#57 Auburn (15-7)

avg: 1447.19  •  sd: 66.49  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
117 Vanderbilt Win 11-9 1429.18 Feb 10th Golden Triangle Invitational
40 Illinois Loss 7-9 1300.35 Feb 10th Golden Triangle Invitational
192 Harding Win 10-5 1425 Feb 10th Golden Triangle Invitational
105 Mississippi State Win 13-8 1706.94 Feb 10th Golden Triangle Invitational
137 Union (Tennessee) Win 13-8 1586.66 Feb 11th Golden Triangle Invitational
76 Purdue Win 12-11 1482.22 Feb 11th Golden Triangle Invitational
40 Illinois Loss 0-7 979.68 Feb 11th Golden Triangle Invitational
74 Cincinnati Win 13-6 1961.2 Feb 24th Easterns Qualifier 2024
68 James Madison Loss 9-12 1031.53 Feb 24th Easterns Qualifier 2024
28 North Carolina-Wilmington Loss 6-12 1155.19 Feb 24th Easterns Qualifier 2024
169 Rutgers Win 9-7 1230.98 Feb 24th Easterns Qualifier 2024
56 Emory Win 11-10 1572.58 Feb 25th Easterns Qualifier 2024
66 Virginia Win 13-12 1519.17 Feb 25th Easterns Qualifier 2024
29 South Carolina Loss 11-15 1302.75 Feb 25th Easterns Qualifier 2024
16 Penn State Loss 8-13 1425.07 Feb 25th Easterns Qualifier 2024
173 Clemson Win 13-4 1539.13 Mar 16th Tally Classic XVIII
97 Florida State Win 12-7 1768.28 Mar 16th Tally Classic XVIII
105 Mississippi State Win 11-8 1576.39 Mar 16th Tally Classic XVIII
360 North Florida** Win 13-4 559.96 Ignored Mar 16th Tally Classic XVIII
201 Alabama-Birmingham Win 10-6 1323.03 Mar 17th Tally Classic XVIII
106 Notre Dame Win 15-8 1775.12 Mar 17th Tally Classic XVIII
75 Ave Maria Loss 11-14 1046.24 Mar 17th Tally Classic XVIII
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
The uncertainty of the mean is equal to the standard deviation of the set of game ratings, divided by the square root of the number of games. We treated a team’s ranking as a normally distributed random variable, with the USAU ranking as the mean and the uncertainty of the ranking as the standard deviation
What's the algorithm again?
  1. Calculate uncertainy for USAU ranking averge
  2. Model ranking as a normal distribution around USAU averge with standard deviation equal to uncertainty
  3. Simulate seasons by drawing a rank for each team from their distribution. Note the teams in the top 16 (club) or top 20 (college)
  4. Sum the fractions for each region for how often each of it's teams appeared in the top 16 (club) or top 20 (college)
  5. Subtract one from each fraction for "autobids"
  6. Award remainings bids to the regions with the highest remaining fraction, subtracting one from the fraction each time a bid is awarded
Is there a longer explanation of all this?
There is an article on Ulitworld written by Scott Dunham and I that gives a little more context (though it probably was the thing that linked you here)