#87 Tennessee-Chattanooga (12-5)

avg: 1436.6  •  sd: 93.36  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
251 Alabama-B** Win 13-2 1332.69 Ignored Jan 21st Tupelo Tuneup
347 Mississippi College** Win 13-1 686.61 Ignored Jan 21st Tupelo Tuneup
304 Mississippi State-B** Win 13-1 1032.02 Ignored Jan 21st Tupelo Tuneup
234 Xavier** Win 13-3 1373.54 Ignored Jan 21st Tupelo Tuneup
209 Alabama-Birmingham Win 13-3 1500.08 Jan 22nd Tupelo Tuneup
89 Mississippi State Win 13-4 2034.06 Jan 22nd Tupelo Tuneup
331 Texas Tech** Win 13-0 859.24 Ignored Feb 25th Mardi Gras XXXV
259 Jacksonville State** Win 13-4 1296.22 Ignored Feb 25th Mardi Gras XXXV
336 Trinity** Win 13-4 814.33 Ignored Feb 25th Mardi Gras XXXV
39 Florida Loss 7-13 1183.89 Feb 25th Mardi Gras XXXV
89 Mississippi State Loss 6-9 1015.49 Feb 26th Mardi Gras XXXV
102 Kennesaw State Loss 9-10 1233.44 Feb 26th Mardi Gras XXXV
186 Texas State Win 12-6 1577.16 Feb 26th Mardi Gras XXXV
65 Indiana Loss 8-13 1069.68 Feb 26th Mardi Gras XXXV
43 Alabama-Huntsville Loss 13-15 1488.95 Mar 11th 2023 College Huckfest
266 Southern Mississippi** Win 15-4 1253.44 Ignored Mar 11th 2023 College Huckfest
89 Mississippi State Win 15-10 1887.66 Mar 12th 2023 College Huckfest
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)