#189 LSU (12-13)

avg: 490.29  •  sd: 60.11  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
163 Alabama Loss 3-11 40.88 Feb 22nd Mardi Gras XXXVII
247 Alabama-Birmingham Win 8-3 616.96 Feb 22nd Mardi Gras XXXVII
233 Auburn Win 10-8 387.43 Feb 22nd Mardi Gras XXXVII
257 Mississippi State Win 6-4 105.22 Feb 22nd Mardi Gras XXXVII
65 Florida** Loss 3-12 719.34 Ignored Mar 15th Tally Classic XIX
172 Florida State Loss 7-8 474.77 Mar 15th Tally Classic XIX
219 Florida Tech Win 8-5 670.39 Mar 15th Tally Classic XIX
214 Minnesota-Duluth Win 9-7 547.51 Mar 15th Tally Classic XIX
44 Texas-Dallas** Loss 2-13 953.39 Ignored Mar 22nd Womens Centex 2025
27 Texas** Loss 1-13 1165.24 Ignored Mar 22nd Womens Centex 2025
88 Rice Loss 5-10 553.51 Mar 22nd Womens Centex 2025
205 Texas A&M Win 9-8 473.05 Mar 23rd Womens Centex 2025
255 Texas-B Win 9-6 283.11 Mar 23rd Womens Centex 2025
124 Jacksonville State Loss 6-9 467.18 Apr 12th Gulf Coast D I Womens Conferences 2025
177 Tulane Loss 8-11 206.57 Apr 12th Gulf Coast D I Womens Conferences 2025
209 Vanderbilt Win 8-3 880.82 Apr 12th Gulf Coast D I Womens Conferences 2025
233 Auburn Win 10-7 514.43 Apr 13th Gulf Coast D I Womens Conferences 2025
124 Jacksonville State Loss 6-15 285.74 Apr 13th Gulf Coast D I Womens Conferences 2025
177 Tulane Win 11-8 937.78 Apr 13th Gulf Coast D I Womens Conferences 2025
99 Emory Loss 3-15 475.33 Apr 26th Southeast D I College Womens Regionals 2025
33 Georgia Tech** Loss 2-15 1051.61 Ignored Apr 26th Southeast D I College Womens Regionals 2025
212 Georgia-B Win 15-8 837.42 Apr 26th Southeast D I College Womens Regionals 2025
124 Jacksonville State Loss 4-12 285.74 Apr 26th Southeast D I College Womens Regionals 2025
156 Georgia Southern Loss 9-13 255.04 Apr 27th Southeast D I College Womens Regionals 2025
209 Vanderbilt Win 11-7 747.71 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)