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final

PIT7

Pittsburgh Penguins

PHI0

Philadelphia Flyers

Wednesday, September 30

Final · Xfinity Mobile Arena

The short version

What happened

Silovs shuts out the Flyers

Nick Robertson scored twice, opening the scoring midway through the first. Six different Penguins scored. Arturs Silovs stopped all 19 shots.

The score was fair. Replay this game’s chances a hundred times and the Penguins win nine in ten. By our Swing measure, Filip Hallander had the best night of anyone. The Penguins tried a line they hadn’t used before: Robertson, Rickard Rakell and Sidney Crosby, and it had a hand in three of their goals.

What it means

  • Keep an eye onWhether the Penguins keep that line together at home against Montréal on Saturday.
  • The previewTwo of the preview’s three calls held.

Our pre-game read

The win chance our model worked out before the game, kept off the site until now.

We had this close to even (42% for Pittsburgh), and Pittsburgh came through.

Two even teams on neutral ice50%
Home ice−4 points46%
Recent chances−9 points37%
Who's been playing+4 points42%
Back-to-back0 points42%
Our chance for Pittsburgh the morning of the game42%
Tonight's lineup+2 points
At puck drop, once the lineups were known44%

Recent chances: how much better each team’s chances have been than their opponents’ lately, with the latest games counting most. Who’s been playing: whether the players who dressed last time were stronger or weaker than the ones behind those recent games, so a star who is out or back counts straight away. Back-to-back: playing for the second night in a row. Tonight’s lineup: any change in who dressed since the last game. Only earlier games went into it, and the preview hinted at it in words without showing the number.

We had this close to even (58% for Philadelphia), and it went Pittsburgh’s way.

Two even teams on neutral ice50%
Home ice+4 points54%
Recent chances+9 points63%
Who's been playing−4 points58%
Back-to-back0 points58%
Our chance for Philadelphia the morning of the game58%
Tonight's lineup−2 points
At puck drop, once the lineups were known56%

Recent chances: how much better each team’s chances have been than their opponents’ lately, with the latest games counting most. Who’s been playing: whether the players who dressed last time were stronger or weaker than the ones behind those recent games, so a star who is out or back counts straight away. Back-to-back: playing for the second night in a row. Tonight’s lineup: any change in who dressed since the last game. Only earlier games went into it, and the preview hinted at it in words without showing the number.

What the preview said, and what happened

Of the 3 calls the preview made, 2 held up, 1 partly did, and 0 didn’t happen.

  1. Before the game

    The matchup inside the matchup

    The Penguins are one of the league’s best for chance quality, and the Flyers are one of the league’s best at preventing dangerous shots. Our lean: the Penguins’ chance quality wins out.

    The call The Penguins’ chances are more dangerous than the league average (a 6.3% chance of scoring on the average shot) against the Flyers.

    Pittsburgh 5th for chance quality (a 6.6% chance of scoring on the average shot) · Philadelphia 5th for preventing dangerous shots

    Held up

    On chance quality, Pittsburgh had 7.2% a shot. The league average is 6.3% a shot, and they came in at 6.6% a shot.

    6.6% a shot
    Coming in
    7.2% a shot
    In this game
    6.3% a shot
    League average

  2. Before the game

    Something has to give

    The Flyers are near the top of the league for the power play, and the Penguins are near the top of the league at the penalty kill. Our lean: the Penguins’ kill holds up, even though power plays usually win these.

    The call The Penguins’ kill holds the Flyers’ power play under the league-average 7.6 expected goals per 60.

    Philadelphia 7th for the power play (7.8 expected goals per 60) · Pittsburgh 6th for the penalty kill

    Held up

    On the power play, Philadelphia had 6.6 per 60. The league average is 7.6 per 60, and they came in at 7.8 per 60.

    7.8 per 60
    Coming in
    6.6 per 60
    In this game
    7.6 per 60
    League average

  3. Before the game

    Bruisers against finesse

    The Flyers are near the top of the league for physicality, at the bruising end; the Penguins are one of the league’s worst, at the finesse end. Expect that gap to show.

    The call The Flyers hit more than the Penguins in the close stretches of the game.

    Physicality: Philadelphia 8th, Pittsburgh 31st

    Partly

    On hit score in close games (arena-adjusted, 100 is league average), Philadelphia had hit score 144 and Pittsburgh hit score 131. Coming in, Philadelphia was at hit score 111 and Pittsburgh at hit score 82.

