#59 Central Florida (14-7)

avg: 1397.07  •  sd: 81.83  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
156 Georgia Southern** Win 12-2 1273.6 Ignored Jan 25th Florida Winter Classic 2025
229 Georgia Tech-B** Win 12-1 763.98 Ignored Jan 25th Florida Winter Classic 2025
65 Florida Loss 5-11 719.34 Jan 25th Florida Winter Classic 2025
169 Miami (Florida)** Win 12-0 1209.04 Ignored Jan 26th Florida Winter Classic 2025
33 Georgia Tech Loss 6-10 1155.45 Jan 26th Florida Winter Classic 2025
172 Florida State** Win 11-1 1199.77 Ignored Jan 26th Florida Winter Classic 2025
76 Columbia Loss 7-8 1094.45 Feb 22nd 2025 Commonwealth Cup Weekend 2
53 Maryland Win 9-8 1582.11 Feb 22nd 2025 Commonwealth Cup Weekend 2
32 Ohio Loss 4-11 1071.76 Feb 22nd 2025 Commonwealth Cup Weekend 2
42 Duke Loss 6-10 1069.34 Feb 23rd 2025 Commonwealth Cup Weekend 2
129 Harvard Win 15-1 1433.28 Mar 15th Tally Classic XIX
51 Middlebury Win 9-7 1761.02 Mar 15th Tally Classic XIX
65 Florida Loss 6-7 1194.34 Mar 15th Tally Classic XIX
248 South Florida** Win 15-0 614.63 Ignored Apr 12th Florida D I Womens Conferences 2025
172 Florida State** Win 15-2 1199.77 Ignored Apr 12th Florida D I Womens Conferences 2025
65 Florida Win 13-10 1647.49 Apr 13th Florida D I Womens Conferences 2025
156 Georgia Southern** Win 15-0 1273.6 Ignored Apr 26th Southeast D I College Womens Regionals 2025
236 Florida-B** Win 15-1 683.7 Ignored Apr 26th Southeast D I College Womens Regionals 2025
99 Emory Win 11-5 1675.33 Apr 26th Southeast D I College Womens Regionals 2025
81 Tennessee Win 15-9 1712.41 Apr 27th Southeast D I College Womens Regionals 2025
33 Georgia Tech Loss 11-15 1270.44 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)