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NHL Stack Finder: Friday, Nov 13
Data updated:
Top 10 stacks
Mika Zibanejad98%, Alexis Lafrenière81%, Gabe Perreault54%
Matchup factors →Tomas Hertl84%, Victor Olofsson15%, Trevor Connelly34%
Matchup factors →Mark Stone93%, Ivan Barbashev68%, Jack Eichel99%
Matchup factors →Mark Stone93%, Tomas Hertl84%, Shea Theodore92%, Jack Eichel99%, Mitch Marner99%
Matchup factors →William Karlsson24%, Mitch Marner99%, Brett Howden16%
Matchup factors →Mika Zibanejad98%, J.T. Miller92%, Adam Fox99%, Pavel Dorofeyev93%, Alexis Lafrenière81%
Matchup factors →Eeli Tolvanen38%, Will Cuylle64%, Noah Laba11%
Matchup factors →Steven Stamkos94%, Roman Josi98%, Ryan O'Reilly84%, Filip Forsberg99%, Matthew Wood31%
Matchup factors →Filip Forsberg99%, Nils Hoglander4.0%, Matthew Wood31%
Matchup factors →Steven Stamkos94%, Ryan O'Reilly84%, Alexander Kerfoot3.2%
Matchup factors →
By game
NYR @ VAN
Mika Zibanejad98%, Alexis Lafrenière81%, Gabe Perreault54%
11.0 min/game · 2.82 xGF/60 · P(intact) 95%
- VAN 5v5 xGA/60 +18%
- vs Kevin Lankinen .872 (82% to start)
- Lankinen .776 on rebounds
- Together 3 of last 3
- DK correlation .28
Mika Zibanejad98%, J.T. Miller92%, Adam Fox99%, Pavel Dorofeyev93%, Alexis Lafrenière81%
2.6 min/game · 6.75 xGF/60 · P(intact) 95%
- VAN shorthanded time −12%
- VAN PK xGA/60 +20%
- vs Kevin Lankinen .872 (82% to start)
- Lankinen .776 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%
- VAN 5v5 xGA/60 +18%
- vs Kevin Lankinen .872 (82% to start)
- Lankinen .776 on rebounds
- Together 3 of last 3
- DK correlation .29
Brock Boeser66%, Paul Cotter39%, Liam Ohgren23%
7.7 min/game · 1.77 xGF/60 · P(intact) 95%
- NYR 5v5 xGA/60 −2%
- vs Igor Shesterkin .913 (61% to start)
- Shesterkin .845 on rebounds
- Together 3 of last 3
- DK correlation .26
Elias Pettersson91%, Linus Karlsson11%, Marco Rossi67%
8.8 min/game · 1.63 xGF/60 · P(intact) 82%
- NYR 5v5 xGA/60 −2%
- vs Igor Shesterkin .913 (61% to start)
- Shesterkin .845 on rebounds
- Together 2 of last 3
- DK correlation .27
Arshdeep Bains3.2%, Jonathan Lekkerimäki25%, Max Sasson4.9%
5.4 min/game · 2.09 xGF/60 · P(intact) 82%
- NYR 5v5 xGA/60 −2%
- vs Igor Shesterkin .913 (61% to start)
- Shesterkin .845 on rebounds
- Together 2 of last 3
- DK correlation .26
J.T. Miller92%, Oliver Bjorkstrand19%, Pavel Dorofeyev93%
7.8 min/game · 3.23 xGF/60 · P(intact) 23%
- VAN 5v5 xGA/60 +18%
- vs Kevin Lankinen .872 (82% to start)
- Lankinen .776 on rebounds
- Together 2 of last 3
Brendan Gallagher3.3%, Drew O'Connor6.7%, Aatu Räty10%
4.8 min/game · 2.22 xGF/60 · P(intact) 82%
- NYR 5v5 xGA/60 −2%
- vs Igor Shesterkin .913 (61% to start)
- Shesterkin .845 on rebounds
- Together 2 of last 3
- DK correlation .28