    PHI hit score 111 · PIT hit score 82
    Coming in
    PHI hit score 144 · PIT hit score 131
    In this game

Each call is checked by a rule set before the game. Held up: the team reached their usual level. Partly: they fell short of their usual level but still beat the league average. When a call says one team will come out ahead, held up means they won by at least half their usual gap, and partly means they won by less. One game is a small sample, so a miss doesn’t mean the preview was wrong about the team.

Read the full preview as it stood at puck drop.

This season so far: 94 held up, 12 partly, 64 didn’t happen, out of 170 graded calls. See the track record.

Run it back

We replayed this game’s chances 100 times. Here is how often each team came out ahead.

Pittsburgh earned this one

Played out 100 times with these chances, Pittsburgh wins 92.

92%
Pittsburgh: 88 wins, plus half of the 7 ties
8%
Philadelphia: 4 wins, plus half of the 7 ties

Pittsburgh had 50 chances worth 4.6 expected goals. Philadelphia had 33 chances worth 1.5 expected goals.

How it works: every shot in regulation that was on target or missed the net goes in as often as our expected-goals model says it should, and the game is played out 100 times that way. A rebound scramble counts as one chance, and empty-net shots are left out. A replay tied after regulation counts as half a win each, since overtime and shootouts are close to coin flips.

It doesn’t know about goalies, finishing skill or passes before a shot. It also favours the team that was chasing, because a team with a lead tends to sit back. Over the last three seasons, teams it gave 80% or more won about two games in three.

What the preview didn’t see coming

The parts of this game furthest from how these teams usually play, biggest first.

Broke the pattern: a team did the opposite of their usual habit. Further than usual: a usual habit, taken much further. Closer than usual: a usual strength or weakness that mostly disappeared. Out of character: a usually average team, far from average. Each is measured against the teams’ numbers before the game.

The numbers

How the game went, beyond the score.

PittsburghPhiladelphia
Goals70
Shots on goal3819
Expected goals4.71.5
Shot attempts at 5-on-55231
Power plays2 of 40 of 3

Swing

How far each player swung tonight’s result, for his team or against it.

The biggest swings: F. Hallander +2.2, H. Lapierre +2.0 and V. Koivunen +1.5.

Showhighlighting

The number is roughly in goals: what he added to his team tonight, or cost it. Tap a player to see where it came from. The label beside it is his report card from “Did they do their job?” below; L1 to L4 and P1 to P3 are tonight’s lines and pairs.

How Swing is worked outHide how Swing is worked out

Scoresheet: each goal is shared 40% to the scorer, 35% to the first assist and 25% to the second, plus a quarter of the expected goals of his own shots. A penalty drawn adds 0.16 and one taken costs 0.16, what a power play is worth on average; each faceoff won or lost moves it by 0.006.

5-on-5 counts most: expected goals for minus against with him on, half compared with league average (adjusted for score and venue) and half compared with his own team when he was on the bench, plus a smaller amount for actual goals. A player on a losing team can score well if his line held its own. Special teams: power-play and penalty-kill time compared with a league-average unit.

Company kept (counted inside 5-on-5): from every player’s 5-on-5 impact over the two seasons before, a player out with strong linemates against weak opponents gives a little back, and the reverse earns a little. Goalies: goals saved above expected. Empty-net shots and shootouts are left out. One game is a small sample: this says who swung this result, not who is better.

Did they do their job?

What each player is relied on for or better than most at, and whether he delivered.

Show
  • S. GirardBig night

    2 assists, 91% of the 5-on-5 chances with him on.

    Defense
    21:02
    G
    0
    A
    2
    +/−
    +3
    xGF–xGA
    1.3–0.1
    Shots
    2
    Hits
    1
    Blocks
    0
    • ✓Creating chances at 5-on-5 Better than mostexpected goals per 60 with him on at 5-on-54.7typical 2.8
  • T. van RiemsdykDid his job
    Defense
    20:42
    G
    0
    A
    0
    +/−
    +1
    xGF–xGA
    1.1–0.3
    Shots
    0
    Hits
    1
    Blocks
    4
    • ✕Kills penalties Relied onexpected goals per 60 allowed on the penalty kill6.9typical 6.2
    • ✓Preventing chances at 5-on-5 Better than mostexpected goals per 60 allowed with him on at 5-on-51.1typical 2.3
    • ✓Blocking shots Better than mostblocked shots4typical 2
  • E. KarlssonMixed night
    Defense
    19:59
    G
    0
    A
    1
    +/−
    +1
    xGF–xGA
    1.1–0.3
    Shots
    3
    Hits
    0
    Blocks
    1
    • ✓Power play Relied onexpected goals per 60 on the power play8.2typical 7.3
    • ✕Kills penalties Relied onexpected goals per 60 allowed on the penalty kill7.7typical 6.2
    • ≈Shooting Better than mostshot attempts at 5-on-52typical 3
  • K. LetangDid his job
    Defense
    18:44
    G
    0
    A
    1
    +/−
    +1
    xGF–xGA
    1.1–0.2
    Shots
    4
    Hits
    2
    Blocks
    0
    • ✓Power play Relied onexpected goals per 60 on the power play9.0typical 6.2
    • –Kills penalties Relied onToo little time to judge
  • R. RakellDid his job
    Right wing
    18:32
    G
    0
    A
    1
    +/−
    +1
    xGF–xGA
    0.8–0.3
    Shots
    2
    Hits
    3
    Blocks
    0
    • ✓Power play Relied onexpected goals per 60 on the power play8.6typical 7.5
    • ✓Getting to dangerous spots Better than mostexpected goals from his own shots at 5-on-50.42typical 0.11
  • K. KorczakBig night

