(1) #33 Maryland (14-10)

1684.28 (18)

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# Opponent Result Effect % of Ranking Status Date Event
7 Pittsburgh Win 10-9 17.29 3.88% Feb 3rd Queen City Tune Up 2018 College Open
150 North Carolina-Asheville Win 11-7 -3.39 3.78% Feb 3rd Queen City Tune Up 2018 College Open
10 Virginia Tech Loss 10-11 4.61 3.88% Feb 3rd Queen City Tune Up 2018 College Open
39 Northwestern Win 11-7 16.15 3.78% Feb 3rd Queen City Tune Up 2018 College Open
8 Massachusetts Loss 9-11 1.22 3.88% Feb 3rd Queen City Tune Up 2018 College Open
84 Virginia Win 13-9 6.22 4.36% Feb 17th Easterns Qualifier 2018
51 Ohio State Win 12-11 -0.98 4.36% Feb 17th Easterns Qualifier 2018
75 Tennessee-Chattanooga Win 13-8 10.37 4.36% Feb 17th Easterns Qualifier 2018
62 Vermont Loss 10-12 -20.8 4.36% Feb 17th Easterns Qualifier 2018
46 South Carolina Loss 9-10 -10.48 4.36% Feb 17th Easterns Qualifier 2018
124 Indiana Win 15-6 6.47 4.36% Feb 18th Easterns Qualifier 2018
12 North Carolina State Loss 8-15 -15.05 4.36% Feb 18th Easterns Qualifier 2018
23 Georgia Tech Win 16-14 12.21 4.36% Feb 18th Easterns Qualifier 2018
103 Delaware Win 13-10 -1.86 5.49% Mar 17th Oak Creek Invite 2018
54 Mary Washington Win 13-5 25.56 5.49% Mar 17th Oak Creek Invite 2018
179 SUNY-Binghamton** Win 13-5 0 0% Ignored Mar 17th Oak Creek Invite 2018
209 SUNY-Buffalo** Win 13-2 0 0% Ignored Mar 17th Oak Creek Invite 2018
78 Georgetown Win 15-13 -3.2 5.49% Mar 18th Oak Creek Invite 2018
34 William & Mary Loss 10-13 -21.16 5.49% Mar 18th Oak Creek Invite 2018
42 Connecticut Win 15-12 12.3 5.49% Mar 18th Oak Creek Invite 2018
1 North Carolina** Loss 6-15 0 0% Ignored Mar 31st Easterns 2018
36 Michigan Loss 12-13 -11.23 6.16% Mar 31st Easterns 2018
13 Wisconsin Loss 12-15 -4.44 6.16% Mar 31st Easterns 2018
14 Florida Loss 9-15 -20.55 6.16% Mar 31st Easterns 2018
**Blowout Eligible

FAQ

The results on this page ("USAU") are the results of an implementation of the USA Ultimate Top 20 algorithm, which is used to allocate post season bids to both colleg and club ultimate teams. The data was obtained by scraping USAU's score reporting website. Learn more about the algorithm here. TL;DR, here is the rating function. Every game a team plays gets a rating equal to the opponents rating +/- the score value. With all these data points, we iterate team ratings until convergence. There is also a rule for discounting blowout games (see next FAQ)
For reference, here is handy table with frequent game scrores and the resulting game value:
"...if a team is rated more than 600 points higher than its opponent, and wins with a score that is more than twice the losing score plus one, the game is ignored for ratings purposes. However, this is only done if the winning team has at least N other results that are not being ignored, where N=5."

Translation: if a team plays a game where even earning the max point win would hurt them, they can have the game ignored provided they win by enough and have suffficient unignored results.