Pittsburgh Penguins

How Pittsburgh plays, trait by trait, against the rest of the league.

Real numbers through Oct 10: 5 games this season, blended with last season. Traits that take longer to settle lean more on last season.

Real numbers through Oct 10, from this season’s 5 games only. Expect these to swing a lot this early, which is why the likely ranges are so wide.

Offense

• Shot volume
  SelectiveRelentless

  58.8 shot attempts per 609th of 32

  58.8 shot attempts per 609th of 32

• Shot quality
  HopefulDangerous

  a 6.9% chance of scoring on the average shot3rd of 32

  a 7.4% chance of scoring on the average shot3rd of 32

• Second chances
  One-and-doneCrashers

  10.0% of chances come from rebounds28th of 32

  5.8% of chances come from rebounds27th of 32

• Off-turnover offense
  PatientOpportunist

  7.5% of chances come right after a turnover13th of 32

  6.7% of chances come right after a turnover20th of 32

• Shots from defensemen
  Forward-ledActive D

  34.4% of shot attempts come from defensemen17th of 32

  36.1% of shot attempts come from defensemen9th of 32

• Shots from in close
  From distanceIn close

  34.3% of shots come from within 20 feet1st of 32

  36.8% of shots come from within 20 feet3rd of 32

Defense

• Shot suppression
  PorousStingy

  58.8 shot attempts allowed per 6022nd of 32

  62.2 shot attempts allowed per 6025th of 32

• Quality allowed
  ExposedSheltered

  a 6.6% chance of scoring on the average shot against27th of 32

  a 6.8% chance of scoring on the average shot against23rd of 32

• Breakdowns avoided
  Fire drillComposed

  0.42 defensive breakdowns per 6020th of 32

  0.76 defensive breakdowns per 6027th of 32

• Goaltending
  SieveWall

  +0.08 goals saved above expected per 6023rd of 32

  +0.38 goals saved above expected per 6016th of 32

Tempo and edge

• Pace
  SlogTrack meet

  84.9 shots per 60, both teams combined3rd of 32

  90.4 shots per 60, both teams combined3rd of 32

• Forecheck pressure
  PassiveHounding

  forecheck score 70 (100 is league average)32nd of 3215.8 forecheck plays recorded per 6032nd of 32

  forecheck score 56 (100 is league average)32nd of 3213.5 forecheck plays recorded per 6032nd of 32

• Physicality
  FinesseBruising

  hit score 66 (100 is league average)32nd of 3217.2 hits recorded per 6032nd of 32

  hit score 51 (100 is league average)32nd of 3214.2 hits recorded per 6032nd of 32

• Depth
  Top-heavyDeep

  43.6% of forward ice time at 5-on-5 goes to the bottom six6th of 32

  43.7% of forward ice time at 5-on-5 goes to the bottom six11th of 32

Special teams

• Power play
  HarmlessLethal

  7.4 expected goals per 60 on the power play15th of 32

  6.6 expected goals per 60 on the power play19th of 32

• Penalty kill
  LeakyAirtight

  7.0 expected goals allowed per 60 shorthanded6th of 32

  6.8 expected goals allowed per 60 shorthanded16th of 32

• Power kill
  BunkeredPredatory

  1.0 expected goals created per 60 shorthanded12th of 32

  2.1 expected goals created per 60 shorthanded4th of 32

• Discipline
  RecklessClean

  0.01 more penalties taken than drawn per 6020th of 32

  0.39 more penalties drawn than taken per 6011th of 32

Forecheck pressure and physicality are shown as arena-adjusted scores; switch “Hits and takeaways” to Raw in the settings to see the numbers as recorded. How the arena adjustment works.

Who Pittsburgh leans on, and what they do best.

• Rickard Rakell

  19:29 a game

  #67 · Right wing · 2 P in 5 GP (0 G, 2 A)

  • Most ice time
  • L2 · Crosby, Rust
  • PP1
  • Kills penalties
  • Tough minutes
  • Tough minutes
  • Power-play chancestop 7%
  • Staying out of the boxtop 10%
  • Creating his own chancestop 11%
  • Faceoffsbottom 3%
  • Preventing chancesbottom 7%

• Sidney Crosby

  19:09 a game

  #87 · Center · 2 P in 5 GP (0 G, 2 A)

  • 2nd in ice time
  • L2 · Rust, Rakell
  • PP1
  • Tough minutes
  • Tough minutes
  • Finishingtop 6%
  • Setting up goalstop 7%
  • Shooting volumetop 16%
  • Shot blockingbottom 8%
  • Shooting volumetop 14%
  • Preventing chancesbottom 9%

• Bryan Rust

  18:45 a game

  #17 · Right wing · 2 P in 2 GP (2 G, 0 A)

  • L2 · Crosby, Rakell
  • Kills penalties
  • Tough minutes
  • Tough minutes
  • Shot blockingtop 8%
  • Shorthanded threattop 10%
  • Preventing chancesbottom 5%

  No clear strengths or weak spots yet.

