwood59%, Zack Ostapchuk3.2%
7.3 min/game · 1.81 xGF/60 · P(intact) 95%
- PIT 5v5 xGA/60 +4%
- vs Arturs Silovs .888 (97% to start)
- Silovs .767 on rebounds
- Together 2 of last 2
- DK correlation .27
Sidney Crosby100%, Erik Karlsson95%, Rickard Rakell82%, Tommy Novak21%, Egor Chinakhov49%
4.2 min/game · 9.42 xGF/60 · P(intact) 12%
- SJS shorthanded time +16%
- SJS PK xGA/60 +7%
- vs Yaroslav Askarov .884 (73% to start)
- Askarov .831 on rebounds
- Together 1 of last 3
- DK correlation .20
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.