(15) #251 East Carolina (9-9)

619.26 (79)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
178 North Carolina-B Loss 6-13 -19.25 131 6.16% Counts (Why) Feb 8th BatCH Bash 2020
262 Campbell Loss 3-13 -43.43 114 6.16% Counts (Why) Feb 8th BatCH Bash 2020
290 Virginia-B Win 12-5 24.63 108 5.91% Counts (Why) Feb 8th BatCH Bash 2020
255 South Carolina-B Loss 7-10 -24.69 106 5.82% Counts Feb 8th BatCH Bash 2020
304 North Carolina State-B Win 9-8 -11.41 65 5.82% Counts Feb 9th BatCH Bash 2020
255 South Carolina-B Win 9-6 23.65 106 5.47% Counts Feb 9th BatCH Bash 2020
117 Appalachian State Loss 3-11 -4.79 64 5.96% Counts (Why) Feb 15th Chucktown Throwdown XVII
301 North Florida Win 10-6 12.4 59 5.96% Counts (Why) Feb 15th Chucktown Throwdown XVII
262 Campbell Win 8-7 3.85 114 5.77% Counts Feb 15th Chucktown Throwdown XVII
241 Wake Forest Loss 6-10 -27.23 79 5.96% Counts Feb 15th Chucktown Throwdown XVII
128 Clemson Loss 5-15 -7.18 84 6.49% Counts (Why) Feb 16th Chucktown Throwdown XVII
338 Alabama-B** Win 11-3 0 81 0% Ignored (Why) Feb 29th Cutlass Classic 2020
95 Connecticut Loss 5-11 1.86 47 6.63% Counts (Why) Feb 29th Cutlass Classic 2020
293 Charleston Win 10-7 12.17 85 6.83% Counts Feb 29th Cutlass Classic 2020
241 Wake Forest Win 12-11 14.89 79 7.22% Counts Feb 29th Cutlass Classic 2020
240 Vermont-C Win 9-7 24.9 75 6.63% Counts Feb 29th Cutlass Classic 2020
95 Connecticut** Loss 4-15 0 47 0% Ignored (Why) Mar 1st Cutlass Classic 2020
128 Clemson Loss 10-12 20.12 84 7.22% Counts Mar 1st Cutlass Classic 2020
**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.