#112 Central Florida (4-9)

avg: 1054.26  •  sd: 84.43  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
3 Ohio State** Loss 1-12 1773 Ignored Jan 19th Florida Winter Classic 2019
20 North Carolina-Wilmington** Loss 3-10 1360.18 Ignored Jan 19th Florida Winter Classic 2019
38 Florida Loss 5-10 1037.22 Jan 19th Florida Winter Classic 2019
43 Georgia Tech Loss 2-9 955.59 Jan 19th Florida Winter Classic 2019
128 North Georgia Win 9-5 1534.4 Jan 20th Florida Winter Classic 2019
8 Dartmouth** Loss 2-15 1558.85 Ignored Jan 20th Florida Winter Classic 2019
51 Florida State Loss 1-13 908.35 Jan 20th Florida Winter Classic 2019
43 Georgia Tech Loss 2-13 955.59 Jan 20th Florida Winter Classic 2019
201 Indiana Win 14-5 1138.64 Mar 2nd Mardi Gras XXXII
214 Mississippi** Win 13-5 1045.64 Ignored Mar 2nd Mardi Gras XXXII
102 LSU Loss 11-12 994.43 Mar 2nd Mardi Gras XXXII
191 Texas Christian Win 11-5 1178.39 Mar 3rd Mardi Gras XXXII
98 Mississippi State Loss 7-9 848.82 Mar 3rd Mardi Gras XXXII
**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)