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Ice Lab

Left wing · #36

Jussi Jokinen

Carolina Hurricanes Pittsburgh Penguins Florida Panthers Edmonton Oilers Los Angeles Kings Columbus Blue Jackets Vancouver Canucks(traded during the season)
Age
43
Shoots
Left
Height
183 cm
Weight
87 kg
Born
Kalajoki, FIN
Draft
2001, round 6, #192 (DAL)

Career · 2009–10 to 2017–18

Games
645
Goals
137
Points
391
TOI per game
16:29
xGF% (5v5)
50.9%
Goals above expected
+18.7

Season by season

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

2009–10CAR81303565+316:4916018.8%2319.9–
2010–11CAR70193352+317:1313614.0%1816.048.6%
2011–12CAR79123446−217:4011810.2%1815.148.8%
2012–13CAR336511−815:35619.8%37.553.5%
2012–13PIT107411+314:551353.8%41.746.8%
2012–13All teams4313922−515:267417.6%79.252.1%
2013–14PIT81213657+1215:4217212.2%2114.053.7%
2014–15FLA8183644−216:441346.0%910.650.1%
2015–16FLA81184260+2518:1715311.8%1215.855.8%
2016–17FLA69111728−1517:251189.3%1010.948.2%
2017–18EDM14011−312:19220.0%12.068.2%
2017–18LAK18145011:15195.3%10.941.9%
2017–18CBJ14011−210:01130.0%11.548.9%
2017–18VAN144610+712:491921.1%22.249.6%
2017–18All teams6051217+211:35736.8%56.651.1%
Total7 teams645137254391+2116:291,13812.0%123118.350.9%

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
10m15m20m100200300400500600Game

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

83rd 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 /600.7767th pct
  • Assists /601.4390th pct
  • ixG /600.6747th pct
  • Goals above expected+18.794th pct

Play-driving

2nd line
  • xGF% (5v5)50.9%68th pct
  • CF% (5v5)52.0%80th pct
  • Relative xGF%+2.481st pct
  • Penalty diff /600.0142nd pct

Usage

2nd line
  • TOI per game16:2980th pct
  • PP time share43.3%80th pct
  • Offensive zone starts55.0%46th pct
  • Quality of competition24.5%69th 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. David KrejciBOS0.95
  2. Nicklas BackstromWSH0.92
  3. Joe ThorntonSJS0.92
  4. Derek RoyBUF/STL/NSH/EDM0.91
  5. Tim ConnollyBUF/TOR0.91
  6. Patrik EliasNJD0.91

Faceoffs

How often Jokinen 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

53.8%

1611–1381 · #31 of 187 regulars, 84th percentile

Against an average centre

54.2%

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

Wins above average

+124

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

Draws per game

5.5

2,992 draws in all.

By dot, attacking to the right

54%356 · 0.051%736 · +1.655%537 · +2.064%103 · +0.646%114 · +0.459%117 · −0.151%84 · +0.956%618 · +1.350%327 · +1.8Attacking 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 zone52.9% 674–599
  • Neutral zone54.8% 424–350
  • Defensive zone54.3% 513–432

By strength

  • Even strength53.8% 1139–979
  • Power play54.5% 316–264
  • Shorthanded54.1% 152–129

What a win leads to

Shot attempts in the next 20 seconds, for minus against, per 100 draws: +16 after a win, −10 after a loss. Each win was worth 1.2 expected goals per 100 draws more than a loss.

Most-faced opponents

Season by season

SeasonDrawsWin rateAgainst average
2009–1026651.1%51.5%
2010–1132052.8%53.9%
2011–1283255.2%55.1%
2012–1343257.9%58.0%
2013–1429953.5%53.8%
2014–1525050.4%51.4%
2015–1626251.5%52.0%
2016–1714452.1%52.4%
2017–1818754.0%54.1%

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.

+18.7 goals above expected

050100150100200300400500600Game

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

−500+50+100