#25 Clemson (23-4)

avg: 1872.28  •  sd: 100.75  •  top 16/20: 23.2%

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# Opponent Result Game Rating Status Date Event
144 Tennessee** Win 13-2 1496.06 Ignored Jan 26th Clutch Classic 2019
139 Tennessee-Chattanooga** Win 13-0 1531.07 Ignored Jan 26th Clutch Classic 2019
204 Georgia Southern** Win 13-2 1106.6 Ignored Jan 26th Clutch Classic 2019
36 Vanderbilt Loss 6-8 1372.79 Jan 26th Clutch Classic 2019
87 Auburn** Win 11-3 1835.26 Ignored Jan 27th Clutch Classic 2019
93 Kennesaw State Win 9-4 1788.04 Jan 27th Clutch Classic 2019
18 South Carolina Loss 7-8 1846.42 Jan 27th Clutch Classic 2019
139 Tennessee-Chattanooga** Win 9-3 1531.07 Ignored Feb 2nd Royal Crown Classic 2019
143 Alabama Win 8-7 1022.51 Feb 2nd Royal Crown Classic 2019
115 South Florida Win 9-5 1579.67 Feb 2nd Royal Crown Classic 2019
261 Emory-B** Win 11-1 657.5 Ignored Feb 2nd Royal Crown Classic 2019
139 Tennessee-Chattanooga** Win 13-2 1531.07 Ignored Feb 3rd Royal Crown Classic 2019
225 Florida-B** Win 11-2 962.25 Ignored Feb 3rd Royal Crown Classic 2019
261 Emory-B** Win 13-1 657.5 Ignored Feb 3rd Royal Crown Classic 2019
41 Harvard Win 12-3 2167.65 Feb 9th Queen City Tune Up 2019 Women
11 Pittsburgh Loss 3-8 1483.27 Feb 9th Queen City Tune Up 2019 Women
38 Florida Loss 7-9 1331.78 Feb 9th Queen City Tune Up 2019 Women
58 Penn State Win 13-0 2051.04 Feb 9th Queen City Tune Up 2019 Women
65 Massachusetts Win 15-6 1996.29 Feb 10th Queen City Tune Up 2019 Women
45 Virginia Win 12-7 2066.21 Feb 10th Queen City Tune Up 2019 Women
41 Harvard Win 11-5 2167.65 Feb 10th Queen City Tune Up 2019 Women
93 Kennesaw State** Win 13-5 1788.04 Ignored Mar 16th Tally Classic XIV
189 Tulane** Win 13-2 1193.98 Ignored Mar 16th Tally Classic XIV
51 Florida State Win 13-4 2108.35 Mar 16th Tally Classic XIV
115 South Florida** Win 13-2 1650.61 Ignored Mar 16th Tally Classic XIV
38 Florida Win 14-3 2211.11 Mar 17th Tally Classic XIV
41 Harvard Win 15-6 2167.65 Mar 17th Tally Classic XIV
**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)