#136 South Florida (4-11)

avg: 1237.03  •  sd: 68.94  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
6 Brigham Young Loss 7-13 1577.2 Feb 8th Florida Warm Up 2019
4 Pittsburgh** Loss 3-13 1584.92 Ignored Feb 8th Florida Warm Up 2019
68 Cincinnati Loss 10-13 1187.23 Feb 8th Florida Warm Up 2019
80 Oklahoma Loss 5-13 851.97 Feb 9th Florida Warm Up 2019
29 Texas-Dallas Loss 3-12 1171.91 Feb 9th Florida Warm Up 2019
73 Temple Loss 5-10 906.97 Feb 9th Florida Warm Up 2019
54 Virginia Tech Loss 8-11 1253.84 Feb 9th Florida Warm Up 2019
127 Boston College Loss 6-14 674.72 Feb 10th Florida Warm Up 2019
65 Florida Loss 7-10 1146.08 Feb 10th Florida Warm Up 2019
25 South Carolina Loss 6-13 1186.69 Mar 23rd College Southerns XVIII
257 Charleston Win 13-7 1387.87 Mar 23rd College Southerns XVIII
146 North Carolina-Asheville Win 12-9 1533.53 Mar 23rd College Southerns XVIII
256 Georgia-B Win 13-5 1431.15 Mar 23rd College Southerns XVIII
89 Luther Win 10-9 1521.55 Mar 24th College Southerns XVIII
35 Middlebury Loss 5-15 1126.5 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)