#82 Central Florida (11-7)

avg: 1130.12  •  sd: 98.67  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
10 Northeastern** Loss 2-7 1534.33 Ignored Jan 28th Florida Winter Classic 2023
203 Miami (Florida)** Win 13-0 645.72 Ignored Jan 28th Florida Winter Classic 2023
216 Florida-B** Win 13-0 336.49 Ignored Jan 28th Florida Winter Classic 2023
47 Florida Win 9-7 1747.23 Jan 28th Florida Winter Classic 2023
46 Florida State Loss 3-7 873.72 Jan 29th Florida Winter Classic 2023
210 Florida Tech** Win 13-0 512.58 Ignored Jan 29th Florida Winter Classic 2023
47 Florida Loss 3-9 867.9 Jan 29th Florida Winter Classic 2023
147 Sam Houston Win 8-5 1076.78 Feb 25th Mardi Gras XXXV
203 Miami (Florida)** Win 13-0 645.72 Ignored Feb 25th Mardi Gras XXXV
83 Trinity Win 8-4 1681.99 Feb 25th Mardi Gras XXXV
136 Alabama Win 5-3 1140.93 Feb 26th Mardi Gras XXXV
109 Texas State Win 7-5 1274.93 Feb 26th Mardi Gras XXXV
54 Georgia Tech Loss 6-10 856.7 Mar 18th Womens Centex1
70 Northwestern Win 9-7 1518.11 Mar 18th Womens Centex1
23 Texas-Dallas** Loss 2-13 1139.5 Ignored Mar 18th Womens Centex1
45 Washington University Loss 5-11 879.26 Mar 19th Womens Centex1
112 Rice Win 10-7 1297.28 Mar 19th Womens Centex1
83 Trinity Loss 6-12 537.87 Mar 19th Womens Centex1
**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)