(66) #168 Carthage (10-6)

903.65 (200)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
282 Rose-Hulman Win 12-8 -0.61 45 5.56% Counts Mar 26th D III Midwestern Invite
327 Indiana-B** Win 15-4 0 16 0% Ignored (Why) Mar 26th D III Midwestern Invite
128 Butler Loss 2-13 -26.1 32 5.56% Counts (Why) Mar 26th D III Midwestern Invite
147 Michigan-B Loss 7-15 -30.68 27 5.56% Counts (Why) Mar 27th D III Midwestern Invite
251 IUPUI Win 1-0 4.11 47 1.28% Counts (Why) Mar 27th D III Midwestern Invite
177 Michigan Tech Loss 9-10 -10.75 126 7.01% Counts Apr 23rd Lake Superior D III College Mens CC 2022
312 Milwaukee School of Engineering Win 11-9 -27.46 117 7.01% Counts Apr 23rd Lake Superior D III College Mens CC 2022
222 Luther Win 10-8 4.78 69 6.82% Counts Apr 23rd Lake Superior D III College Mens CC 2022
87 Wisconsin-Platteville Loss 6-13 -19.87 28 7.01% Counts (Why) Apr 23rd Lake Superior D III College Mens CC 2022
177 Michigan Tech Win 12-8 31.91 126 7.01% Counts Apr 24th Lake Superior D III College Mens CC 2022
222 Luther Win 13-8 25.5 69 7.87% Counts May 7th North Central D III College Mens Regionals 2022
253 St John's Win 13-8 16.8 120 7.87% Counts May 7th North Central D III College Mens Regionals 2022
96 Carleton College-CHOP Win 13-9 61.66 136 7.87% Counts May 7th North Central D III College Mens Regionals 2022
162 Grinnell Loss 12-13 -9.6 42 7.87% Counts May 7th North Central D III College Mens Regionals 2022
177 Michigan Tech Loss 12-13 -12.18 126 7.87% Counts May 8th North Central D III College Mens Regionals 2022
222 Luther Win 13-12 -6.18 69 7.87% Counts May 8th North Central D III College Mens Regionals 2022
**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.