#225 Florida-B (1-15)

avg: 362.25  •  sd: 114.86  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
128 North Georgia** Loss 0-11 405.34 Ignored Jan 19th Florida Winter Classic 2019
49 Emory** Loss 1-11 918.42 Ignored Jan 19th Florida Winter Classic 2019
220 Florida Tech Loss 2-11 -207.93 Jan 19th Florida Winter Classic 2019
115 South Florida** Loss 0-11 450.61 Ignored Jan 19th Florida Winter Classic 2019
128 North Georgia** Loss 2-9 405.34 Ignored Jan 20th Florida Winter Classic 2019
49 Emory** Loss 1-15 918.42 Ignored Jan 20th Florida Winter Classic 2019
139 Tennessee-Chattanooga Loss 2-8 331.07 Feb 2nd Royal Crown Classic 2019
143 Alabama Loss 1-10 297.51 Feb 2nd Royal Crown Classic 2019
261 Emory-B Loss 6-7 -67.5 Feb 2nd Royal Crown Classic 2019
115 South Florida** Loss 1-11 450.61 Ignored Feb 2nd Royal Crown Classic 2019
25 Clemson** Loss 2-11 1272.28 Ignored Feb 3rd Royal Crown Classic 2019
20 North Carolina-Wilmington** Loss 0-13 1360.18 Ignored Mar 23rd College Southerns XVIII
128 North Georgia** Loss 0-13 405.34 Ignored Mar 23rd College Southerns XVIII
64 Carleton College-Eclipse** Loss 2-13 805.19 Ignored Mar 23rd College Southerns XVIII
149 Luther Loss 11-13 640.43 Mar 24th College Southerns XVIII
254 Georgia Tech-B Win 11-3 715.46 Mar 24th College Southerns XVIII
**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)