(7) #231 Alabama-Birmingham (8-16)

821.08 (4)

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# Opponent Result Effect % of Ranking Status Date Event
94 Kentucky Loss 10-12 10.76 3.43% Jan 20th T Town Throwdown XIV Open
431 Alabama-B** Win 13-5 0 0% Ignored Jan 20th T Town Throwdown XIV Open
155 Vanderbilt Loss 7-13 -9.43 3.43% Jan 20th T Town Throwdown XIV Open
23 Georgia Tech** Loss 2-13 0 0% Ignored Jan 20th T Town Throwdown XIV Open
241 Harding Win 15-9 17.09 3.43% Jan 21st T Town Throwdown XIV Open
97 Alabama Loss 9-15 0.4 3.43% Jan 21st T Town Throwdown XIV Open
259 Northern Illinois Win 7-6 1.64 2.83% Jan 21st T Town Throwdown XIV Open
352 Belmont Win 12-8 -1.02 4.57% Feb 24th Music City Tune Up 2018
95 Purdue Loss 4-10 -2.84 3.99% Feb 24th Music City Tune Up 2018
120 Mississippi State Loss 6-11 -4.81 4.33% Feb 24th Music City Tune Up 2018
300 Southern Indiana Loss 10-11 -17.28 4.57% Feb 24th Music City Tune Up 2018
23 Georgia Tech Loss 6-13 17.47 5.13% Mar 10th Tally Classic XIII
224 Georgia Southern Loss 7-15 -30.29 5.13% Mar 10th Tally Classic XIII
50 Notre Dame** Loss 4-13 0 0% Ignored Mar 10th Tally Classic XIII
46 South Carolina Loss 7-13 10.86 5.13% Mar 10th Tally Classic XIII
81 Florida State Loss 4-13 -0.67 5.13% Mar 10th Tally Classic XIII
272 Miami Loss 11-15 -27.08 5.13% Mar 11th Tally Classic XIII
120 Mississippi State Loss 6-13 -9.77 5.76% Mar 24th Magic City Invite 2018
375 Memphis Win 13-4 3.71 5.76% Mar 24th Magic City Invite 2018
242 Samford Win 13-5 34.54 5.76% Mar 24th Magic City Invite 2018
335 Southern Mississippi Win 13-9 1.58 5.76% Mar 24th Magic City Invite 2018
154 Mississippi Loss 9-15 -13.57 5.76% Mar 25th Magic City Invite 2018
97 Alabama Loss 6-15 -4.47 5.76% Mar 25th Magic City Invite 2018
189 Georgia State Win 14-12 23.21 5.76% Mar 25th Magic City Invite 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.