#78 Central Florida (11-7)

avg: 1012.53  •  sd: 98.71  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
10 Northeastern** Loss 2-7 1410.32 Ignored Jan 28th Florida Winter Classic 2023
200 Miami (Florida)** Win 13-0 521.25 Ignored Jan 28th Florida Winter Classic 2023
214 Florida-B** Win 13-0 218.13 Ignored Jan 28th Florida Winter Classic 2023
45 Florida Win 9-7 1640.77 Jan 28th Florida Winter Classic 2023
46 Florida State Loss 3-7 759.02 Jan 29th Florida Winter Classic 2023
208 Florida Tech** Win 13-0 414.44 Ignored Jan 29th Florida Winter Classic 2023
45 Florida Loss 3-9 761.44 Jan 29th Florida Winter Classic 2023
152 Sam Houston Win 8-5 954.15 Feb 25th Mardi Gras XXXV
200 Miami (Florida)** Win 13-0 521.25 Ignored Feb 25th Mardi Gras XXXV
81 Trinity Win 8-4 1563.43 Feb 25th Mardi Gras XXXV
140 Alabama Win 5-3 1010.31 Feb 26th Mardi Gras XXXV
106 Texas State Win 7-5 1167.82 Feb 26th Mardi Gras XXXV
56 Georgia Tech Loss 6-10 730.05 Mar 18th Womens Centex1
68 Northwestern Win 9-7 1394.4 Mar 18th Womens Centex1
22 Texas-Dallas** Loss 2-13 1023.85 Ignored Mar 18th Womens Centex1
47 Washington University Loss 5-11 755.16 Mar 19th Womens Centex1
112 Rice Win 10-7 1191.08 Mar 19th Womens Centex1
81 Trinity Loss 6-12 419.31 Mar 19th Womens Centex1
**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)