NHL statistics · 2026-27 regular season

NHL expected goals leaders

Individual expected goals (ixG): every unblocked attempt weighed by its chance of scoring from that spot, shot type and strength, against the goals actually scored.

#Player
1Tomas Hertl#48 · VGK · C433.3−0.321.1573.0221.4%
2Andrei Svechnikov#37 · CAR · R413.2−2.225.1292.716.7%
3Brandon Hagel#38 · TBL · L312.8−1.823.1212.535.9%
4Alexis Lafrenière#13 · NYR · L532.7+0.315.1791.6927.3%
5John Tavares#91 · TOR · C412.3−1.319.1232.007.1%
6Leon Draisaitl#29 · EDM · C332.3+0.721.1112.1418.8%
7Matt Boldy#12 · MIN · L302.3−2.321.1082.160.0%
8Kyle Connor#81 · WPG · L332.2+0.826.0862.1215.0%
9Nick Schmaltz#8 · UTA · C452.2+2.818.1201.7829.4%
10Frank Nazar#91 · CHI · C412.1−1.110.2141.7212.5%
11Will Cuylle#50 · NYR · L502.1−2.121.1001.660.0%
12Tage Thompson#72 · BUF · C322.1−0.124.0862.0611.8%
13Cole Perfetti#91 · WPG · C322.0−0.019.1072.2420.0%
14Dylan Guenther#11 · UTA · R432.0+1.023.0881.8817.6%
15Adrian Kempe#9 · LAK · R312.0−1.020.1001.918.3%
16William Eklund#27 · OTT · L312.0−1.014.1422.2011.1%
17Kirill Kaprizov#97 · MIN · L332.0+1.018.1101.8433.3%
18Vasily Podkolzin#92 · EDM · R332.0+1.017.1152.0723.1%
19Sam Reinhart#13 · FLA · C401.9−1.918.1061.300.0%
20Pavel Dorofeyev#16 · NYR · R511.9−0.921.0891.386.7%
21J.T. Miller#10 · NYR · C511.9−0.915.1251.3011.1%
22William Nylander#88 · TOR · R431.9+1.121.0881.3833.3%
23Auston Matthews#34 · TOR · C421.8+0.221.0871.2214.3%
24Sebastian Aho#20 · CAR · C441.8+2.221.0841.3326.7%
25Mark Stone#61 · VGK · R421.8+0.210.1771.4525.0%
26Jake Guentzel#59 · TBL · C311.7−0.712.1451.6410.0%
27Clayton Keller#9 · UTA · R411.7−0.717.1021.469.1%
28Jack Quinn#22 · BUF · R321.7+0.321.0791.6218.2%
29Kirill Marchenko#86 · TOR · R411.6−0.617.0951.238.3%
30Eeli Tolvanen#17 · NYR · R531.6+1.48.2001.4150.0%
31Bobby McMann#74 · SEA · C421.6+0.423.0681.4113.3%
32Steven Stamkos#91 · NSH · C331.6+1.414.1111.6037.5%
33Brett Howden#21 · VGK · C401.6−1.614.1111.430.0%
34Michael Brandsegg-Nygård#28 · DET · R301.5−1.515.1032.210.0%
35Alex DeBrincat#93 · DET · R321.5+0.511.1371.4725.0%
36Jackson Blake#53 · CAR · R401.5−1.514.1081.200.0%
37Jack Hughes#86 · NJD · C311.5−0.518.0821.307.7%
38Mika Zibanejad#93 · NYR · C511.4−0.414.1020.8311.1%
39Jordan Eberle#7 · SEA · R421.4+0.614.1021.3228.6%
40Wyatt Johnston#53 · DAL · C301.3−1.312.1111.300.0%
41Tyson Foerster#71 · PHI · R411.3−0.316.0831.0910.0%
42Sandis Vilmanis#95 · FLA · L401.3−1.313.1011.600.0%
43Sidney Crosby#87 · PIT · C301.3−1.315.0871.370.0%
44Timo Meier#28 · NJD · R301.3−1.321.0611.410.0%
45Brayden Point#21 · TBL · C311.3−0.314.0921.2614.3%
46Pontus Holmberg#29 · TBL · R311.3−0.38.1611.7816.7%
47Pavel Zacha#18 · BOS · C401.3−1.315.0851.030.0%
48Zach Benson#6 · BUF · L301.3−1.311.1161.300.0%
49Bo Horvat#14 · NYI · C321.3+0.715.0841.2920.0%
50Luke Evangelista#77 · NJD · R321.2+0.814.0891.3422.2%
About this table

How to read it

Expected goals separate getting chances from finishing them. A player with high ixG and few goals is getting to the right places and has been unlucky or cold; one with many more goals than ixG is either an elite shooter or running hot. ixG per 60 minutes is the fairest comparison between players with different roles.

GP
Games played.
G
Goals.
ixG
Individual expected goals: the chance of scoring of every unblocked attempt he took (location, shot type, strength, rebounds), added up.
G−xG
Goals minus ixG: finishing. Above zero, he scores more than his chances predict. Elite shooters stay above zero year after year; for most players it drifts back towards zero.
Att
Unblocked shot attempts: shots on goal, goals and misses (blocked attempts are left out because their location is where they were blocked).
xG/Att
Expected goals per attempt: the average quality of his chances. A higher number means more shots from the slot and the crease.
ixG/60
Individual expected goals per 60 minutes on the ice, so players with different ice time can be compared.
S%
Shooting percentage.

How expected goals are built, and how well the model predicts, is on the methodology page.

Guide

What expected goals measure

Expected goals (xG) give every unblocked shot attempt a probability of scoring, from where it was taken, the shot type and what happened just before it. A shot from the slot after a pass across the ice is worth far more than a wrist shot from the point. Add them up and you get the goals a player’s chances would usually produce.

Goals minus expected goals is finishing. A player well above his expected goals is converting more than his chances suggest, which some elite shooters do year after year and most players do for a few weeks. Over a season, expected goals predict future scoring better than goals do. How the model works.

Season reports refresh once a day after new finals.