#107 Florida State (12-12)

avg: 1182.08  •  sd: 69.49  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
122 Boston College Win 6-5 1200.76 Feb 24th Mardi Gras XXXVI college
66 Trinity Loss 4-12 856.11 Feb 24th Mardi Gras XXXVI college
155 Tulane Loss 2-5 248.55 Feb 24th Mardi Gras XXXVI college
221 LSU** Win 13-1 856.64 Ignored Feb 24th Mardi Gras XXXVI college
32 Central Florida** Loss 1-11 1217.19 Ignored Feb 25th Mardi Gras XXXVI college
170 Jacksonville State Win 10-5 1335.67 Feb 25th Mardi Gras XXXVI college
234 Florida Tech** Win 9-2 661.95 Ignored Mar 16th Tally Classic XVIII
155 Tulane Win 10-5 1422.45 Mar 16th Tally Classic XVIII
222 Notre Dame-B** Win 12-1 850.6 Ignored Mar 16th Tally Classic XVIII
55 Georgia Tech Loss 3-9 948.96 Mar 17th Tally Classic XVIII
23 Notre Dame Loss 7-15 1331.53 Mar 17th Tally Classic XVIII
55 Georgia Tech Loss 4-11 948.96 Mar 17th Tally Classic XVIII
32 Central Florida** Loss 4-15 1217.19 Ignored Apr 13th Florida D I Womens Conferences 2024
61 Florida Loss 8-12 1052.28 Apr 13th Florida D I Womens Conferences 2024
214 Miami (Florida)** Win 15-1 917.24 Ignored Apr 13th Florida D I Womens Conferences 2024
61 Florida Loss 8-10 1230.77 Apr 14th Florida D I Womens Conferences 2024
241 Florida-B** Win 15-0 435.05 Ignored Apr 14th Florida D I Womens Conferences 2024
214 Miami (Florida)** Win 15-4 917.24 Ignored Apr 14th Florida D I Womens Conferences 2024
202 Alabama** Win 14-4 1034.07 Ignored Apr 27th Southeast D I College Womens Regionals 2024
162 Emory Win 12-4 1416.03 Apr 27th Southeast D I College Womens Regionals 2024
221 LSU** Win 15-0 856.64 Ignored Apr 27th Southeast D I College Womens Regionals 2024
19 Georgia** Loss 4-14 1428.17 Ignored Apr 27th Southeast D I College Womens Regionals 2024
32 Central Florida Loss 8-10 1554.52 Apr 28th Southeast D I College Womens Regionals 2024
63 Tennessee Loss 9-12 1132.75 Apr 28th Southeast 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)