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 offensive-only EGA, which accumulates the offensive value each player has produced. So if an attackman causes a turnover, that contribution would be captured in the total value but not in the offensive 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 Offensive EGA 1-Week Change
Pat Spencer Loyola 17 89.87 83.78
Chris Gray Boston U 17 86.98 80.20
Grant Ament Penn State 18 79.70 76.18 2
Jake Carraway Georgetown 18 78.20 70.54 1
Daniel Bucaro Georgetown 18 75.45 72.45 1
Matt Moore Virginia 20 74.99 67.04 4
Mac OKeefe Penn State 18 74.27 70.42
Michael Kraus Virginia 20 70.12 64.12 4
Asher Nolting High Point 16 69.90 66.19 1
Jackson Morrill Yale 19 68.33 63.51
Michael Sowers Princeton 14 66.28 61.71 3
Matt Brandau Yale 19 65.66 57.64 20
Brendan Sunday Towson 16 65.46 60.96 3
James Burr Boston U 17 62.50 59.58 1
Max Tuttle Sacred Heart 15 62.34 53.60 1
Joe Saggese Sacred Heart 15 61.83 55.00 1
Tyson Gibson Robert Morris 17 61.38 52.97 1
Jared Bernhardt Maryland 17 60.66 57.07 1
Brendan Nichtern Army 18 59.61 56.10 1
Joey Epstein Johns Hopkins 16 58.82 56.41 1
Eric Holden Hobart 16 58.47 53.70 1
Logan Wisnauskas Maryland 17 56.29 53.14 1
Adam Charalambides Rutgers 15 54.75 49.66 1
Charlie Kitchen Delaware 15 54.57 51.34 1
Ryan Smith Robert Morris 17 53.74 47.28 2
Jeff Teat Cornell 15 53.08 48.86 1
Dox Aitken Virginia 20 52.97 48.77 19
Ryan Tierney Hofstra 14 52.84 52.54 1
Adam Goldner Penn 16 52.44 49.60 1
Ryan Lanchbury Richmond 17 52.40 49.31 1
Ian Laviano Virginia 20 52.30 44.86 19
Simon Mathias Penn 16 52.09 48.09 2
Bryan Costabile Notre Dame 16 51.97 49.40 1
Kevin Lindley Loyola 17 51.69 49.33 1
Dylan Beckwith Fairfield 14 51.62 48.68 2
Ryan Conrad Virginia 20 51.51 36.73 29
Sam Handley Penn 16 51.03 50.21 1
Corson Kealey Robert Morris 17 50.88 44.84 3
Jack Dolan Jacksonville 15 50.52 46.80 1
Joe Robertson Duke 18 49.62 43.38 10
Jack Tigh Yale 19 49.43 46.27 24
Matthew Varian Drexel 15 48.39 43.86 3
John Piatelli Cornell 15 48.26 44.90 2
Ryan Frawley UMBC 16 48.03 44.34 3
Teddy Hatfield Richmond 17 47.80 42.58 4
Marc ORourke Bryant 14 47.70 42.73 4
Connor Kirst Villanova 15 47.36 44.29 3
Dylan Jinks Hartford 15 47.29 46.02 2
Lucas Spence Lehigh 17 47.14 41.46 3
Trevor Patschorke UMBC 16 47.09 44.70 3