(9) #207 Florida-B (16-6)

920.75 (21)

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# Opponent Result Effect % of Ranking Status Date Event
292 Central Florida-B Win 13-5 13.98 4.65% Feb 16th Warm Up A Florida Affair 2018
309 Embry-Riddle (Florida) Win 13-2 11.55 4.65% Feb 16th Warm Up A Florida Affair 2018
230 Florida State-B Win 11-7 17.76 4.53% Feb 16th Warm Up A Florida Affair 2018
410 Florida Tech-B Win 13-6 -19.28 4.65% Feb 16th Warm Up A Florida Affair 2018
359 Northwestern-B Win 13-4 1.17 4.65% Feb 17th Warm Up A Florida Affair 2018
367 Florida Atlantic Win 13-6 -0.25 4.65% Feb 17th Warm Up A Florida Affair 2018
180 Pittsburgh-B Win 13-10 20.47 4.65% Feb 18th Warm Up A Florida Affair 2018
216 North Florida Win 14-10 18.33 4.65% Feb 18th Warm Up A Florida Affair 2018
248 North Georgia Loss 9-13 -33.1 5.53% Mar 10th Tally Classic XIII
399 Florida Polytechnic University Win 15-8 -17.64 5.53% Mar 10th Tally Classic XIII
410 Florida Tech-B** Win 13-2 0 0% Ignored Mar 10th Tally Classic XIII
376 Tulane-B** Win 13-5 0 0% Ignored Mar 10th Tally Classic XIII
295 Georgia Tech-B Loss 6-11 -48.11 5.24% Mar 10th Tally Classic XIII
370 Notre Dame-B** Win 15-6 0 0% Ignored Mar 11th Tally Classic XIII
340 Stetson Win 15-10 -3.31 5.53% Mar 11th Tally Classic XIII
150 North Carolina-Asheville Win 13-10 33.54 5.86% Mar 17th College Southerns 2018
201 Wisconsin-Eau Claire Loss 12-13 -7.05 5.86% Mar 17th College Southerns 2018
69 Carleton College-GoP Loss 5-13 -4.44 5.86% Mar 17th College Southerns 2018
273 Wake Forest Win 13-6 23.73 5.86% Mar 17th College Southerns 2018
248 North Georgia Win 11-8 13.65 5.86% Mar 18th College Southerns 2018
75 Tennessee-Chattanooga Loss 5-13 -6.55 5.86% Mar 18th College Southerns 2018
201 Wisconsin-Eau Claire Loss 9-11 -14.78 5.86% Mar 18th College Southerns 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.