#33 Northwestern (16-7)

avg: 1665.39  •  sd: 65.31  •  top 16/20: 0.7%

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# Opponent Result Game Rating Status Date Event
95 Connecticut Win 13-7 1803.03 Jan 25th Santa Barbara Invite 2020
43 Stanford Loss 10-13 1271.39 Jan 25th Santa Barbara Invite 2020
15 California Loss 9-12 1540.8 Jan 25th Santa Barbara Invite 2020
64 Victoria Win 13-10 1737.83 Jan 25th Santa Barbara Invite 2020
32 Dartmouth Loss 9-13 1264.87 Jan 26th Santa Barbara Invite 2020
40 Santa Clara Loss 10-11 1486.92 Jan 26th Santa Barbara Invite 2020
43 Stanford Win 12-8 2040.69 Jan 26th Santa Barbara Invite 2020
35 Northeastern Loss 11-12 1506.35 Feb 14th Florida Warm Up 2020 Weekend 1
63 Cincinnati Win 12-9 1762 Feb 14th Florida Warm Up 2020 Weekend 1
62 Florida Win 13-10 1747 Feb 14th Florida Warm Up 2020 Weekend 1
69 Texas A&M Win 12-10 1622.71 Feb 15th Florida Warm Up 2020 Weekend 1
25 Georgia Tech Loss 7-13 1219.22 Feb 15th Florida Warm Up 2020 Weekend 1
60 LSU Win 12-10 1662.57 Feb 15th Florida Warm Up 2020 Weekend 1
62 Florida Win 14-11 1732.2 Feb 15th Florida Warm Up 2020 Weekend 1
63 Cincinnati Win 15-6 2016.63 Feb 16th Florida Warm Up 2020 Weekend 1
11 Minnesota Loss 12-15 1692.28 Feb 16th Florida Warm Up 2020 Weekend 1
219 Kansas State** Win 13-2 1352.3 Ignored Mar 7th Midwest Throwdown 2020
196 Wisconsin-Eau Claire** Win 11-2 1438.26 Ignored Mar 7th Midwest Throwdown 2020
- University of Missouri-B** Win 13-2 600 Ignored Mar 7th Midwest Throwdown 2020
169 Luther** Win 11-2 1565.12 Ignored Mar 7th Midwest Throwdown 2020
105 Kansas Win 12-6 1777.98 Mar 8th Midwest Throwdown 2020
100 Truman State Win 12-2 1809.73 Mar 8th Midwest Throwdown 2020
84 Missouri S&T Win 9-5 1836.96 Mar 8th Midwest Throwdown 2020
**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)