#16 Vermont (9-6)

avg: 1899.81  •  sd: 96.54  •  top 16/20: 90.2%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
24 Northwestern Win 11-4 2328.69 Jan 25th Santa Barbara Invite 2020
37 Utah Win 13-4 2080.83 Jan 25th Santa Barbara Invite 2020
32 Brigham Young Win 12-5 2149.89 Jan 25th Santa Barbara Invite 2020
8 California-Santa Barbara Loss 8-13 1539.33 Jan 25th Santa Barbara Invite 2020
51 California-Santa Cruz Win 9-8 1472.54 Jan 25th Santa Barbara Invite 2020
6 Northeastern Win 12-7 2580.23 Jan 26th Santa Barbara Invite 2020
3 California-San Diego Loss 3-12 1598.9 Jan 26th Santa Barbara Invite 2020
8 California-Santa Barbara Win 12-6 2614.8 Jan 26th Santa Barbara Invite 2020
24 Northwestern Win 11-10 1853.69 Feb 22nd Commonwealth Cup 2020 Weekend 2
5 Ohio State Loss 8-10 1827.86 Feb 22nd Commonwealth Cup 2020 Weekend 2
9 Pittsburgh Loss 5-12 1428.45 Feb 22nd Commonwealth Cup 2020 Weekend 2
21 Georgia Win 11-10 1894.84 Feb 22nd Commonwealth Cup 2020 Weekend 2
6 Northeastern Loss 11-14 1746.38 Feb 23rd Commonwealth Cup 2020 Weekend 2
36 Pennsylvania Win 10-4 2089.18 Feb 23rd Commonwealth Cup 2020 Weekend 2
11 Virginia Loss 6-10 1510.23 Feb 23rd Commonwealth Cup 2020 Weekend 2
**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)