(3) #37 Northwestern (9-12)

2028.18 (469)

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# Opponent Result Effect % of Ranking Status Date Event
5 Oregon Loss 7-15 -0.81 4.37% Feb 17th Presidents Day Invitational Tournament 2018
2 California-San Diego** Loss 4-14 0 0% Ignored Feb 17th Presidents Day Invitational Tournament 2018
33 UCLA Loss 8-11 -15.13 4.37% Feb 17th Presidents Day Invitational Tournament 2018
105 Chico State Win 14-3 2.34 4.37% Feb 18th Presidents Day Invitational Tournament 2018
16 Western Washington Loss 8-9 8.25 4.13% Feb 18th Presidents Day Invitational Tournament 2018
22 Minnesota Loss 7-12 -14.62 4.37% Feb 18th Presidents Day Invitational Tournament 2018
20 Washington Loss 7-9 -2.81 4.01% Feb 19th Presidents Day Invitational Tournament 2018
44 Colorado State Win 9-7 10.97 4.5% Mar 3rd Midwest Throwdown 2018
55 Iowa State Loss 6-12 -38.16 4.77% Mar 3rd Midwest Throwdown 2018
96 St Olaf Win 15-6 5.05 4.91% Mar 3rd Midwest Throwdown 2018
42 Wisconsin Loss 8-11 -20.12 4.91% Mar 4th Midwest Throwdown 2018
108 Wisconsin-Eau Claire Win 15-0 0.98 4.91% Mar 4th Midwest Throwdown 2018
89 Iowa Win 11-6 4.33 4.64% Mar 4th Midwest Throwdown 2018
57 Kansas Win 14-3 21.07 4.91% Mar 4th Midwest Throwdown 2018
28 Washington University Loss 10-11 -2.43 5.83% Mar 24th Womens Centex 2018
13 Ohio State Loss 7-13 -11.2 5.83% Mar 24th Womens Centex 2018
55 Iowa State Win 13-10 9.07 5.83% Mar 24th Womens Centex 2018
33 UCLA Win 11-10 9.88 5.83% Mar 24th Womens Centex 2018
28 Washington University Win 14-9 34.67 5.83% Mar 24th Womens Centex 2018
9 Colorado Loss 7-15 -7.96 5.83% Mar 25th Womens Centex 2018
11 Texas Loss 10-13 7.15 5.83% Mar 25th Womens Centex 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.