#139 Florida State (9-14)

avg: 1083.69  •  sd: 61.27  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
38 Utah State Loss 4-13 1032.62 Jan 31st Florida Warm Up 2025
19 Georgia** Loss 5-13 1292.49 Ignored Jan 31st Florida Warm Up 2025
15 Washington University** Loss 2-13 1351.63 Ignored Jan 31st Florida Warm Up 2025
4 Carleton College** Loss 1-13 1603.31 Ignored Feb 1st Florida Warm Up 2025
56 Cornell Loss 9-13 1105.38 Feb 1st Florida Warm Up 2025
47 McGill Loss 1-13 991.44 Feb 1st Florida Warm Up 2025
61 Alabama-Huntsville Loss 8-12 1023.19 Feb 2nd Florida Warm Up 2025
134 South Florida Loss 9-12 767.04 Feb 2nd Florida Warm Up 2025
209 Arkansas Win 12-6 1341.46 Feb 22nd Mardi Gras XXXVII
79 Florida Loss 7-10 958.21 Feb 22nd Mardi Gras XXXVII
160 LSU Win 10-9 1117.08 Feb 22nd Mardi Gras XXXVII
103 Texas A&M Win 12-11 1365.66 Feb 22nd Mardi Gras XXXVII
69 Auburn Loss 9-14 954.52 Mar 15th Tally Classic XIX
222 Harvard Win 15-11 1091.07 Mar 15th Tally Classic XIX
198 Georgia State Loss 9-10 710.3 Mar 15th Tally Classic XIX
160 LSU Win 11-10 1117.08 Mar 15th Tally Classic XIX
388 American-B** Win 14-5 179.27 Ignored Mar 22nd Atlantic Coast Open 2025
96 Appalachian State Loss 12-14 1053.47 Mar 22nd Atlantic Coast Open 2025
163 Messiah Win 15-11 1362.76 Mar 22nd Atlantic Coast Open 2025
115 Vermont-B Loss 8-9 1069.71 Mar 22nd Atlantic Coast Open 2025
184 East Carolina Loss 13-14 764.71 Mar 23rd Atlantic Coast Open 2025
255 Wake Forest Win 15-4 1186.48 Mar 23rd Atlantic Coast Open 2025
163 Messiah Win 13-8 1477.76 Mar 23rd Atlantic Coast Open 2025
**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)