(8) #27 Northeastern (9-9)

2092.61 (184)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
2 Carleton College** Loss 1-13 0 3 0% Ignored (Why) Feb 15th Queen City Tune Up 2025
67 Florida Win 10-4 5.53 75 4.78% Counts (Why) Feb 15th Queen City Tune Up 2025
64 South Carolina Win 13-6 8.23 27 5.47% Counts (Why) Feb 15th Queen City Tune Up 2025
30 Wisconsin Win 9-4 25.16 99 4.53% Counts (Why) Feb 16th Queen City Tune Up 2025
20 Virginia Win 8-4 33.71 82 4.35% Counts (Why) Feb 16th Queen City Tune Up 2025
16 California-Davis Win 11-9 30.34 10 6.15% Counts Mar 1st Stanford Invite 2025 Womens
12 California-Santa Cruz Loss 9-10 16.99 25 6.15% Counts Mar 1st Stanford Invite 2025 Womens
68 Santa Clara Win 13-7 3.44 62 6.15% Counts (Why) Mar 1st Stanford Invite 2025 Womens
17 California-Santa Barbara Loss 9-12 -8.78 20 6.15% Counts Mar 2nd Stanford Invite 2025 Womens
12 California-Santa Cruz Loss 6-10 -6.67 25 5.64% Counts Mar 2nd Stanford Invite 2025 Womens
8 Washington Loss 5-10 -8.02 6 5.46% Counts Mar 2nd Stanford Invite 2025 Womens
24 Minnesota Loss 9-11 -17.42 210 7.74% Counts Mar 29th East Coast Invite 2025
31 Pittsburgh Loss 8-10 -27.77 65 7.54% Counts Mar 29th East Coast Invite 2025
20 Virginia Loss 10-11 4.31 82 7.74% Counts Mar 29th East Coast Invite 2025
23 Pennsylvania Loss 8-12 -24.16 99 7.74% Counts Mar 29th East Coast Invite 2025
102 Lehigh** Win 8-1 0 75 0% Ignored (Why) Mar 30th East Coast Invite 2025
112 West Chester Win 12-6 -24.42 93 7.54% Counts (Why) Mar 30th East Coast Invite 2025
77 Penn State Win 9-6 -13.06 100 6.88% Counts Mar 30th East Coast Invite 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.