Buy-Low / Sell-High

2025-26 · finishing = goals − expected goals (xGF). Ranked by SNAKEBIT: the luck share of the deficit (chronic under-finishers discounted) PLUS goals lost to posts/crossbars. Empty-netters removed before the split.

❓ How to read this (plain English)

Finding players whose goal totals lie about how well they're actually playing.

G − xG
Goals scored minus goals EXPECTED from the shots taken. Negative = getting robbed; positive = running hot.
Luck (regresses)
The share of that gap that's genuinely bad/good luck — it fades. This is the number that predicts a rebound.
Skill (persists)
The share that's just how this player finishes, year after year. Chronic under-finishers are NOT buy-lows.
Iron
Posts + crossbars hit (and the goal value of those shots). Pure bad luck — centimeters from goals.
ENG
Empty-net goals — real points, but they say nothing about shooting skill, so we remove them before judging.
Snakebit
The bottom line: luck deficit plus iron. Most negative = most deserving of better results = best buy.
#PlayerTeamPosGPGxGFSOGG − xGLuck (regresses)Skill (persists)IronENGHD finishHD shotsSnakebit score
1Cole Sillinger CBJ · CCBJC81814.5136-6.5-5.4-4.13 (0.2 xG)3-3.734-5.6
2Andrew Copp DET · CDETC79915.5115-6.5-5.2-4.33-5.960-5.2
3Jonathan Drouin · LL64411.786-7.7-4.8-2.93 (0.2 xG)-3.729-5.0
4Ross Colton NSH · CNSHC73915.82153-6.8-4.8-4.03 (0.2 xG)2-5.543-5.0
5Cole Perfetti WPG · CWPGC681218.04136-6.0-3.6-3.47 (0.8 xG)1-1.548-4.4
6Jack McBain UTA · CUTAC75915.8106-6.8-4.3-3.51-5.362-4.3
7Nazem Kadri COL · CCOLC771624.53213-8.5-3.7-4.83 (0.3 xG)-5.870-4.0
8Brendan Gallagher VAN · RVANR77713.79121-6.8-3.9-2.92 (0.1 xG)-4.347-4.0
9Kent Johnson CBJ · CCBJC76712.23114-5.2-3.8-2.42 (0.2 xG)1-0.734-4.0
10Barrett Hayton UTA · CUTAC671013.91119-3.9-4.0-2.93-7.558-4.0
11Mackie Samoskevich SEA · RSEAR771219.91161-7.9-3.9-4.0-3.9
12Yakov Trenin MIN · CMINC82612.4198-6.4-3.9-2.5-5.347-3.9
13Marco Kasper DET · CDETC81914.77131-5.8-3.8-3.02 (0 xG)1-4.352-3.8
14Phillip Danault MTL · CMTLC75610.5591-4.5-3.6-2.02 (0.2 xG)1-3.734-3.8
15Tomas Hertl VGK · CVGKC822430.86202-6.9-3.4-5.52 (0.2 xG)2-5.4113-3.6
16Timo Meier NJD · RNJDR772430.8269-6.8-3.4-5.44 (0.2 xG)2-491-3.6
17Quinn Hughes MIN · DMIND74712.91187-5.9-3.5-2.42 (0.1 xG)010-3.6
18Dawson Mercer NJD · CNJDC822020.66158-0.7-3.2-3.53 (0.4 xG)6-4.669-3.6
19Anders Lee UTA · LUTAL821927.08199-8.1-3.3-4.72 (0.2 xG)-6.2107-3.5
20Adam Lowry WPG · CWPGC70510.1371-5.1-3.3-1.81 (0.1 xG)-0.930-3.4
21William Eklund OTT · LOTTL781521.71176-6.7-3.1-3.63 (0.2 xG)-2.674-3.3
22Oliver Bjorkstrand NYR · RNYRR801217.84130-5.8-3.0-2.84 (0.3 xG)+0.135-3.3
23Luke Evangelista NSH · RNSHR811216.68176-4.7-3.0-2.72 (0.2 xG)1-2.754-3.2
24Emmitt Finnie DET · CDETC821317.43120-4.4-2.8-2.64 (0.4 xG)1-5.870-3.2
25Jake DeBrusk VAN · LVANL812329.74219-6.7-2.6-4.15 (0.5 xG)-1.9121-3.1
26Sean Monahan CBJ · CCBJC781316.77131-3.8-3.1-2.71 (0 xG)2-3.156-3.1
27Brady Tkachuk FLA · LFLAL602224.96221-3.0-3.0-4.04-6.689-3.0
28Berkly Catton SEA · CSEAC66711.2678-4.3-2.7-1.62 (0.2 xG)-1.131-2.9
29Christian Dvorak PHI · CPHIC801822.24151-4.2-2.9-3.42-3.277-2.9
30Gabriel Landeskog COL · LCOLL601417.7132-3.7-2.4-2.32 (0.5 xG)1+0.155-2.9
31Braeden Bowman VGK · RVGKR54812.4975-4.5-2.7-1.82 (0.1 xG)-2.8
32Tanner Jeannot BOS · LBOSL77610.3378-4.3-2.8-1.5-2.332-2.8
33Eeli Tolvanen · RR781214.84141-2.8-2.7-2.12 (0.1 xG)2-2.126-2.8
34Claude Giroux OTT · ROTTR821414.55138-0.6-2.6-2.01 (0.2 xG)4-0.935-2.8
35Yanni Gourde TBL · CTBLC82913.26114-4.3-2.5-1.81 (0.2 xG)-2.136-2.7
36Jordan Martinook CAR · LCARL771213.17109-1.2-2.5-1.72 (0.2 xG)3-1.729-2.7
37Jonathan Marchessault NSH · CNSHC621215.29132-3.3-2.4-1.93 (0.2 xG)1-1.553-2.6
38Zach Benson BUF · LBUFL651314.51116-1.5-2.6-2.01 (0 xG)3-2.362-2.6
39Matt Coronato CGY · RCGYR801821.98197-4.0-2.3-2.73 (0.2 xG)1-4.156-2.5
40Roope Hintz DAL · CDALC531517.19126-2.2-2.2-2.02 (0.3 xG)2-2.5