#24 Auburn (18-9)

avg: 1796.78  •  sd: 52.42  •  top 16/20: 5.9%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
36 Alabama Win 9-8 1848.14 Jan 26th T Town Throwdown
48 Kennesaw State Win 13-2 2246.49 Jan 26th T Town Throwdown
106 Illinois State Win 12-5 1927.34 Jan 26th T Town Throwdown
37 Illinois Win 11-4 2320.39 Jan 26th T Town Throwdown
72 Alabama-Huntsville Win 14-11 1797.33 Jan 27th T Town Throwdown
37 Illinois Win 10-9 1845.39 Jan 27th T Town Throwdown
27 LSU Loss 10-11 1652.74 Jan 27th T Town Throwdown
131 Chicago Win 13-4 1866.49 Feb 9th Queen City Tune Up 2019 Men
44 Virginia Win 12-6 2250.72 Feb 9th Queen City Tune Up 2019 Men
26 North Carolina-Wilmington Loss 9-12 1435.61 Feb 9th Queen City Tune Up 2019 Men
64 Ohio Loss 10-12 1301.28 Feb 9th Queen City Tune Up 2019 Men
94 Appalachian State Win 15-5 1972.43 Feb 10th Queen City Tune Up 2019 Men
119 Clemson Win 15-6 1883.55 Feb 10th Queen City Tune Up 2019 Men
44 Virginia Win 15-9 2186.9 Feb 10th Queen City Tune Up 2019 Men
143 Minnesota-Duluth Win 13-3 1799.07 Mar 16th Tally Classic XIV
55 Florida State Win 13-10 1939.82 Mar 16th Tally Classic XIV
88 Tennessee-Chattanooga Win 12-7 1939.7 Mar 16th Tally Classic XIV
43 Harvard Win 15-11 2053.44 Mar 16th Tally Classic XIV
72 Alabama-Huntsville Win 12-10 1722.11 Mar 17th Tally Classic XIV
15 Central Florida Loss 10-15 1536.71 Mar 17th Tally Classic XIV
2 Brown Loss 11-13 2000.32 Mar 30th Easterns 2019 Men
28 Northeastern Loss 13-14 1650.83 Mar 30th Easterns 2019 Men
11 North Carolina State Loss 8-13 1531.41 Mar 30th Easterns 2019 Men
47 Maryland Win 13-11 1885.17 Mar 30th Easterns 2019 Men
54 Virginia Tech Win 13-12 1744.44 Mar 31st Easterns 2019 Men
45 California-Santa Barbara Loss 12-13 1538.25 Mar 31st Easterns 2019 Men
22 Georgia Loss 5-15 1234.49 Mar 31st Easterns 2019 Men
**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)