#61 James Madison (15-11)

avg: 1472.52  •  sd: 58.72  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
116 Appalachian State Loss 7-10 884.79 Feb 3rd Queen City Tune Up 2018 College Open
41 Northeastern Loss 8-9 1478.36 Feb 3rd Queen City Tune Up 2018 College Open
36 Michigan Loss 5-11 1038.31 Feb 3rd Queen City Tune Up 2018 College Open
50 Notre Dame Win 9-8 1664.28 Feb 3rd Queen City Tune Up 2018 College Open
42 Connecticut Loss 8-9 1470.56 Feb 3rd Queen City Tune Up 2018 College Open
39 Northwestern Win 8-4 2193.51 Feb 4th Queen City Tune Up 2018 College Open
48 Dartmouth Loss 8-13 1069.27 Feb 17th Easterns Qualifier 2018
149 Davidson Win 9-6 1559.43 Feb 17th Easterns Qualifier 2018
151 George Mason Win 13-7 1674.37 Feb 17th Easterns Qualifier 2018
66 Kennesaw State Loss 12-13 1333.01 Feb 17th Easterns Qualifier 2018
98 Clemson Win 13-8 1834.2 Feb 17th Easterns Qualifier 2018
40 Iowa Loss 8-15 1060 Feb 18th Easterns Qualifier 2018
102 Richmond Win 15-11 1708.05 Feb 18th Easterns Qualifier 2018
75 Tennessee-Chattanooga Win 15-14 1540.67 Feb 18th Easterns Qualifier 2018
149 Davidson Win 13-7 1698.39 Mar 17th Oak Creek Invite 2018
109 Williams Win 13-10 1624.35 Mar 17th Oak Creek Invite 2018
60 Cornell Win 13-12 1598.23 Mar 17th Oak Creek Invite 2018
91 Penn State Win 14-11 1687.24 Mar 18th Oak Creek Invite 2018
42 Connecticut Win 14-13 1720.56 Mar 18th Oak Creek Invite 2018
34 William & Mary Loss 14-15 1523.2 Mar 18th Oak Creek Invite 2018
48 Dartmouth Loss 9-13 1146.86 Mar 24th Atlantic Coast Open 2018
28 Carnegie Mellon Loss 6-13 1118.65 Mar 24th Atlantic Coast Open 2018
84 Virginia Win 13-12 1527.14 Mar 24th Atlantic Coast Open 2018
34 William & Mary Loss 6-15 1048.2 Mar 25th Atlantic Coast Open 2018
113 Lehigh Win 11-8 1649.69 Mar 25th Atlantic Coast Open 2018
86 Duke Win 12-11 1523.98 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)