#172 Florida State (12-11)

avg: 600.38  •  sd: 59.45  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
237 Florida-B Win 7-1 684.15 Jan 25th Florida Winter Classic 2025
170 Miami (Florida) Win 7-6 734.35 Jan 25th Florida Winter Classic 2025
33 Georgia Tech** Loss 1-12 1050.8 Ignored Jan 25th Florida Winter Classic 2025
59 Central Florida** Loss 1-11 796.52 Ignored Jan 26th Florida Winter Classic 2025
65 Florida Loss 5-9 789.53 Jan 26th Florida Winter Classic 2025
230 Georgia Tech-B Win 7-3 764.45 Jan 26th Florida Winter Classic 2025
72 Union (Tennessee) Loss 4-8 706.29 Feb 22nd Mardi Gras XXXVII
136 Trinity Loss 6-10 310.64 Feb 22nd Mardi Gras XXXVII
125 Jacksonville State Win 10-9 1011.38 Feb 22nd Mardi Gras XXXVII
215 Minnesota-Duluth Win 15-2 868.78 Mar 15th Tally Classic XIX
51 Middlebury** Loss 4-14 881.55 Ignored Mar 15th Tally Classic XIX
189 LSU Win 8-7 616.15 Mar 15th Tally Classic XIX
221 Florida Tech Loss 5-6 92.36 Mar 15th Tally Classic XIX
59 Central Florida** Loss 2-15 796.52 Ignored Apr 12th Florida D I Womens Conferences 2025
237 Florida-B Win 15-2 684.15 Apr 12th Florida D I Womens Conferences 2025
248 South Florida Win 11-0 615.12 Apr 12th Florida D I Womens Conferences 2025
221 Florida Tech Win 14-3 817.36 Apr 13th Florida D I Womens Conferences 2025
170 Miami (Florida) Win 9-6 1027.92 Apr 13th Florida D I Womens Conferences 2025
203 Tennessee-Chattanooga Loss 9-10 270.46 Apr 26th Southeast D I College Womens Regionals 2025
210 Vanderbilt Loss 10-11 156.56 Apr 26th Southeast D I College Womens Regionals 2025
29 Georgia** Loss 5-15 1124.96 Ignored Apr 26th Southeast D I College Womens Regionals 2025
234 Auburn Win 12-8 566.52 Apr 27th Southeast D I College Womens Regionals 2025
237 Florida-B Win 9-6 502.72 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)