#87 Georgetown (10-11)

avg: 1554.4  •  sd: 58.46  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
114 Davidson Win 15-8 2002.08 Jan 27th Carolina Kickoff 2024
14 North Carolina State** Loss 4-15 1571.47 Ignored Jan 27th Carolina Kickoff 2024
16 Penn State Loss 9-15 1632.74 Jan 27th Carolina Kickoff 2024
78 Carleton College-CHOP Win 14-9 2078.1 Jan 28th Carolina Kickoff 2024
214 North Carolina-B Win 15-8 1638.6 Jan 28th Carolina Kickoff 2024
83 Indiana Loss 10-11 1456.32 Jan 28th Carolina Kickoff 2024
13 Alabama-Huntsville** Loss 5-15 1597.22 Ignored Feb 10th Queen City Tune Up 2024
90 Tennessee Win 15-11 1925.01 Feb 10th Queen City Tune Up 2024
42 South Carolina Loss 12-15 1546.27 Feb 10th Queen City Tune Up 2024
51 Missouri Loss 8-13 1268.72 Feb 10th Queen City Tune Up 2024
79 Case Western Reserve Loss 6-11 1049 Feb 11th Queen City Tune Up 2024
83 Indiana Win 14-12 1802.27 Feb 11th Queen City Tune Up 2024
175 Delaware Win 15-9 1737.36 Apr 20th Colonial D I Mens Conferences 2024
217 George Washington Win 12-10 1296.63 Apr 20th Colonial D I Mens Conferences 2024
126 Towson Win 12-11 1514.09 Apr 20th Colonial D I Mens Conferences 2024
64 Maryland Loss 10-14 1279.19 Apr 21st Colonial D I Mens Conferences 2024
147 Maryland-Baltimore County Win 15-6 1915.87 Apr 21st Colonial D I Mens Conferences 2024
72 Appalachian State Loss 12-15 1328.16 May 4th Atlantic Coast D I College Mens Regionals 2024
42 South Carolina Loss 14-15 1721.77 May 4th Atlantic Coast D I College Mens Regionals 2024
126 Towson Loss 14-15 1264.09 May 4th Atlantic Coast D I College Mens Regionals 2024
147 Maryland-Baltimore County Win 13-11 1544.71 May 5th Atlantic Coast D I College Mens Regionals 2024
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)