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Ice Lab

Left wing · #88

Jamie McGinn

San Jose Sharks Colorado Avalanche Buffalo Sabres Anaheim Ducks Arizona Coyotes Florida Panthers(traded during the season)
Age
38
Shoots
Left
Height
185 cm
Weight
93 kg
Born
Fergus, CAN
Draft
2006, round 2, #36 (SJS)

Career · 2009–10 to 2018–19

Games
582
Goals
113
Points
214
TOI per game
13:37
xGF% (5v5)
46.7%
Goals above expected
−2.9

Season by season

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

2009–10SJS5910313−310:007613.2%07.4–
2010–11SJS49156−611:35631.6%06.748.6%
2011–12SJS61121224+112:3310411.5%411.852.9%
2011–12COL178513−416:405514.5%45.953.7%
2011–12All teams78201737−313:2715912.6%817.653.1%
2012–13COL47111122−1317:171288.6%713.147.1%
2013–14COL79191938−315:4716711.4%918.945.7%
2014–15COL19426−914:463611.1%14.232.9%
2015–16BUF63141327−1014:1010912.8%914.149.1%
2015–16ANA218412+314:414717.0%36.450.7%
2015–16All teams84221739−714:1815614.1%1220.549.5%
2016–17ARI729817−2313:101167.8%211.343.9%
2017–18FLA76131629−513:2711611.2%613.744.9%
2018–19FLA19437−510:412317.4%12.645.2%
Total6 teams582113101214−7713:371,04010.9%46115.946.7%

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)
00.20.40.60.811.2100200300400500
10m15m20m100200300400500Game

Player card

Model-based

How 2009–10 to 2018–19 compares with everyone else at the position over the same seasons, and the players with the most similar profile.

Overall rating

3rd line

47th 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

2nd line
  • Goals /600.8676th pct
  • Assists /600.7739th pct
  • ixG /600.8880th pct
  • Goals above expected−2.938th pct

Play-driving

4th line
  • xGF% (5v5)46.7%28th pct
  • CF% (5v5)46.9%26th pct
  • Relative xGF%−2.235th pct
  • Penalty diff /600.0039th pct

Usage

2nd line
  • TOI per game13:3753rd pct
  • PP time share27.8%62nd pct
  • Offensive zone starts61.1%65th pct
  • Quality of competition24.3%64th 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. Gilbert BruleEDM/PHX0.77
  2. David JonesCOL/CGY0.75
  3. Jimmy HayesCHI/FLA/BOS/NJD0.73
  4. David ClarksonNJD/TOR0.72
  5. Joffrey LupulANA/TOR0.72
  6. Anthony BeauvillierNYI0.72

Faceoffs

How often McGinn wins the draw over 2009–10 to 2018–19, against whom and where, and what a win leads to. Ranked among players with 1944+ draws over the same seasons.

Win rate

48.8%

39–41 · below the 1944 draws of a regular

Against an average centre

49.7%

Opponents won 50.9% of their draws; an average centre would have won 49.1% against them.

Wins above average

0

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

Draws per game

1.3

80 draws in all.

By dot, attacking to the right

83%6 · 0.040%25 · −2.014%7 · +1.786%7 · −0.540%5 · 0.033%6 · 0.033%3 · +0.953%17 · +1.775%4 · +3.8Attacking 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 zone36.4% 12–21
  • Neutral zone59.3% 16–11
  • Defensive zone55.0% 11–9

By strength

  • Even strength50.8% 33–32
  • Power play40.0% 4–6
  • Shorthanded40.0% 2–3

What a win leads to

Shot attempts in the next 20 seconds, for minus against, per 100 draws: +15 after a win, +7 after a loss. Each win was worth -0.2 expected goals per 100 draws more than a loss.

Most-faced opponents

Season by season

SeasonDrawsWin rateAgainst average
2009–101643.8%42.2%
2010–111172.7%72.1%
2011–12785.7%85.4%
2012–13650.0%54.0%
2013–14250.0%56.7%
2014–151100.0%102.6%
2015–16757.1%60.3%
2016–17333.3%34.8%
2017–182626.9%28.6%
2018–191100.0%98.1%

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.

−2.9 goals above expected

020406080100120100200300400500Game

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

−500+50+100+150