(7) #171 Illinois (8-13)

408.98 (213)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
213 St. Olaf-B** Win 9-1 0 177 0% Ignored (Why) Mar 4th Midwest Throwdown 2023
209 Purdue-B Win 6-1 6.07 183 3.71% Counts (Why) Mar 4th Midwest Throwdown 2023
70 Northwestern** Loss 1-11 0 145 0% Ignored (Why) Mar 4th Midwest Throwdown 2023
189 Wisconsin-Milwaukee Win 6-4 7.85 184 4.03% Counts (Why) Mar 4th Midwest Throwdown 2023
122 Purdue Loss 5-11 -9.69 146 5.09% Counts (Why) Mar 5th Midwest Throwdown 2023
106 Marquette Loss 4-8 -1.02 179 4.41% Counts Mar 5th Midwest Throwdown 2023
109 Texas State Loss 9-12 12.79 162 6.23% Counts Mar 18th Womens Centex1
104 Iowa Loss 4-13 -2.8 160 6.23% Counts (Why) Mar 18th Womens Centex1
179 LSU Win 10-7 20.56 160 5.89% Counts Mar 18th Womens Centex1
112 Rice Loss 6-13 -6.74 162 6.23% Counts (Why) Mar 18th Womens Centex1
190 Colorado-B Win 10-5 23.1 161 5.54% Counts (Why) Mar 19th Womens Centex1
207 Northwestern-B Win 10-8 -8.76 166 6.06% Counts Mar 19th Womens Centex1
179 LSU Win 9-7 13.22 160 5.72% Counts Mar 19th Womens Centex1
109 Texas State Loss 2-7 -2.94 162 4.52% Counts (Why) Mar 19th Womens Centex1
73 St. Olaf Loss 4-7 18.08 95 5.32% Counts Apr 1st Illinois Invite1
165 Truman State Loss 3-5 -16.41 150 4.54% Counts Apr 1st Illinois Invite1
106 Marquette Loss 3-5 5.9 179 4.54% Counts Apr 1st Illinois Invite1
123 Denver Loss 1-7 -10.05 129 5.07% Counts (Why) Apr 1st Illinois Invite1
165 Truman State Loss 3-7 -28.15 150 5.07% Counts (Why) Apr 2nd Illinois Invite1
214 Notre Dame-B Win 9-4 -0.84 21 5.78% Counts (Why) Apr 2nd Illinois Invite1
174 Wheaton (Illinois) Loss 6-8 -20.09 27 6% Counts Apr 2nd Illinois Invite1
**Blowout Eligible. Learn more about how this works here.

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.