#80 Cincinnati (14-7)

avg: 1354.51  •  sd: 102.44  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
31 Alabama-Huntsville Loss 2-11 1232.1 Feb 10th College Womens Huckfest
33 Union (Tennessee) Loss 4-9 1201.17 Feb 10th College Womens Huckfest
211 Vanderbilt** Win 11-1 932.2 Ignored Feb 10th College Womens Huckfest
202 Alabama** Win 11-2 1034.07 Ignored Feb 11th College Womens Huckfest
233 Alabama-Birmingham** Win 11-1 686.05 Ignored Feb 11th College Womens Huckfest
129 Illinois Win 10-6 1533.66 Feb 11th College Womens Huckfest
129 Illinois Win 7-5 1365.65 Feb 11th College Womens Huckfest
49 Ohio Win 9-5 2135.77 Mar 2nd Huckleberry Flick
243 Dayton** Win 15-0 405.14 Ignored Mar 2nd Huckleberry Flick
159 Kenyon Win 14-3 1425.76 Mar 2nd Huckleberry Flick
224 Butler** Win 15-0 820.15 Ignored Mar 3rd Huckleberry Flick
134 Franciscan Win 10-9 1106 Mar 3rd Huckleberry Flick
49 Ohio Loss 4-10 1006.71 Mar 3rd Huckleberry Flick
158 Case Western Reserve Win 11-1 1434.5 Apr 20th Ohio D I Womens Conferences 2024
24 Ohio State Win 7-3 2493.87 Apr 20th Ohio D I Womens Conferences 2024
49 Ohio Loss 4-8 1041.9 Apr 20th Ohio D I Womens Conferences 2024
112 Carnegie Mellon Loss 6-9 715.46 Apr 27th Ohio Valley D I College Womens Regionals 2024
22 Pittsburgh Loss 4-9 1334.21 Apr 27th Ohio Valley D I College Womens Regionals 2024
121 Temple Win 8-7 1203.5 Apr 27th Ohio Valley D I College Womens Regionals 2024
24 Ohio State Loss 4-13 1293.87 Apr 27th Ohio Valley D I College Womens Regionals 2024
158 Case Western Reserve Win 15-5 1434.5 Apr 28th Ohio Valley D I College Womens Regionals 2024
**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)