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Ice Lab

Left wing · #40

Michael Grabner

Vancouver Canucks New York Islanders Toronto Maple Leafs New York Rangers New Jersey Devils Arizona Coyotes(traded during the season)
Age
39
Shoots
Left
Height
185 cm
Weight
85 kg
Born
Villach, AUT
Draft
2006, round 1, #14 (VAN)

Career · 2009–10 to 2019–20

Games
640
Goals
175
Points
276
TOI per game
14:25
xGF% (5v5)
48.8%
Goals above expected
+8.6

Season by season

The regular-season line for each season, with the total, by team for traded players.

2009–10VAN205611+213:54637.9%46.2–
2010–11NYI76341852+1315:0522814.9%427.252.7%
2011–12NYI78201232−1815:3317411.5%220.346.1%
2012–13NYI4516521+414:4810814.8%312.348.8%
2013–14NYI64121426−1014:121378.8%018.150.5%
2014–15NYI348513+412:566312.7%07.155.4%
2015–16TOR809918−414:281167.8%013.546.3%
2016–17NYR76271340+2214:0616216.7%021.547.1%
2017–18NYR5925631+1114:5313119.1%119.248.9%
2017–18NJD21235014:39365.6%04.548.1%
2017–18All teams8027936+1114:4916716.2%123.848.7%
2018–19ARI419716−214:236513.8%09.249.4%
2019–20ARI468311−412:226113.1%07.344.7%
Total6 teams640175101276+1814:251,34413.0%14166.448.8%

Form

Rolling averages smooth out single games so the trend shows.

Form, ten-game rolling

Points and individual expected goals per game (left scale), averaged over the previous ten games. Ice time is on the second chart.

Points per gameixG per gameTOI per game (minutes)
00.511.5100200300400500600
10m12m14m16m18m20m100200300400500600Game

Player card

Model-based

How 2009–10 to 2019–20 compares with everyone else at the position over the same seasons, and the players with the most similar profile.

Overall rating

2nd line

73rd percentile among qualified forwards, blending scoring 40%, play-driving 40%, usage 20%.

  1. 1st line
  2. 2nd line
  3. 3rd line
  4. 4th line
  5. Extra / AHL

Scoring

1st line
  • Goals /601.1494th pct
  • Assists /600.6628th pct
  • ixG /601.0896th pct
  • Goals above expected+8.686th pct

Play-driving

3rd line
  • xGF% (5v5)48.8%46th pct
  • CF% (5v5)47.7%34th pct
  • Relative xGF%0.058th pct
  • Penalty diff /600.3275th pct

Usage

2nd line
  • TOI per game14:2561st pct
  • PP time share6.4%34th pct
  • Offensive zone starts37.6%11th pct
  • Quality of competition24.7%78th pct

Percentiles among forwards with 200+ minutes at 5-on-5 and 20+ games. Ratings rank each column's average percentile among the same players and read it as a role on a depth chart (how).

Most similar players this season

  1. Eric FehrWSH/WPG/PIT/SJS/MIN0.80
  2. Pierre Engvall0.78
  3. Miles WoodNJD0.71
  4. Blake ColemanNJD0.68
  5. Dominik KubalikCHI0.68
  6. Niklas HagmanTOR/CGY/ANA0.64

Faceoffs

How often Grabner wins the draw over 2009–10 to 2019–20, against whom and where, and what a win leads to. Ranked among players with 2117+ draws over the same seasons.

Win rate

41.4%

48–68 · below the 2117 draws of a regular

Against an average centre

41.7%

Opponents won 50.3% of their draws; an average centre would have won 49.7% against them.

Wins above average

−10

Draws won beyond what an average centre facing the same opponents would have won.

Draws per game

1.2

116 draws in all.

By dot, attacking to the right

63%8 · 0.044%18 · +3.429%7 · +1.938%8 · +0.60%2 · –50%8 · +1.343%7 · +0.647%36 · +9.427%22 · +5.9Attacking zone →← Defending zone

Win rate at each dot; the small numbers are draws and the xG swing (×100) of winning rather than losing there.

By zone

  • Offensive zone40.0% 10–15
  • Neutral zone45.5% 15–18
  • Defensive zone39.7% 23–35

By strength

  • Even strength48.3% 28–30
  • Shorthanded33.3% 19–38

What a win leads to

Shot attempts in the next 20 seconds, for minus against, per 100 draws: +19 after a win, −35 after a loss. Each win was worth 4.9 expected goals per 100 draws more than a loss.

Most-faced opponents

Season by season

SeasonDrawsWin rateAgainst average
2009–10250.0%48.8%
2010–11633.3%33.3%
2011–12560.0%61.0%
2012–132245.5%45.7%
2013–141546.7%46.9%
2014–1520.0%6.1%
2015–161323.1%23.1%
2016–171353.8%54.5%
2017–182245.5%44.5%
2018–191241.7%42.4%
2019–2040.0%4.6%

Finishing

Model-based

Did the goals match the chances?

Goals against expected goals

Cumulative goals (solid) and individual xG (dashed) through the season. The gap is finishing: above the dashed line, the player scored more than an average shooter would from the same chances.

+8.6 goals above expected

050100150200100200300400500600Game

Goals above expected, everyone at the same position with 20+ games

−500+50+100+150