Joseph Veleno4.9%, Tye Kartye7.2%, Jaroslav Chmelar0.1%
5.3 min/game · 1.87 xGF/60 · P(intact) 23%
- VAN 5v5 xGA/60 +18%
- vs Kevin Lankinen .872 (82% to start)
- Lankinen .776 on rebounds
- Together 2 of last 3
Brock Boeser66%, Filip Hronek92%, Elias Pettersson91%, Drew O'Connor6.7%, Marco Rossi67%
5.3 min/game · 4.13 xGF/60 · P(intact) 12%
- NYR shorthanded time +2%
- NYR PK xGA/60 +18%
- vs Igor Shesterkin .913 (61% to start)
- Shesterkin .845 on rebounds
- Together 1 of last 3
- DK correlation .20
NSH @ VGK
Tomas Hertl84%, Victor Olofsson15%, Trevor Connelly34%
7.3 min/game · 4.39 xGF/60 · P(intact) 95%
- NSH 5v5 xGA/60 +9%
- vs Juuse Saros .895 (85% to start)
- Saros .786 on rebounds
- Together 3 of last 3
Mark Stone93%, Ivan Barbashev68%, Jack Eichel99%
9.5 min/game · 3.36 xGF/60 · P(intact) 95%
- NSH 5v5 xGA/60 +9%
- vs Juuse Saros .895 (85% to start)
- Saros .786 on rebounds
- Together 3 of last 3
- DK correlation .28
Mark Stone93%, Tomas Hertl84%, Shea Theodore92%, Jack Eichel99%, Mitch Marner99%
3.8 min/game · 7.83 xGF/60 · P(intact) 95%
- NSH shorthanded time +6%
- NSH PK xGA/60 +5%
- vs Juuse Saros .895 (85% to start)
- Saros .786 on rebounds
- Together 3 of last 3
- DK correlation .18
William Karlsson24%, Mitch Marner99%, Brett Howden16%
9.6 min/game · 2.48 xGF/60 · P(intact) 95%
- NSH 5v5 xGA/60 +9%
- vs Juuse Saros .895 (85% to start)
- Saros .786 on rebounds
- Together 3 of last 3
- DK correlation .27
Steven Stamkos94%, Roman Josi98%, Ryan O'Reilly84%, Filip Forsberg99%, Matthew Wood31%
3.5 min/game · 5.17 xGF/60 · P(intact) 95%
- VGK shorthanded time +7%
- VGK PK xGA/60 −7%
- vs Carter Hart .889 (45% to start)
- Hart .880 on other shots
- Together 2 of last 2
- DK correlation .21
Filip Forsberg99%, Nils Hoglander4.0%, Matthew Wood31%
5.9 min/game · 2.97 xGF/60 · P(intact) 95%
- VGK 5v5 xGA/60 −12%
- vs Carter Hart .889 (45% to start)
- Hart .880 on other 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%
- VGK 5v5 xGA/60 −12%
- vs Carter Hart .889 (45% to start)
- Hart .880 on other shots
- Together 2 of last 2
- DK correlation .30
Nic Dowd3.2%, Marc Gatcomb5.7%, Braeden Bowman16%
5.7 min/game · 2.16 xGF/60 · P(intact) 95%
- NSH 5v5 xGA/60 +9%
- vs Juuse Saros .895 (85% to start)
- Saros .786 on rebounds
- Together 3 of last 3
Jonathan Marchessault24%, Ross Colton8.1%, Mavrik Bourque34%
8.0 min/game · 1.48 xGF/60 · P(intact) 95%
- VGK 5v5 xGA/60 −12%
- vs Carter Hart .889 (45% to start)
- Hart .880 on other shots
- Together 2 of last 2
Jack Drury4.8%, Adam Edstrom0.0%, Reid Schaefer7.2%
7.5 min/game · 2.28 xGF/60 · P(intact) 18%
- VGK 5v5 xGA/60 −12%
- vs Carter Hart .889 (45% to start)
- Hart .880 on other shots
- Together 1 of last 2
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.