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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.

Takeaway - Giveaway / 60

n = 201 qualified D

Net puck-battle result: takeaways minus giveaways per 60 minutes.

all · higher is better — leaders on top · /60

#TmPlayerValuevs. position
1FLA-0.68
ELITE
100th
2MTL-0.95
ELITE
100th
3FLA-0.99
ELITE
99th
4ANA-1.06
ELITE
99th
5ANA-1.24
ELITE
98th
6SEA-1.27
ELITE
97th
7CHI-1.28
ELITE
97th
8STL-1.29
ELITE
96th
9PIT-1.31
ELITE
96th
10PHI-1.32
ELITE
95th
11BUF-1.33
ELITE
95th
12NYR-1.34
ELITE
94th
13CAR-1.34
ELITE
94th
14NYI-1.37
ELITE
93rd
15COL-1.38
ELITE
93rd
16LAK-1.42
ELITE
92nd
17WSH-1.46
ELITE
92nd
18MIN-1.48
ELITE
91st
19NSH-1.48
ELITE
91st
20COL-1.48
ELITE
91st
21CAR-1.53
ELITE
90th
22STL-1.53
ELITE
90th
23MTL-1.54
STRONG
89th
24NYI-1.54
STRONG
89th
25TBL-1.55
STRONG
88th
26DET-1.56
STRONG
88th
27WSH-1.58
STRONG
87th
28VGK-1.58
STRONG
86th
29OTT-1.59
STRONG
86th
30MIN-1.59
STRONG
86th
31CAR-1.61
STRONG
85th
32WPG-1.62
STRONG
85th
33CBJ-1.64
STRONG
84th
34MIN-1.65
STRONG
83rd
35DAL-1.65
STRONG
83rd
36PHI-1.69
STRONG
83rd
37MIN-1.70
STRONG
82nd
38VGK-1.72
STRONG
81st
39DET-1.72
STRONG
81st
40PHI-1.72
STRONG
81st
41CGY-1.73
STRONG
80th
42VGK-1.75
STRONG
80th
43ANA-1.75
STRONG
79th
44FLA-1.78
STRONG
79th
45DAL-1.78
STRONG
78th
46OTT-1.80
STRONG
78th
47SJS-1.81
STRONG
77th
48NYR-1.82
STRONG
77th
49DAL-1.84
STRONG
76th
50OTT-1.85
STRONG
76th
51NJD-1.87
STRONG
75th
52NYI-1.90
STRONG
75th
53EDM-1.91
STRONG
74th
54PHI-1.91
STRONG
73rd
55CBJ-1.91
STRONG
73rd
56NSH-1.92
STRONG
72nd
57PIT-1.93
STRONG
72nd
58WPG-1.94
STRONG
72nd
59NSH-1.95
STRONG
71st
60BUF-1.95
STRONG
70th
61TBL-1.97
STRONG
70th
62MTL-1.97
AVERAGE
69th
63BOS-1.97
AVERAGE
69th
64TOR-1.98
AVERAGE
69th
65CAR-1.99
AVERAGE
68th
66DET-2.00
AVERAGE
67th
67LAK-2.00
AVERAGE
67th
68STL-2.00
AVERAGE
67th
69SEA-2.02
AVERAGE
66th
70BUF-2.03
AVERAGE
66th
71TBL-2.04
AVERAGE
65th
72CHI-2.05
AVERAGE
65th
73NYR-2.06
AVERAGE
64th
74OTT-2.07
AVERAGE
63rd
75OTT-2.08
AVERAGE
63rd
76WSH-2.09
AVERAGE
63rd
77ANA-2.09
AVERAGE
62nd
78WSH-2.10
AVERAGE
62nd
79BOS-2.10
AVERAGE
61st
80CHI-2.11
AVERAGE
61st
81SEA-2.11
AVERAGE
60th
82DET-2.12
AVERAGE
59th
83BUF-2.12
AVERAGE
59th
84WPG-2.12
AVERAGE
58th
85TBL-2.14
AVERAGE
58th
86CAR-2.14
AVERAGE
57th
87ANA-2.14
AVERAGE
57th
88TBL-2.14
AVERAGE
56th
89EDM-2.15
AVERAGE
56th
90BOS-2.16
AVERAGE
56th
91VAN-2.17
AVERAGE
55th
92CBJ-2.17
AVERAGE
54th
93ANA-2.17
AVERAGE
54th
94NYI-2.19
AVERAGE
53rd
95VGK-2.20
AVERAGE
53rd
96CHI-2.20
AVERAGE
53rd
97COL-2.20
AVERAGE
52nd
98PIT-2.20
AVERAGE
52nd
99MIN-2.21
AVERAGE
51st
100NSH-2.23
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.