(3) #117 Mississippi State (15-8)

1075.61 (9)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
211 Alabama-Birmingham Win 13-4 7.48 31 5.34% Counts (Why) Jan 21st Tupelo Tuneup
267 Memphis** Win 13-3 0 13 0% Ignored (Why) Jan 21st Tupelo Tuneup
255 Harding** Win 13-1 0 6 0% Ignored (Why) Jan 21st Tupelo Tuneup
259 Southern Mississippi** Win 13-2 0 33 0% Ignored (Why) Jan 21st Tupelo Tuneup
232 Xavier** Win 13-4 0 6 0% Ignored (Why) Jan 22nd Tupelo Tuneup
106 Tennessee-Chattanooga Loss 4-13 -30.87 5 5.34% Counts (Why) Jan 22nd Tupelo Tuneup
254 Alabama-B** Win 13-4 0 44 0% Ignored (Why) Jan 28th T Town Throwdown1
225 Jacksonville State Win 13-5 3.07 30 5.66% Counts (Why) Jan 28th T Town Throwdown1
221 Florida-B Win 13-5 3.96 229 5.66% Counts (Why) Jan 28th T Town Throwdown1
102 Central Florida Win 7-2 29.07 14 4.11% Counts (Why) Jan 29th T Town Throwdown1
141 LSU Win 13-5 30.24 28 5.66% Counts (Why) Jan 29th T Town Throwdown1
42 Emory Loss 9-11 7.79 20 5.66% Counts Jan 29th T Town Throwdown1
102 Central Florida Loss 9-10 -3.54 14 7.13% Counts Feb 25th Mardi Gras XXXV
303 Mississippi** Win 13-2 0 1 0% Ignored (Why) Feb 25th Mardi Gras XXXV
215 Tulane-B Win 13-6 8.42 1 7.13% Counts (Why) Feb 25th Mardi Gras XXXV
96 Texas A&M Loss 6-11 -30.54 75 6.75% Counts Feb 25th Mardi Gras XXXV
141 LSU Win 8-7 1.97 28 6.34% Counts Feb 26th Mardi Gras XXXV
40 Florida Loss 5-11 -14.92 30 6.54% Counts (Why) Feb 26th Mardi Gras XXXV
96 Texas A&M Loss 7-8 -0.04 75 6.34% Counts Feb 26th Mardi Gras XXXV
106 Tennessee-Chattanooga Win 9-6 31.91 5 6.34% Counts Feb 26th Mardi Gras XXXV
39 Alabama-Huntsville Loss 9-15 -10.86 4 8% Counts Mar 11th 2023 College Huckfest
259 Southern Mississippi** Win 15-1 0 33 0% Ignored (Why) Mar 11th 2023 College Huckfest
106 Tennessee-Chattanooga Loss 10-15 -34.85 5 8% Counts Mar 12th 2023 College Huckfest
**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.