#99 Central Florida (7-15)

avg: 1211.68  •  sd: 70.64  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
276 Mississippi Win 15-8 1042.3 Jan 18th TTown Throwdown 2020 Open
65 Tennessee-Chattanooga Loss 9-12 1050.53 Jan 18th TTown Throwdown 2020 Open
164 Illinois State Loss 10-11 848.7 Jan 18th TTown Throwdown 2020 Open
60 LSU Loss 10-12 1186.32 Jan 18th TTown Throwdown 2020 Open
49 Alabama-Huntsville Loss 9-15 985.21 Jan 19th TTown Throwdown 2020 Open
101 Vanderbilt Loss 7-13 652.15 Jan 19th TTown Throwdown 2020 Open
9 Pittsburgh** Loss 5-13 1442.76 Ignored Feb 14th Florida Warm Up 2020 Weekend 1
10 Carleton College-CUT Loss 7-13 1476.1 Feb 14th Florida Warm Up 2020 Weekend 1
13 Brown Loss 6-13 1328.06 Feb 14th Florida Warm Up 2020 Weekend 1
35 Northeastern Loss 8-11 1265.74 Feb 15th Florida Warm Up 2020 Weekend 1
11 Minnesota Loss 6-13 1392.77 Feb 15th Florida Warm Up 2020 Weekend 1
31 Texas-Dallas Loss 3-13 1097.27 Feb 15th Florida Warm Up 2020 Weekend 1
69 Texas A&M Win 13-12 1509.58 Feb 15th Florida Warm Up 2020 Weekend 1
141 Harvard Win 15-10 1493.21 Feb 16th Florida Warm Up 2020 Weekend 1
60 LSU Win 15-14 1549.45 Feb 16th Florida Warm Up 2020 Weekend 1
131 Johns Hopkins Win 13-5 1694.57 Feb 29th Easterns Qualifier 2020
45 Notre Dame Loss 5-13 973.57 Feb 29th Easterns Qualifier 2020
58 Virginia Win 11-7 1919.05 Feb 29th Easterns Qualifier 2020
107 Ohio Loss 5-13 588.06 Feb 29th Easterns Qualifier 2020
73 Carnegie Mellon Loss 10-13 1038.32 Mar 1st Easterns Qualifier 2020
67 Wisconsin-Milwaukee Loss 6-15 791.64 Mar 1st Easterns Qualifier 2020
107 Ohio Win 15-14 1313.06 Mar 1st Easterns Qualifier 2020
**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)