#25 Georgia (8-10)

avg: 1775.26  •  sd: 59.72  •  top 16/20: 3.4%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
74 South Florida Win 13-4 1863.77 Jan 18th Florida Winter Classic 2020
31 Florida State Win 10-9 1788.97 Jan 18th Florida Winter Classic 2020
11 Dartmouth Loss 4-9 1435.62 Jan 18th Florida Winter Classic 2020
7 Ohio State Loss 7-11 1639.88 Jan 18th Florida Winter Classic 2020
15 Florida Loss 7-11 1511.31 Jan 19th Florida Winter Classic 2020
74 South Florida Win 15-7 1863.77 Jan 19th Florida Winter Classic 2020
11 Dartmouth Loss 10-13 1707.47 Jan 19th Florida Winter Classic 2020
3 Tufts Loss 8-9 2143.54 Feb 8th Queen City Tune Up 2020 Women
84 Notre Dame Win 8-5 1641.99 Feb 8th Queen City Tune Up 2020 Women
38 Duke Loss 8-9 1432.66 Feb 8th Queen City Tune Up 2020 Women
83 Clemson Win 11-4 1802.24 Feb 8th Queen City Tune Up 2020 Women
28 Michigan Win 8-7 1855.66 Feb 9th Queen City Tune Up 2020 Women
21 Vermont Loss 10-11 1800.53 Feb 22nd Commonwealth Cup 2020 Weekend 2
7 Ohio State Loss 6-13 1506.77 Feb 22nd Commonwealth Cup 2020 Weekend 2
13 Pittsburgh Win 13-8 2490.97 Feb 22nd Commonwealth Cup 2020 Weekend 2
12 Virginia Loss 12-13 1910.27 Feb 23rd Commonwealth Cup 2020 Weekend 2
82 Oberlin Win 14-7 1800.9 Feb 23rd Commonwealth Cup 2020 Weekend 2
22 Northwestern Loss 10-12 1551.62 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)