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The Lab · Leaderboards
2025-26last seasonAs of Sun, Sep 20

Whole-league leaderboards

Rank every qualified skater on any of 30 metrics — the on-off impact, puck-security, and finishing-luck numbers most sites never surface. Pick a metric, pick a pool, and read the whole league sorted the model's way. Percentiles are always position-relative.

Relative xG% (on-off)

n = 201 qualified D

How much a team's expected-goals share improves with this player on the ice at 5-on-5 versus off it.

5on5 · higher is better — leaders on top · %

#TmPlayerValuevs. position
1NYR+12.6%
ELITE
100th
2VAN+12.4%
ELITE
100th
3EDM+7.6%
ELITE
99th
4EDM+7.3%
ELITE
98th
5CBJ+6.9%
ELITE
98th
6OTT+6.6%
ELITE
97th
7CBJ+6.5%
ELITE
97th
8STL+6.1%
ELITE
97th
9MTL+5.8%
ELITE
96th
10SEA+5.4%
ELITE
96th
11NYR+5.2%
ELITE
95th
12SJS+5.1%
ELITE
95th
13DET+5.1%
ELITE
94th
14UTA+4.7%
ELITE
93rd
15TOR+4.6%
ELITE
93rd
16STL+4.4%
ELITE
92nd
17CGY+4.3%
ELITE
92nd
18WSH+4.2%
ELITE
92nd
19CHI+4.1%
ELITE
91st
20COL+4.0%
ELITE
91st
21FLA+4.0%
ELITE
90th
22NYI+4.0%
STRONG
89th
23BOS+3.9%
STRONG
89th
24CGY+3.6%
STRONG
88th
25TBL+3.5%
STRONG
88th
26BUF+3.5%
STRONG
87th
27NSH+3.5%
STRONG
87th
28UTA+3.4%
STRONG
87th
29STL+3.2%
STRONG
86th
30CAR+3.2%
STRONG
86th
31CGY+3.2%
STRONG
85th
32SEA+3.1%
STRONG
85th
33NYI+3.1%
STRONG
84th
34LAK+2.9%
STRONG
83rd
35SEA+2.7%
STRONG
83rd
36BOS+2.7%
STRONG
82nd
37WPG+2.6%
STRONG
82nd
38CBJ+2.6%
STRONG
81st
39FLA+2.5%
STRONG
81st
40TBL+2.5%
STRONG
80th
41UTA+2.5%
STRONG
80th
42NYR+2.3%
STRONG
79th
43TOR+2.3%
STRONG
79th
44DET+2.2%
STRONG
79th
45ANA+2.1%
STRONG
78th
46DAL+2.0%
STRONG
77th
47WSH+2.0%
STRONG
77th
48UTA+2.0%
STRONG
76th
49WPG+1.9%
STRONG
76th
50OTT+1.9%
STRONG
75th
51VAN+1.9%
STRONG
75th
52CAR+1.8%
STRONG
74th
53PIT+1.8%
STRONG
74th
54SJS+1.7%
STRONG
73rd
55CAR+1.7%
STRONG
73rd
56COL+1.7%
STRONG
72nd
57MTL+1.7%
STRONG
72nd
58WSH+1.6%
STRONG
71st
59PIT+1.5%
STRONG
71st
60STL+1.5%
STRONG
71st
61LAK+1.4%
STRONG
70th
62PHI+1.4%
STRONG
70th
63TBL+1.2%
AVERAGE
69th
64STL+1.2%
AVERAGE
69th
65SJS+1.2%
AVERAGE
68th
66CAR+1.1%
AVERAGE
68th
67DAL+1.0%
AVERAGE
67th
68CBJ+1.0%
AVERAGE
67th
69NSH+0.9%
AVERAGE
66th
70CBJ+0.9%
AVERAGE
65th
71ANA+0.9%
AVERAGE
65th
72TOR+0.8%
AVERAGE
65th
73FLA+0.8%
AVERAGE
64th
74CHI+0.8%
AVERAGE
63rd
75NSH+0.8%
AVERAGE
63rd
76TOR+0.8%
AVERAGE
63rd
77NYI+0.7%
AVERAGE
62nd
78UTA+0.7%
AVERAGE
62nd
79BOS+0.6%
AVERAGE
61st
80NSH+0.6%
AVERAGE
61st
81VGK+0.5%
AVERAGE
60th
82COL+0.5%
AVERAGE
59th
83PIT+0.5%
AVERAGE
59th
84BUF+0.4%
AVERAGE
58th
85NSH+0.4%
AVERAGE
58th
86COL+0.4%
AVERAGE
57th
87VGK+0.4%
AVERAGE
57th
88NSH+0.4%
AVERAGE
56th
89WPG+0.3%
AVERAGE
56th
90VAN+0.3%
AVERAGE
55th
91OTT+0.2%
AVERAGE
55th
92PIT+0.2%
AVERAGE
54th
93VGK+0.2%
AVERAGE
54th
94ANA+0.1%
AVERAGE
54th
95NJD+0.1%
AVERAGE
53rd
96PHI-0.0%
AVERAGE
53rd
97BOS-0.0%
AVERAGE
52nd
98LAK-0.1%
AVERAGE
52nd
99NYI-0.1%
AVERAGE
51st
100BUF-0.1%
AVERAGE
51st

◆ Method · Single-metric leaderboard over players with games_played >= minGP in the metric's situation; percentiles are position-group relative. Data: MoneyPuck data/mp_skaters_2025.csv. · percentiles are position-relative, model-estimated proxies from MoneyPuck aggregates via the analytics sidecar.