#209 Vanderbilt (9-17)

avg: 280.82  •  sd: 70.81  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
163 Alabama Win 9-7 920.22 Jan 25th T Town Throwdown XX
155 Berry Loss 5-8 223.82 Jan 25th T Town Throwdown XX
198 Harding Win 10-9 579.21 Jan 25th T Town Throwdown XX
66 Illinois** Loss 1-13 708.53 Ignored Mar 1st Midwest Throwdown 2025
144 Knox Loss 4-7 229.53 Mar 1st Midwest Throwdown 2025
87 Michigan Tech** Loss 1-13 533.92 Ignored Mar 1st Midwest Throwdown 2025
253 Northwestern-B Win 9-3 508.95 Mar 2nd Midwest Throwdown 2025
245 Wisconsin-B Win 8-6 326.93 Mar 2nd Midwest Throwdown 2025
215 Washington University-B Win 9-8 387.07 Mar 2nd Midwest Throwdown 2025
203 Tennessee-Chattanooga Loss 8-9 270.01 Mar 22nd Moxie Madness 2025
71 Union (Tennessee)** Loss 1-13 670.35 Ignored Mar 22nd Moxie Madness 2025
154 Xavier Loss 6-8 376.98 Mar 22nd Moxie Madness 2025
163 Alabama Loss 3-7 40.88 Mar 23rd Moxie Madness 2025
233 Auburn Win 8-7 249.76 Mar 23rd Moxie Madness 2025
32 Ohio** Loss 1-13 1071.76 Ignored Mar 23rd Moxie Madness 2025
233 Auburn Win 8-7 249.76 Apr 12th Gulf Coast D I Womens Conferences 2025
124 Jacksonville State** Loss 3-12 285.74 Ignored Apr 12th Gulf Coast D I Womens Conferences 2025
189 LSU Loss 3-8 -109.71 Apr 12th Gulf Coast D I Womens Conferences 2025
177 Tulane Loss 6-8 271.68 Apr 12th Gulf Coast D I Womens Conferences 2025
233 Auburn Win 10-4 724.76 Apr 13th Gulf Coast D I Womens Conferences 2025
172 Florida State Win 11-10 724.77 Apr 26th Southeast D I College Womens Regionals 2025
29 Georgia** Loss 3-15 1126.12 Ignored Apr 26th Southeast D I College Womens Regionals 2025
81 Tennessee** Loss 4-15 596.93 Ignored Apr 26th Southeast D I College Womens Regionals 2025
203 Tennessee-Chattanooga Loss 5-12 -204.99 Apr 26th Southeast D I College Womens Regionals 2025
189 LSU Loss 7-11 23.4 Apr 27th Southeast D I College Womens Regionals 2025
203 Tennessee-Chattanooga Loss 8-11 29.4 Apr 27th Southeast D I College Womens Regionals 2025
**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)