#78 Georgetown (15-14)

avg: 1415.07  •  sd: 38.09  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
48 Dartmouth Loss 9-12 1220.06 Feb 3rd Mid Atlantic Warmup 2018
107 Rutgers Loss 9-10 1189.37 Feb 3rd Mid Atlantic Warmup 2018
126 Elon Win 12-10 1450.24 Feb 3rd Mid Atlantic Warmup 2018
84 Virginia Win 13-10 1730.28 Feb 3rd Mid Atlantic Warmup 2018
44 Illinois Loss 8-14 1052.99 Feb 4th Mid Atlantic Warmup 2018
115 Villanova Win 13-11 1505.51 Feb 4th Mid Atlantic Warmup 2018
34 William & Mary Loss 7-8 1523.2 Feb 4th Mid Atlantic Warmup 2018
40 Iowa Loss 2-13 1024.81 Feb 17th Easterns Qualifier 2018
12 North Carolina State Loss 8-12 1477.71 Feb 17th Easterns Qualifier 2018
133 Case Western Reserve Win 10-9 1300.77 Feb 17th Easterns Qualifier 2018
73 Michigan State Win 13-12 1544.54 Feb 17th Easterns Qualifier 2018
23 Georgia Tech Loss 7-13 1186.43 Feb 17th Easterns Qualifier 2018
51 Ohio State Loss 9-11 1288.49 Feb 18th Easterns Qualifier 2018
102 Richmond Win 14-12 1547.84 Feb 18th Easterns Qualifier 2018
75 Tennessee-Chattanooga Loss 11-13 1186.83 Feb 18th Easterns Qualifier 2018
167 North Carolina-B Win 13-7 1623.78 Mar 17th Oak Creek Invite 2018
115 Villanova Win 12-8 1717.83 Mar 17th Oak Creek Invite 2018
204 SUNY-Geneseo Win 13-9 1344.08 Mar 17th Oak Creek Invite 2018
42 Connecticut Loss 9-13 1176.99 Mar 17th Oak Creek Invite 2018
60 Cornell Loss 11-13 1244.39 Mar 18th Oak Creek Invite 2018
33 Maryland Loss 13-15 1470.1 Mar 18th Oak Creek Invite 2018
91 Penn State Win 11-9 1623.11 Mar 18th Oak Creek Invite 2018
243 Rowan** Win 13-5 1384.01 Ignored Mar 24th Atlantic Coast Open 2018
28 Carnegie Mellon Loss 5-10 1144.75 Mar 24th Atlantic Coast Open 2018
174 East Carolina Win 11-7 1499.31 Mar 24th Atlantic Coast Open 2018
84 Virginia Win 12-11 1527.14 Mar 24th Atlantic Coast Open 2018
56 Temple Win 13-11 1738.44 Mar 24th Atlantic Coast Open 2018
48 Dartmouth Win 11-10 1690.43 Mar 25th Atlantic Coast Open 2018
34 William & Mary Loss 10-13 1320.06 Mar 25th Atlantic Coast Open 2018
**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)