    2 assists, 93% of the 5-on-5 chances with him on.

    Defense
    18:31
    G
    0
    A
    2
    +/−
    +3
    xGF–xGA
    1.2–0.1
    Shots
    3
    Hits
    1
    Blocks
    2
    • ✓Preventing chances at 5-on-5 Better than mostexpected goals per 60 allowed with him on at 5-on-50.4typical 2.0
    • ✓Hitting Better than mosthits1typical 1
Show 12 more Pittsburgh playersHide the other Pittsburgh players
  • S. CrosbyMixed night
    Center
    17:39
    G
    0
    A
    1
    +/−
    +1
    xGF–xGA
    0.8–0.3
    Shots
    3
    Hits
    2
    Blocks
    0
    • ✓Power play Relied onexpected goals per 60 on the power play8.8typical 7.3
    • ✓Creating chances at 5-on-5 Better than mostexpected goals per 60 with him on at 5-on-54.0typical 2.6
    • ✕Faceoffs Better than mostfaceoffs won9 of 20typical 55%
  • E. ChinakhovMixed night
    Right wing
    16:58
    G
    1
    A
    0
    +/−
    0
    xGF–xGA
    0.2–0.1
    Shots
    3
    Hits
    1
    Blocks
    0
    • ✓Shooting Better than mostshot attempts at 5-on-53typical 3
    • ✕Getting to dangerous spots Better than mostexpected goals from his own shots at 5-on-50.06typical 0.11
  • D. CarlileDid his job
    Defense
    16:30
    G
    0
    A
    1
    +/−
    +1
    xGF–xGA
    1.3–0.4
    Shots
    2
    Hits
    1
    Blocks
    0
    • ✕Kills penalties Relied onexpected goals per 60 allowed on the penalty kill11.1typical 6.1
    • ✓Hitting Better than mosthits1typical 1
  • T. NovakOff night
    Center
    16:04
    G
    0
    A
    1
    +/−
    0
    xGF–xGA
    0.2–0.1
    Shots
    0
    Hits
    0
    Blocks
    1
    • ✕Creating chances at 5-on-5 Better than mostexpected goals per 60 with him on at 5-on-50.8typical 2.8
    • ✕Getting to dangerous spots Better than mostexpected goals from his own shots at 5-on-50.00typical 0.11
  • E. MalkinMixed night
    Center
    15:47
    G
    1
    A
    0
    +/−
    0
    xGF–xGA
    0.7–0.2
    Shots
    2
    Hits
    0
    Blocks
    0
    • ✓Power play Relied onexpected goals per 60 on the power play8.3typical 7.4
    • ✕Getting to dangerous spots Better than mostexpected goals from his own shots at 5-on-50.07typical 0.12
    • ✓Creating chances at 5-on-5 Better than mostexpected goals per 60 with him on at 5-on-52.8typical 2.7
  • N. RobertsonBig night

    2 goals (one shorthanded, one at even strength), 72% of the 5-on-5 chances with him on.

    Left wing
    15:02
    G
    2
    A
    0
    +/−
    +2
    xGF–xGA
    0.9–0.3
    Shots
    4
    Hits
    0
    Blocks
    1
    • C. DewarMixed night
      Center
      14:51
      G
      0
      A
      0
      +/−
      0
      xGF–xGA
      0.5–0.1
      Shots
      0
      Hits
      4
      Blocks
      1
      • ✓Kills penalties Relied onexpected goals per 60 allowed on the penalty kill4.0typical 5.9
      • ✕Shooting Better than mostshot attempts at 5-on-50typical 3
      • ✓Blocking shots Better than mostblocked shots1typical 1
    • V. KoivunenBig night

      A goal from a player who scores in about 1 game in 10, 91% of the 5-on-5 chances with him on, on top of doing his usual jobs.

