(4) #20 Northeastern (11-9)

1830.32 (65)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
74 Cincinnati Win 13-6 5.13 6 3.77% Counts (Why) Feb 2nd Florida Warm Up 2024
2 Georgia Loss 10-13 4.48 80 3.77% Counts Feb 2nd Florida Warm Up 2024
42 Michigan Win 13-9 6.06 170 3.77% Counts Feb 2nd Florida Warm Up 2024
9 Brown Loss 14-15 2.73 49 3.77% Counts Feb 3rd Florida Warm Up 2024
82 Central Florida Win 13-2 4.19 52 3.77% Counts (Why) Feb 3rd Florida Warm Up 2024
101 Cornell Win 13-6 -0.23 51 3.77% Counts (Why) Feb 3rd Florida Warm Up 2024
10 Carleton College Loss 14-15 2.16 87 3.77% Counts Feb 4th Florida Warm Up 2024
17 Brigham Young Loss 7-10 -18.3 39 5.04% Counts Mar 16th College Mens Centex Tier 1
67 Chicago Win 13-7 6.43 40 5.33% Counts (Why) Mar 16th College Mens Centex Tier 1
41 Florida Loss 10-11 -21.65 4 5.33% Counts Mar 16th College Mens Centex Tier 1
40 Illinois Loss 12-13 -21.16 18 5.33% Counts Mar 16th College Mens Centex Tier 1
128 Colorado College Win 13-7 -7.71 232 5.33% Counts (Why) Mar 17th College Mens Centex Tier 1
53 Colorado State Win 13-8 7.68 118 5.33% Counts Mar 17th College Mens Centex Tier 1
10 Carleton College Loss 11-13 -3.11 87 5.99% Counts Mar 30th Easterns 2024
4 Massachusetts Loss 9-13 -0.89 47 5.99% Counts Mar 30th Easterns 2024
13 North Carolina State Win 13-12 15.36 42 5.99% Counts Mar 30th Easterns 2024
29 South Carolina Loss 9-11 -25.19 52 5.99% Counts Mar 30th Easterns 2024
36 North Carolina-Charlotte Win 13-10 7.39 20 5.99% Counts Mar 31st Easterns 2024
34 Ohio State Win 15-11 12.27 140 5.99% Counts Mar 31st Easterns 2024
33 Wisconsin Win 15-8 24.19 14 5.99% Counts (Why) Mar 31st Easterns 2024
**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.