#276 Mississippi (2-16)

avg: 477.49  •  sd: 73.52  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
49 Alabama-Huntsville** Loss 0-11 900.69 Ignored Jan 18th TTown Throwdown 2020 Open
57 Illinois** Loss 2-11 852.91 Ignored Jan 18th TTown Throwdown 2020 Open
172 South Florida Loss 5-11 342.95 Jan 18th TTown Throwdown 2020 Open
25 Georgia Tech** Loss 3-13 1176.75 Ignored Jan 18th TTown Throwdown 2020 Open
99 Central Florida Loss 8-15 646.87 Jan 18th TTown Throwdown 2020 Open
172 South Florida Loss 7-15 342.95 Jan 19th TTown Throwdown 2020 Open
80 Boston College** Loss 3-10 720.57 Ignored Feb 22nd Music City Tune Up 2020
146 Michigan State Loss 4-13 414.35 Feb 22nd Music City Tune Up 2020
101 Vanderbilt Loss 6-13 609.68 Feb 22nd Music City Tune Up 2020
300 Belmont University Win 14-6 939.97 Feb 23rd Music City Tune Up 2020
281 Butler Loss 8-11 82.25 Feb 23rd Music City Tune Up 2020
289 Olivet Nazarene Win 14-5 1012.1 Feb 23rd Music City Tune Up 2020
153 Florida State Loss 4-13 403.71 Feb 29th Mardi Gras XXXIII
87 Texas State** Loss 2-13 686.68 Ignored Feb 29th Mardi Gras XXXIII
230 Sam Houston State Loss 8-13 240.69 Feb 29th Mardi Gras XXXIII
157 Iowa Loss 7-13 437.5 Feb 29th Mardi Gras XXXIII
175 Alabama-Birmingham Loss 8-13 436.24 Mar 1st Mardi Gras XXXIII
288 St John's Loss 11-12 297.64 Mar 1st Mardi Gras XXXIII
**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)