(8) #230 Harvard (7-11)

957.31 (247)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
375 Harvard-B** Win 13-2 0 239 0% Ignored (Why) Mar 9th MIT Invite
364 MIT-B Win 13-1 0.59 209 5.22% Counts (Why) Mar 9th MIT Invite
214 MIT Loss 6-7 -2.78 281 4.32% Counts Mar 9th MIT Invite
294 Northeastern-C Win 8-5 10.13 369 4.32% Counts (Why) Mar 9th MIT Invite
101 Berry Loss 9-15 -0.61 255 5.53% Counts Mar 15th Tally Classic XIX
132 Florida State Loss 11-15 -0.64 244 5.53% Counts Mar 15th Tally Classic XIX
174 Minnesota-Duluth Win 12-10 27.03 439 5.53% Counts Mar 15th Tally Classic XIX
123 Connecticut Loss 5-12 -12.48 181 5.96% Counts (Why) Mar 29th East Coast Invite 2025
161 Delaware Loss 7-11 -12.47 292 6.05% Counts Mar 29th East Coast Invite 2025
167 Pennsylvania Loss 7-10 -8.57 298 5.87% Counts Mar 29th East Coast Invite 2025
219 Princeton Win 8-7 10.37 155 5.52% Counts Mar 29th East Coast Invite 2025
154 Johns Hopkins Loss 7-14 -18.8 250 6.21% Counts Mar 30th East Coast Invite 2025
219 Princeton Loss 8-11 -20.73 155 6.21% Counts Mar 30th East Coast Invite 2025
248 NYU Win 15-4 35.14 238 6.21% Counts (Why) Mar 30th East Coast Invite 2025
85 Boston College Loss 7-14 -1.8 244 6.97% Counts Apr 12th Metro Boston D I Mens Conferences 2025
318 Massachusetts-Lowell Win 10-7 3.15 227 6.59% Counts Apr 12th Metro Boston D I Mens Conferences 2025
105 Boston University Loss 8-14 -3.27 282 6.97% Counts Apr 13th Metro Boston D I Mens Conferences 2025
214 MIT Loss 11-12 -4.62 281 6.97% Counts Apr 13th Metro Boston D I Mens Conferences 2025
**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.