(5) #55 Iowa State (8-13)

1846.46 (417)

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# Opponent Result Effect % of Ranking Status Date Event
79 Chicago Win 9-8 -3.01 4.23% Feb 17th Presidents Day Invitational Tournament 2018
105 Chico State Win 13-7 8.91 4.47% Feb 17th Presidents Day Invitational Tournament 2018
36 Colorado College Loss 4-13 -19.34 4.47% Feb 17th Presidents Day Invitational Tournament 2018
4 Stanford Loss 9-13 20.14 4.47% Feb 17th Presidents Day Invitational Tournament 2018
17 California-Santa Barbara Loss 7-14 -5.1 4.47% Feb 18th Presidents Day Invitational Tournament 2018
79 Chicago Win 10-7 8.68 4.23% Feb 18th Presidents Day Invitational Tournament 2018
5 Oregon** Loss 3-15 0 0% Ignored Feb 18th Presidents Day Invitational Tournament 2018
16 Western Washington Loss 4-13 -4.78 4.47% Feb 19th Presidents Day Invitational Tournament 2018
43 Southern California Loss 6-8 -6.25 3.84% Feb 19th Presidents Day Invitational Tournament 2018
37 Northwestern Win 12-6 39.07 4.88% Mar 3rd Midwest Throwdown 2018
44 Colorado State Loss 7-9 -6.96 4.6% Mar 3rd Midwest Throwdown 2018
96 St Olaf Win 13-6 14.77 5.02% Mar 3rd Midwest Throwdown 2018
42 Wisconsin Loss 10-13 -9.03 5.02% Mar 4th Midwest Throwdown 2018
112 Illinois Win 14-7 8.85 5.02% Mar 4th Midwest Throwdown 2018
142 North Park Win 12-7 -4.63 5.02% Mar 4th Midwest Throwdown 2018
37 Northwestern Loss 10-13 -9.29 5.97% Mar 24th Womens Centex 2018
13 Ohio State Loss 9-10 27.5 5.97% Mar 24th Womens Centex 2018
95 Texas State Loss 11-15 -44.06 5.97% Mar 24th Womens Centex 2018
28 Washington University Loss 8-12 -11.02 5.97% Mar 24th Womens Centex 2018
65 Utah Loss 13-14 -12.03 5.97% Mar 25th Womens Centex 2018
123 MIT Win 15-4 7.16 5.97% Mar 25th Womens Centex 2018
**Blowout Eligible

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.