Chicago Blackhawks

How Chicago 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

  45.8 shot attempts per 6030th of 32

  42.8 shot attempts per 6030th of 32

• Shot quality
  HopefulDangerous

  a 6.0% chance of scoring on the average shot28th of 32

  a 5.5% chance of scoring on the average shot28th of 32

• Second chances
  One-and-doneCrashers

  10.3% of chances come from rebounds14th of 32

  8.9% of chances come from rebounds18th of 32

• Off-turnover offense
  PatientOpportunist

  7.6% of chances come right after a turnover10th of 32

  4.2% of chances come right after a turnover26th of 32

• Shots from defensemen
  Forward-ledActive D

  35.4% of shot attempts come from defensemen12th of 32

  33.9% of shot attempts come from defensemen17th of 32

• Shots from in close
  From distanceIn close

  26.5% of shots come from within 20 feet32nd of 32

  25.0% of shots come from within 20 feet29th of 32

Defense

• Shot suppression
  PorousStingy

  60.0 shot attempts allowed per 6026th of 32

  60.4 shot attempts allowed per 6024th of 32

• Quality allowed
  ExposedSheltered

  a 6.5% chance of scoring on the average shot against22nd of 32

  a 6.8% chance of scoring on the average shot against24th of 32

• Breakdowns avoided
  Fire drillComposed

  0.37 defensive breakdowns per 605th of 32

  0.48 defensive breakdowns per 6018th of 32

• Goaltending
  SieveWall

  +0.08 goals saved above expected per 6021st of 32

  −0.47 goals saved above expected per 6023rd of 32

Tempo and edge

• Pace
  SlogTrack meet

  81.3 shots per 60, both teams combined21st of 32

  78.7 shots per 60, both teams combined19th of 32

• Forecheck pressure
  PassiveHounding

  forecheck score 83 (100 is league average)29th of 3218.6 forecheck plays recorded per 6030th of 32

  forecheck score 84 (100 is league average)24th of 3220.2 forecheck plays recorded per 6026th of 32

• Physicality
  FinesseBruising

  hit score 76 (100 is league average)31st of 3220.0 hits recorded per 6030th of 32

  hit score 72 (100 is league average)29th of 3220.7 hits recorded per 6029th of 32

• Depth
  Top-heavyDeep

  41.2% of forward ice time at 5-on-5 goes to the bottom six22nd of 32

  41.9% of forward ice time at 5-on-5 goes to the bottom six19th of 32

Special teams

• Power play
  HarmlessLethal

  6.1 expected goals per 60 on the power play31st of 32

  4.6 expected goals per 60 on the power play27th of 32

• Penalty kill
  LeakyAirtight

  7.4 expected goals allowed per 60 shorthanded16th of 32

  6.4 expected goals allowed per 60 shorthanded13th of 32

• Power kill
  BunkeredPredatory

  1.0 expected goals created per 60 shorthanded13th of 32

  2.8 expected goals created per 60 shorthanded1st of 32

• Discipline
  RecklessClean

  0.09 more penalties taken than drawn per 6024th of 32

  0.40 more penalties taken than drawn per 6024th 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 Chicago leans on, and what they do best.

• Patrick Kane

  19:48 a game

  #88 · Right wing · 2 P in 5 GP (1 G, 1 A)

  • Most ice time
  • L3 · Nazar, Lardis
  • PP1
  • Tough minutes
  • Tough minutes
  • Takeawaysbottom 1%
  • Preventing chancesbottom 22%

• Roman Kantserov

  18:51 a game

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

  • 2nd in ice time
  • L2 · Bertuzzi, Frondell
  • PP1
  • Tough minutes
  • Tough minutes

  No clear strengths or weak spots yet.
  • Top speedTop 10
  • Creating his own chancesbottom 21%

• Frank Nazar

  18:50 a game

  #91 · Center · 3 P in 5 GP (2 G, 1 A)

  • L3 · Kane, Lardis
  • PP2
  • Kills penalties
  • Tough minutes
  • Shorthanded threattop 7%
  • Takeawaystop 11%
  • Top speedtop 4%
  • Hittingbottom 15%
  • Shorthanded threattop 11%
  • Fast burststop 8%
  • Top speedtop 10%
  • Shooting volumebottom 15%

• Anton Frondell

  18:10 a game

  #16 · Center · 4 P in 5 GP (1 G, 3 A)

  • L2 · Bertuzzi, Kantserov
  • PP1
  • Kills penalties
  • Tough minutes
  • Tough minutes

  No clear strengths or weak spots yet.
  • Hardest shot1st
  • Faceoffsbottom 12%

• Bowen Byram

  24:29 a game

  #24 · Defenseman · 0 P in 4 GP (0 G, 0 A)

  • Most ice time
  • P2 · Levshunov
  • PP1
  • Tough minutes
  • Creating his own chancestop 19%
  • Fast burststop 9%
  • Top speedtop 14%
  • Hittingbottom 8%
  • Fast burstsTop 10
  • Preventing chancesbottom 12%

• Artyom Levshunov

  20:16 a game

  #55 · Defenseman · 1 P in 5 GP (0 G, 1 A)

  • 2nd in ice time
  • P2 · Byram
  • Kills penalties
  • Tough minutes
  • Creating his own chancestop 22%
  • Finishingbottom 1%
  • Takeawaystop 16%
  • Creating his own chancestop 25%
  • Fast burststop 10%
  • Shot blockingbottom 25%

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 Blackhawks 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 New York Islanders, the team used the same lines and pairs as above.

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

Each strip adds to 100%: it shows how one Chicago 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 Chicago, every Chicago 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 Chicago 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 Chicago’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.