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Ice Lab

Right wing · #10

Kris Versteeg

Chicago Blackhawks Toronto Maple Leafs Philadelphia Flyers Florida Panthers Carolina Hurricanes Los Angeles Kings Calgary Flames(traded during the season)
Age
40
Shoots
Right
Height
180 cm
Weight
80 kg
Born
Lethbridge, CAN
Draft
2004, round 5, #134 (BOS)

Career · 2009–10 to 2017–18

Games
552
Goals
125
Points
301
TOI per game
16:07
xGF% (5v5)
48.8%
Goals above expected
+13.6

Season by season

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

2009–10CHI79202444+815:4418410.9%1219.4–
2010–11TOR53142135−1318:5612810.9%1312.748.2%
2010–11PHI277411+415:225213.5%14.745.2%
2010–11All teams80212546−917:4418011.7%1417.447.3%
2011–12FLA71233154+419:5518112.7%1816.849.1%
2012–13FLA10224−816:532010.0%11.838.6%
2013–14FLA18257−915:42474.3%23.042.6%
2013–14CHI63101929+914:061109.1%69.451.1%
2013–14All teams81122436014:281577.6%812.449.4%
2014–15CHI61142034+1115:5113410.4%513.349.4%
2015–16CAR63112233−616:231368.1%913.754.6%
2015–16LAK14415+610:542020.0%02.658.9%
2015–16All teams77152338015:231569.6%916.455.1%
2016–17CGY69152237−314:4413611.0%1610.642.2%
2017–18CGY24358−813:11496.1%53.145.2%
Total7 teams552125176301−516:071,19710.4%88111.448.8%

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)
00.511.5100200300400500
10m12m14m16m18m20m22m100200300400500Game

Player card

Model-based

How 2009–10 to 2017–18 compares with everyone else at the position over the same seasons, and the players with the most similar profile.

Overall rating

1st line

80th 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 /600.8474th pct
  • Assists /601.1977th pct
  • ixG /600.7562nd pct
  • Goals above expected+13.691st pct

Play-driving

2nd line
  • xGF% (5v5)48.8%47th pct
  • CF% (5v5)51.9%79th pct
  • Relative xGF%−1.641st pct
  • Penalty diff /600.1961st pct

Usage

2nd line
  • TOI per game16:0775th pct
  • PP time share43.9%80th pct
  • Offensive zone starts69.9%93rd pct
  • Quality of competition24.7%75th 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. Victor RaskCAR0.93
  2. Brad RichardsDAL/NYR/CHI/DET0.93
  3. Tomas FleischmannWSH/FLA/MTL/CHI0.92
  4. Patrick KaneCHI0.92
  5. Kyle TurrisOTT0.92
  6. Gustav NyquistDET0.91

Faceoffs

How often Versteeg wins the draw over 2009–10 to 2017–18, against whom and where, and what a win leads to. Ranked among players with 1739+ draws over the same seasons.

Win rate

45.4%

339–407 · below the 1739 draws of a regular

Against an average centre

45.9%

Opponents won 50.5% of their draws; an average centre would have won 49.5% against them.

Wins above average

−31

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

Draws per game

2.5

746 draws in all.

By dot, attacking to the right

46%76 · +0.548%126 · +3.945%298 · +1.955%29 · +1.038%47 · +1.063%19 · +2.429%41 · +3.551%39 · −0.344%71 · +0.8Attacking 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 zone46.2% 196–228
  • Neutral zone43.9% 93–119
  • Defensive zone45.5% 50–60

By strength

  • Even strength46.2% 265–308
  • Power play42.4% 64–87
  • Shorthanded40.0% 8–12

What a win leads to

Shot attempts in the next 20 seconds, for minus against, per 100 draws: +23 after a win, −8 after a loss. Each win was worth 1.9 expected goals per 100 draws more than a loss.

Most-faced opponents

Season by season

SeasonDrawsWin rateAgainst average
2009–1018342.1%42.2%
2010–1113048.5%48.7%
2011–126532.3%32.9%
2012–1350.0%1.6%
2013–1411947.1%47.6%
2014–154831.3%32.2%
2015–161650.0%49.9%
2016–1710252.0%52.6%
2017–187859.0%60.0%

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.

+13.6 goals above expected

050100100200300400500Game

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

−500+50+100