#97 Florida State (10-15)

avg: 1247.77  •  sd: 65.52  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
42 Michigan Loss 10-13 1238.28 Feb 2nd Florida Warm Up 2024
52 Virginia Tech Win 12-11 1600.52 Feb 2nd Florida Warm Up 2024
33 Wisconsin Loss 11-12 1520.5 Feb 2nd Florida Warm Up 2024
27 Georgia Tech Loss 2-13 1140.14 Feb 3rd Florida Warm Up 2024
4 Massachusetts Loss 7-13 1677.43 Feb 3rd Florida Warm Up 2024
185 South Florida Win 15-7 1466.3 Feb 3rd Florida Warm Up 2024
132 Arkansas Loss 8-9 986.85 Feb 24th Mardi Gras XXXVI college
44 Tulane Loss 7-8 1416.68 Feb 24th Mardi Gras XXXVI college
172 Texas-San Antonio Win 10-8 1202.96 Feb 24th Mardi Gras XXXVI college
91 Indiana Loss 11-13 1041.97 Feb 25th Mardi Gras XXXVI college
139 LSU Loss 5-11 484.6 Feb 25th Mardi Gras XXXVI college
200 Spring Hill Win 7-4 1324.4 Feb 25th Mardi Gras XXXVI college
201 Alabama-Birmingham Win 12-7 1347.38 Mar 16th Tally Classic XVIII
57 Auburn Loss 7-12 926.68 Mar 16th Tally Classic XVIII
173 Clemson Win 11-7 1406.02 Mar 16th Tally Classic XVIII
360 North Florida** Win 13-2 559.96 Ignored Mar 16th Tally Classic XVIII
75 Ave Maria Loss 11-12 1234.58 Mar 17th Tally Classic XVIII
105 Mississippi State Loss 8-10 948.12 Mar 17th Tally Classic XVIII
105 Mississippi State Win 15-6 1810.79 Mar 17th Tally Classic XVIII
38 Duke Loss 12-15 1290.26 Mar 30th Atlantic Coast Open 2024
61 William & Mary Loss 6-15 832.01 Mar 30th Atlantic Coast Open 2024
73 Richmond Loss 11-13 1135.42 Mar 30th Atlantic Coast Open 2024
165 RIT Win 15-14 1090.29 Mar 30th Atlantic Coast Open 2024
62 Massachusetts -B Loss 13-15 1217.6 Mar 31st Atlantic Coast Open 2024
87 Tennessee-Chattanooga Win 11-7 1776.87 Mar 31st Atlantic Coast Open 2024
**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)