(2) #97 Alabama (17-8)

1347.93 (9)

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# Opponent Result Effect % of Ranking Status Date Event
66 Kennesaw State Loss 7-12 -13.03 3.08% Jan 20th T Town Throwdown XIV Open
264 LSU-B Win 11-9 -11.55 3.08% Jan 20th T Town Throwdown XIV Open
153 Xavier Loss 12-13 -11.35 3.08% Jan 20th T Town Throwdown XIV Open
335 Southern Mississippi Win 11-8 -17.59 3.08% Jan 20th T Town Throwdown XIV Open
154 Mississippi Win 15-8 10.52 3.08% Jan 21st T Town Throwdown XIV Open
231 Alabama-Birmingham Win 15-9 -0.36 3.08% Jan 21st T Town Throwdown XIV Open
155 Vanderbilt Win 6-4 2.98 2.23% Jan 21st T Town Throwdown XIV Open
94 Kentucky Loss 8-10 -10.33 4% Feb 24th Music City Tune Up 2018
229 Toledo Win 13-4 3.62 4.11% Feb 24th Music City Tune Up 2018
228 Wooster Win 13-5 3.78 4.11% Feb 24th Music City Tune Up 2018
189 Georgia State Win 11-6 7.22 3.89% Feb 24th Music City Tune Up 2018
124 Indiana Win 15-8 21.42 4.61% Mar 10th Tally Classic XIII
8 Massachusetts Loss 9-12 13.07 4.61% Mar 10th Tally Classic XIII
140 Florida Tech Win 12-11 -2.68 4.61% Mar 10th Tally Classic XIII
37 Central Florida Loss 8-10 1.14 4.49% Mar 10th Tally Classic XIII
28 Carnegie Mellon Loss 6-13 -11.08 4.61% Mar 10th Tally Classic XIII
81 Florida State Loss 11-14 -12.21 4.61% Mar 11th Tally Classic XIII
50 Notre Dame Loss 8-11 -8.42 4.61% Mar 11th Tally Classic XIII
244 Berry Win 13-6 1.95 5.18% Mar 24th Magic City Invite 2018
154 Mississippi Win 13-9 10.11 5.18% Mar 24th Magic City Invite 2018
155 Vanderbilt Win 13-10 5.08 5.18% Mar 24th Magic City Invite 2018
317 Troy University** Win 13-3 0 0% Ignored Mar 24th Magic City Invite 2018
120 Mississippi State Win 15-12 11.67 5.18% Mar 25th Magic City Invite 2018
236 Middle Tennessee State Win 13-2 2.86 5.18% Mar 25th Magic City Invite 2018
231 Alabama-Birmingham Win 15-6 3.99 5.18% Mar 25th Magic City Invite 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.