Our expected goals added metric allows us to compare two stat lines, even if the players play different positions. The idea is to normalize different plays to get to a standard view of how many equivalent goals a player generated.

This table shows the cumulative season totals for the top 100 players to give a view of who is having the most productive season. We have included the primary role for each player so you can get a sense for how the role they play on their team. The primary role is calculated based on the percentage of a player’s value that comes from faceoffs vs offensive plays vs defensive plays. I have also put together a detailed post to explain how this classification works.

The rankings below are, by default, sorted by total EGA. That is, the total amount of value a player has produced for the season, across all play types. I have also separated out the faceoff-only EGA, which accumulates the value each player has produced specifically on faceoffs. So if a FOGO scores a goal off a faceoff, that contribution would be captured in the total value but not in the faceoff-only EGA column.

The basic philosophy here is that we want to rank based on the cumulative contribution. But we also don’t want to lose sight of the fact that some players contribute by being well-rounded while some are more laser-focused on a given role. By splitting out the value numbers, we can shed some light on just how each player does what they do.

All Players Non-FOGO Offense Defensive Players FOGOs
Last Updated: May 28, 2019 14:22 ET
All Offense Defense FOGOs
Player Team Team Games Season EGA FOGO EGA 1-Week Change
TD Ierlan Yale 19 120.06 109.30
Gerard Arceri Penn State 18 81.45 74.42
Kyle Gallagher Penn 16 75.96 69.94
Matthew Pedicine Hobart 16 70.38 67.22
Alex Woodall Towson 16 66.12 61.15
Conor Gaffney Lehigh 17 64.91 62.89
Bailey Savio Loyola 17 63.99 61.57
Jimmeh Koita Drexel 15 59.43 58.88
Petey LaSalla Virginia 20 58.85 50.06 9
Charles Leonard Notre Dame 16 58.02 51.71
Davis Sampere High Point 16 57.42 54.17
Peyton Smith Marist 17 56.85 56.99
James Reilly Georgetown 18 53.80 47.98 1
Liam McDonough UMass-Lowell 14 52.58 45.42 1
Tom Meyers UMass 15 52.41 53.34
Sean Christman Boston U 17 52.06 49.71 1
Dan OConnell Holy Cross 14 51.62 47.60 1
Alex Jarzembowski Detroit 15 51.44 45.71 1
Brett Boos Denver 15 50.84 48.86 1
Ashton Wood Mercer 13 50.57 45.08 1
Justin Inacio Ohio State 12 49.91 47.29 1
Trent Harper Air Force 15 49.74 45.40 1
Zach Cole Saint Joseph’s 14 47.65 43.19
Brian Smyth Duke 18 46.09 40.46 1
Brian Herber Hofstra 14 44.45 43.99
Sam Stephan Mount St Marys 16 43.90 37.33
Danny Tesler Cleveland State 15 40.31 37.87
Daniel Balawejder Canisius 16 39.91 36.93
Trey Arnold Robert Morris 17 39.01 35.32
Nick Warren Wagner 14 38.66 32.02
Jarett Witzal Bucknell 15 38.44 40.33 1
Zachary Tucci North Carolina 15 37.83 35.10
Jake Giaquinto Sacred Heart 15 36.78 30.22
Jason Zou Siena 13 36.29 34.80
Frankie Labetti Fairfield 14 34.43 29.97
Austin Henningsen Maryland 17 33.66 34.12
Kyle Prouty Johns Hopkins 16 33.02 30.95
Malcolm Feeney Colgate 13 32.78 33.11
Jakob Phaup Syracuse 14 31.81 31.88
Jason Simaan Brown 16 30.30 27.22
Austin Jones Albany 14 29.91 31.60
Colin Keating Providence 16 29.29 26.07
Dan Fisher Villanova 15 29.21 28.75
Nick Barry Navy 13 28.99 30.39
Demitri George Quinnipiac 16 28.58 28.35
Tyler Stevenson NJIT 14 28.58 27.89
Robert Carroll Manhattan 14 28.56 27.00
Alex Semler Vermont 15 27.71 27.30
Matt Nareweski Johns Hopkins 16 27.68 26.48
Brandon Galloway UMBC 16 25.73 21.92