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Ice Lab

Left wing · #55

Cody McLeod

Colorado Avalanche Nashville Predators New York Rangers(traded during the season)
Age
42
Shoots
Left
Height
188 cm
Weight
93 kg
Born
Binscarth, CAN
Draft
Undrafted

Career · 2009–10 to 2018–19

Games
531
Goals
47
Points
88
TOI per game
10:21
xGF% (5v5)
44.0%
Goals above expected
−11.0
ShowAll teamsColorado AvalancheNashville PredatorsNew York Rangers

Season by season

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

2009–10COL7471118−1312:561176.0%011.6–
2010–11COL71538−79:47736.8%27.746.1%
2011–12COL75651107:12629.7%06.148.8%
2012–13COL488412+413:057910.1%18.950.9%
2013–14COL715813+210:20766.6%05.738.8%
2014–15COL827512−211:11947.4%010.638.5%
2015–16COL828513+110:327311.0%16.745.2%
2016–17COL28101−25:53128.3%00.831.2%
2016–17NSH31415−18:201822.2%01.537.1%
2016–17All teams59516−37:103016.7%02.335.3%
2017–18NSH2311206:49119.1%00.940.4%
2017–18NYR25022−117:54250.0%02.235.2%
2017–18All teams48134−117:23362.8%03.137.1%
2018–19NYR31101−106:49214.8%02.136.1%
2018–19NSH7000−35:0210.0%00.442.0%
2018–19All teams38101−136:29224.5%02.537.2%
Total3 teams648534598−429:496628.0%465.142.6%

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)
00.20.40.60.8100200300400500
4m6m8m10m12m14m16m18m100200300400500Game

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

Extra / AHL

3rd 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

Extra / AHL
  • Goals /600.5030th pct
  • Assists /600.428th pct
  • ixG /600.6137th pct
  • Goals above expected−12.19th pct

Play-driving

Extra / AHL
  • xGF% (5v5)42.6%8th pct
  • CF% (5v5)43.4%7th pct
  • Relative xGF%−4.917th pct
  • Penalty diff /60-0.714th pct

Usage

Extra / AHL
  • TOI per game9:4912th pct
  • PP time share3.7%26th pct
  • Offensive zone starts51.7%37th pct
  • Quality of competition22.9%12th 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. Mike BlundenCBJ0.96
  2. Jay RosehillTOR/PHI0.95
  3. Jody ShelleySJS/PHI0.95
  4. Brad StaubitzSJS/MIN/ANA0.94
  5. Patrick BordeleauCOL0.93
  6. Eric BoultonATL/NJD/NYI0.93

Faceoffs

How often McLeod 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

31.7%

20–43 · below the 1944 draws of a regular

Against an average centre

31.7%

Opponents won 50.0% of their draws; an average centre would have won 50.0% against them.

Wins above average

−12

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

Draws per game

1.3

63 draws in all.

By dot, attacking to the right

20%5 · +0.622%18 · −1.614%7 · −0.675%4 · +0.1100%1 · –44%9 · 0.025%4 · +3.017%6 · +3.844%9 · −0.2Attacking 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 zone20.0% 5–20
  • Neutral zone43.5% 10–13
  • Defensive zone33.3% 5–10

By strength

  • Even strength39.5% 15–23
  • Power play0.0% 0–2
  • Shorthanded21.7% 5–18

What a win leads to

Shot attempts in the next 20 seconds, for minus against, per 100 draws: +10 after a win, −2 after a loss. Each win was worth 0.3 expected goals per 100 draws more than a loss.

Most-faced opponents

Season by season

SeasonDrawsWin rateAgainst average
2009–101330.8%30.7%
2010–11837.5%37.7%
2011–12366.7%66.6%
2012–131741.2%40.9%
2013–141020.0%20.5%
2014–15911.1%11.0%
2015–161100.0%100.9%
2016–1710.0%-6.3%
2018–1910.0%3.6%

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.

−11.0 goals above expected

0102030405060100200300400500Game

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

−500+50+100+150