• Evgeni Malkin

  17:37 a game

  #71 · Center · 5 P in 5 GP (3 G, 2 A)

  • L1 · Novak, Chinakhov
  • PP2
  • Setting up goalstop 5%
  • Takeawaystop 6%
  • Creating chancestop 10%
  • Shot blockingbottom 5%
  • Distance skatedtop 7%
  • Hittingbottom 18%

• Erik Karlsson

  22:38 a game

  #65 · Defenseman · 5 P in 5 GP (0 G, 5 A)

  • Most ice time
  • P2 · Carlile
  • PP1
  • Kills penalties
  • Tough minutes
  • Tough minutes
  • Creating chancesTop 10
  • Setting up goalstop 6%
  • Top speedTop 5
  • Shot blockingbottom 1%
  • Creating chancestop 11%
  • Fast burstsTop 10
  • Top speedtop 6%
  • Preventing chancesbottom 19%

• Kris Letang

  19:37 a game

  #58 · Defenseman · 3 P in 5 GP (0 G, 3 A)

  • 2nd in ice time
  • P3 · van Riemsdyk
  • PP2
  • Takeawaystop 14%
  • Shooting volumetop 22%
  • Finishingbottom 4%
  • Shooting volumetop 20%
  • Takeawaystop 20%

The 4 forwards and 2 defensemen with the most ice time a game (at least half the games played). Tags show how each is used; rows show his clearest strengths, and a weak spot in grey, as a percentile against his position. Point at anything for details. All Penguins players.

Who plays together at 5-on-5, and how each group is doing.

Lines and pairs are numbered by 5-on-5 ice time together over the team’s last 10 games (5 so far this season), with each older game counting half as much as the one after it, so the latest combinations come first. With so few games, each group’s results are pulled toward the average for its line number.

Last game

At Columbus Blue Jackets, the team used the same lines and pairs as above.

Which opposing lines each Pittsburgh group has actually been out against at 5-on-5.

Each strip adds to 100%: it shows how one Pittsburgh group’s 5-on-5 time is split across the opponent’s four forward lines, numbered the same way as above. Sized by ice time, a wider box means more time against that line; even columns line the boxes up so you can compare groups straight down. At home the coach changes last and picks these matchups; on the road the other coach does. Faded rows have under ten minutes.

What “with no line matching” means: if a coach just rolled his lines and took whoever was out there, each of his groups would face the opponent’s first line about as often as that line is on the ice. If opposing first lines play a third of the time against Pittsburgh, every Pittsburgh group would see them for about a third of its shifts. A number well above that means the coach is sending that group out against them on purpose; well below means he is keeping it away.

Who Pittsburgh sends out with a man up and a man down.

Each power-play unit is built around its quarterback, the defenseman running it, plus the four players most often out with him over the last 10 games (5 so far). Power-play units’ expected goals per 60 are pulled toward league average while samples are small. Penalty kills are too loose for fixed units (the most common foursome covers only about a tenth of a typical team’s shorthanded time), so penalty killers are grouped by when they go on: the ones who start kills, the second wave who come on after the first change, and spot duty. Point at a power-play name to see his shots on the map.

What the tags mean

Quarterbackthe defenseman who runs the unit from the blue line.

Triggerthe unit’s main shooter, with the most dangerous power-play shots on the team over this season and last.

Distributorthe main passer, with the most first assists on the team’s power-play goals over this season and last.

Net-frontparks in front of the net. At least 40% of his power-play shots come from within 15 feet.

Pointa second defenseman on the unit, alongside the quarterback.

Is he stopping more than he should, and what is his team asking him to face?

Expected-goal models can’t see passes before a shot, so a goalie whose team gives up a lot of cross-ice passes will look worse here than he really is. Ratings compare him with goalies who have at least 10 starts over two seasons, or 2 this season.

How Pittsburgh’s goals are scored and allowed, against the league average, and how much of any difference luck alone could explain.

Every goal counts once, in the first of these that applies: empty net, power play, shorthanded, goalie pulled, then rebound, turnover, faceoff win, and everyday play. These mixes are mostly luck: over three seasons, teams’ goals came from much the same places, and most of the differences here didn’t last.