      Right wing
      13:50
      G
      1
      A
      0
      +/−
      +3
      xGF–xGA
      1.9–0.2
      Shots
      2
      Hits
      0
      Blocks
      0
      • ✓Preventing chances at 5-on-5 Better than mostexpected goals per 60 allowed with him on at 5-on-51.0typical 2.3
    • B. LizotteMixed night
      Center
      13:13
      G
      0
      A
      0
      +/−
      0
      xGF–xGA
      0.6–0.3
      Shots
      4
      Hits
      0
      Blocks
      1
      • ✓Kills penalties Relied onexpected goals per 60 allowed on the penalty kill5.6typical 5.9
      • ✓Preventing chances at 5-on-5 Better than mostexpected goals per 60 allowed with him on at 5-on-51.5typical 2.3
      • ✕Faceoffs Relied onfaceoffs won8 of 16typical 50%
    • H. LapierreBig night

      A goal, 1 assist, 99% of the 5-on-5 chances with him on.

      Center
      13:02
      G
      1
      A
      1
      +/−
      +3
      xGF–xGA
      1.9–0.0
      Shots
      1
      Hits
      4
      Blocks
      1
      • E. SoderblomMixed night
        Left wing
        12:39
        G
        0
        A
        0
        +/−
        0
        xGF–xGA
        0.3–0.1
        Shots
        0
        Hits
        2
        Blocks
        0
        • ✕Creating chances at 5-on-5 Better than mostexpected goals per 60 with him on at 5-on-51.6typical 2.3
        • ✓Hitting Better than mosthits2typical 2
      • F. HallanderBig night

        A goal, 2 assists.

        Center
        10:55
        G
        1
        A
        2
        +/−
        +4
        xGF–xGA
        1.6–0.1
        Shots
        3
        Hits
        1
        Blocks
        0
        • ✓Shooting Better than mostshot attempts at 5-on-54typical 2
      How the cards are gradedHide how the cards are graded

      ✓ a typical night for him in the ice time he got (the level he reaches in about half his games). ≈ beat an average player at his position, a typical power play or kill, or his own team with him off the ice. ✕ neither. Power-play and penalty-kill results count half, since five players share them.

      Huge night: a hat trick or four or more points. Big night: two or more points, or a goal from a player who scores in fewer than one game in five on top of doing his jobs. Rough night: no points while the other team had 70% or more of the 5-on-5 chances with him on (xGF–xGA). Plus-minus never sets the level. A shorthanded goal counts as two points. Points never fully cover for jobs that went badly: with his jobs off, a huge night reads big and a big night reads mixed.

      Judged only from games before this one; 5-on-5 rates adjusted for score and venue. One game is a small sample: even a strong player misses a typical night about half the time. Both teams: 39 ✓, 6 ≈, 29 ✕.

      In net

      Each goalie’s night: the goals he stopped beyond what the shots were worth, and the dangerous and routine saves.

      • A. SilovsBig night

        A shutout, 19 saves on 19 shots, +1.5 goals saved above expected.

        Goalie
        60:00
        Shots
        19
        Saves
        19
        Sv%
        1.000
        xGA
        1.5
        GSAx
        +1.5
        Dangerous
        0/0
        • ✓Saving more than expected goals saved above expected+1.5typical +0.1
        • –Dangerous shots Too few shots to judge
        • ✓Routine shots saves on shots under a 15% chance19 of 19typically saves 18 of 19
      • D. VladarRough night

        31 saves on 38 shots, −2.3 goals saved above expected.

        Goalie
        59:41
        Shots
        38
        Saves
        31
        Sv%
        .816
        xGA
        4.7
        GSAx
        −2.4
        Dangerous
        3/6
        • ✕Saving more than expected goals saved above expected-2.3typical +0.6
        • ✕Dangerous shots saves on shots with a 15%+ chance3 of 6typically saves 4 of 6
        • ✕Routine shots saves on shots under a 15% chance28 of 32typically saves 30 of 32

      Every goalie has the same three jobs, judged against his own earlier starts (✓) and an average goalie (≈). Huge night: a shutout on 25 or more shots, or 3+ goals saved above expected. Big night: any other shutout, or 1.5+. Rough night: 2+ goals worse than expected, or pulled early after three or more.

      Empty-net shots are left out. Expected-goal models can’t see passes before a shot, so a goalie beaten by cross-ice passes looks worse here than he really was.

      Team pages: Pittsburgh Penguins · Philadelphia Flyers