#113 Saint Louis (12-12)

avg: 1131.28  •  sd: 60.4  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
133 Truman State Loss 6-7 856.98 Feb 17th Dust Bowl 2024
42 Texas-Dallas Loss 1-11 1079.92 Feb 17th Dust Bowl 2024
124 Arkansas Loss 4-8 506.96 Feb 17th Dust Bowl 2024
177 Missouri State Win 9-3 1282.97 Feb 17th Dust Bowl 2024
53 Texas Loss 0-15 961.29 Feb 17th Dust Bowl 2024
96 Iowa State Loss 7-9 974.17 Feb 18th Dust Bowl 2024
177 Missouri State Win 6-4 1048.58 Feb 18th Dust Bowl 2024
195 Washington University-B** Win 10-4 1111.38 Ignored Mar 2nd Midwest Throwdown 2024
133 Truman State Win 9-7 1261.32 Mar 2nd Midwest Throwdown 2024
34 Washington University Loss 5-8 1330.55 Mar 2nd Midwest Throwdown 2024
237 Northwestern-B** Win 11-1 621.81 Ignored Mar 2nd Midwest Throwdown 2024
83 Kansas Win 7-4 1839.16 Mar 3rd Midwest Throwdown 2024
102 Iowa Win 6-4 1577.88 Mar 3rd Midwest Throwdown 2024
34 Washington University Loss 4-9 1184.16 Mar 3rd Midwest Throwdown 2024
35 St Olaf Loss 4-7 1282.33 Mar 3rd Midwest Throwdown 2024
34 Washington University** Loss 2-14 1184.16 Ignored Apr 13th Ozarks D I Womens Conferences 2024
83 Kansas Loss 4-10 743 Apr 13th Ozarks D I Womens Conferences 2024
124 Arkansas Win 11-10 1196.77 Apr 14th Ozarks D I Womens Conferences 2024
195 Washington University-B Win 9-7 790.72 Apr 14th Ozarks D I Womens Conferences 2024
177 Missouri State Win 14-3 1282.97 Apr 14th Ozarks D I Womens Conferences 2024
18 Colorado State** Loss 4-15 1471.59 Ignored Apr 27th South Central D I College Womens Regionals 2024
149 Texas A&M Win 8-5 1331.12 Apr 27th South Central D I College Womens Regionals 2024
153 Texas State Win 9-6 1279.8 Apr 27th South Central D I College Womens Regionals 2024
77 Missouri Loss 6-9 950.39 Apr 27th South Central 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)