#32 Florida (11-13)

avg: 2080.24  •  sd: 93.85  •  top 16/20: 3.3%

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# Opponent Result Game Rating Status Date Event
8 West Chester Loss 4-15 1905.97 Jan 13th Florida Winter Classic 2018
21 Michigan Win 8-6 2538.92 Jan 13th Florida Winter Classic 2018
46 North Carolina-Wilmington Loss 10-11 1853.21 Jan 13th Florida Winter Classic 2018
54 Florida State Loss 6-8 1555.56 Jan 14th Florida Winter Classic 2018
48 Georgia Win 10-3 2555.58 Jan 14th Florida Winter Classic 2018
21 Michigan Loss 6-14 1638.43 Jan 14th Florida Winter Classic 2018
34 Northeastern Loss 7-8 1929.9 Feb 3rd Queen City Tune Up 2018 College Women
31 Penn State Win 8-7 2211.19 Feb 3rd Queen City Tune Up 2018 College Women
8 West Chester Loss 7-12 1985.46 Feb 3rd Queen City Tune Up 2018 College Women
3 North Carolina Loss 5-10 2156.6 Feb 3rd Queen City Tune Up 2018 College Women
25 Notre Dame Loss 9-15 1624.23 Mar 10th Tally Classic XIII
262 Notre Dame-B** Win 11-1 712.35 Ignored Mar 10th Tally Classic XIII
107 LSU Win 15-7 2066.19 Mar 10th Tally Classic XIII
23 Auburn Loss 6-8 1908.36 Mar 10th Tally Classic XIII
245 George Mason University** Win 11-0 1094.17 Ignored Mar 10th Tally Classic XIII
40 Kennesaw State Loss 12-14 1796.63 Mar 11th Tally Classic XIII
46 North Carolina-Wilmington Win 13-12 2103.21 Mar 11th Tally Classic XIII
34 Northeastern Win 9-6 2473.47 Mar 24th Womens Centex 2018
42 Wisconsin Win 14-7 2586.58 Mar 24th Womens Centex 2018
65 Utah Win 11-8 2147.53 Mar 24th Womens Centex 2018
11 Texas Loss 10-13 2143.6 Mar 24th Womens Centex 2018
13 Ohio State Loss 6-15 1804.92 Mar 25th Womens Centex 2018
7 Tufts Loss 3-15 1908.79 Mar 25th Womens Centex 2018
9 Colorado Win 13-12 2624.69 Mar 25th Womens Centex 2018
**Blowout Eligible

FAQ

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
  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
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)