#22 Northwestern (12-9)

avg: 1789.74  •  sd: 90.47  •  top 16/20: 13.6%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
21 Vermont Loss 4-11 1325.53 Jan 25th Santa Barbara Invite 2020
36 Brigham Young Win 13-7 2124.68 Jan 25th Santa Barbara Invite 2020
27 California-Davis Win 13-8 2241.63 Jan 25th Santa Barbara Invite 2020
10 California-Santa Barbara Loss 7-11 1575 Jan 25th Santa Barbara Invite 2020
58 California-Santa Cruz Win 13-7 1924.18 Jan 25th Santa Barbara Invite 2020
4 California-San Diego Loss 6-13 1637.65 Jan 26th Santa Barbara Invite 2020
8 Northeastern Loss 8-13 1610.48 Jan 26th Santa Barbara Invite 2020
20 Wisconsin Loss 6-11 1387.77 Jan 26th Santa Barbara Invite 2020
21 Vermont Loss 10-11 1800.53 Feb 22nd Commonwealth Cup 2020 Weekend 2
2 North Carolina** Loss 6-15 1886.51 Ignored Feb 22nd Commonwealth Cup 2020 Weekend 2
8 Northeastern Loss 8-11 1741.03 Feb 22nd Commonwealth Cup 2020 Weekend 2
25 Georgia Win 12-10 2013.38 Feb 23rd Commonwealth Cup 2020 Weekend 2
33 North Carolina State Loss 8-10 1375.64 Feb 23rd Commonwealth Cup 2020 Weekend 2
56 North Carolina-Wilmington Win 15-1 1984.72 Feb 23rd Commonwealth Cup 2020 Weekend 2
227 Knox** Win 13-0 555.76 Ignored Mar 7th Midwest Throwdown 2020
67 Carleton College Win 9-4 1899.76 Mar 7th Midwest Throwdown 2020
185 Washington University-B** Win 13-0 1037.83 Ignored Mar 7th Midwest Throwdown 2020
162 Wisconsin-Eau Claire** Win 13-1 1177.2 Ignored Mar 7th Midwest Throwdown 2020
73 Truman State Win 10-4 1876.3 Mar 8th Midwest Throwdown 2020
57 Kansas Win 9-6 1789.01 Mar 8th Midwest Throwdown 2020
51 Texas-Dallas Win 8-4 1994.78 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)