#89 Mississippi State (20-8)

avg: 1434.06  •  sd: 61.08  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
209 Alabama-Birmingham Win 13-4 1500.08 Jan 21st Tupelo Tuneup
284 Memphis** Win 13-3 1157.6 Ignored Jan 21st Tupelo Tuneup
269 Harding** Win 13-1 1249.53 Ignored Jan 21st Tupelo Tuneup
266 Southern Mississippi** Win 13-2 1253.44 Ignored Jan 21st Tupelo Tuneup
234 Xavier** Win 13-4 1373.54 Ignored Jan 22nd Tupelo Tuneup
87 Tennessee-Chattanooga Loss 4-13 836.6 Jan 22nd Tupelo Tuneup
251 Alabama-B** Win 13-4 1332.69 Ignored Jan 28th T Town Throwdown1
259 Jacksonville State** Win 13-5 1296.22 Ignored Jan 28th T Town Throwdown1
233 Florida-B** Win 13-5 1379.91 Ignored Jan 28th T Town Throwdown1
88 Central Florida Win 7-2 2034.22 Jan 29th T Town Throwdown1
141 LSU Win 13-5 1783.87 Jan 29th T Town Throwdown1
61 Emory Loss 9-11 1327.77 Jan 29th T Town Throwdown1
88 Central Florida Loss 9-10 1309.22 Feb 25th Mardi Gras XXXV
344 Mississippi** Win 13-2 718.21 Ignored Feb 25th Mardi Gras XXXV
218 Tulane-B Win 13-6 1467.73 Feb 25th Mardi Gras XXXV
79 Texas A&M Loss 6-11 926.99 Feb 25th Mardi Gras XXXV
141 LSU Win 8-7 1308.87 Feb 26th Mardi Gras XXXV
39 Florida Loss 5-11 1141.42 Feb 26th Mardi Gras XXXV
79 Texas A&M Loss 7-8 1348.68 Feb 26th Mardi Gras XXXV
87 Tennessee-Chattanooga Win 9-6 1855.16 Feb 26th Mardi Gras XXXV
43 Alabama-Huntsville Loss 9-15 1187.65 Mar 11th 2023 College Huckfest
266 Southern Mississippi** Win 15-1 1253.44 Ignored Mar 11th 2023 College Huckfest
87 Tennessee-Chattanooga Loss 10-15 982.99 Mar 12th 2023 College Huckfest
251 Alabama-B Win 13-8 1228.85 Mar 25th Magic City Invite 2023
209 Alabama-Birmingham Win 13-3 1500.08 Mar 25th Magic City Invite 2023
141 LSU Win 13-4 1783.87 Mar 25th Magic City Invite 2023
85 Alabama Win 11-7 1913.89 Mar 26th Magic City Invite 2023
141 LSU Win 13-6 1783.87 Mar 26th Magic City Invite 2023
**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)