#59 Georgetown (14-4)

avg: 1519.65  •  sd: 58.07  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
123 Liberty Win 10-5 1552.42 Jan 27th Winta Binta Vinta 2024
21 Ohio State Loss 3-13 1482.16 Jan 27th Winta Binta Vinta 2024
70 James Madison Win 9-6 1838.14 Jan 27th Winta Binta Vinta 2024
181 Virginia-B** Win 10-4 1061.64 Ignored Jan 27th Winta Binta Vinta 2024
61 Penn State Loss 3-7 903.49 Jan 28th Winta Binta Vinta 2024
123 Liberty Win 9-2 1578.52 Jan 28th Winta Binta Vinta 2024
70 James Madison Win 8-7 1544.57 Jan 28th Winta Binta Vinta 2024
162 South Carolina-B** Win 11-2 1240.77 Ignored Feb 17th Commonwealth Cup Weekend 1 2024
128 Cedarville Win 13-6 1546.97 Feb 17th Commonwealth Cup Weekend 1 2024
129 Richmond Win 9-5 1475.8 Feb 17th Commonwealth Cup Weekend 1 2024
53 American Win 6-5 1709.8 Feb 18th Commonwealth Cup Weekend 1 2024
123 Liberty Win 9-5 1507.58 Feb 18th Commonwealth Cup Weekend 1 2024
28 St Olaf Loss 1-6 1321.34 Mar 23rd Needle in a Ho Stack 2024
149 Emory** Win 13-1 1403.75 Ignored Mar 23rd Needle in a Ho Stack 2024
43 Alabama-Huntsville Loss 8-10 1438.03 Mar 24th Needle in a Ho Stack 2024
97 Appalachian State Win 11-2 1820.34 Mar 24th Needle in a Ho Stack 2024
167 Wake Forest** Win 13-1 1174.52 Ignored Mar 24th Needle in a Ho Stack 2024
88 Virginia Tech Win 9-8 1422.26 Mar 24th Needle in a Ho Stack 2024
**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)