#35 Ave Maria (19-1)

avg: 1797.22  •  sd: 83.02  •  top 16/20: 1.4%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
287 Texas State** Win 13-3 1345.81 Ignored Feb 22nd Mardi Gras XXXVII
118 Mississippi State Win 13-5 1957.25 Feb 22nd Mardi Gras XXXVII
99 Tennessee-Chattanooga Win 13-10 1781.76 Feb 22nd Mardi Gras XXXVII
71 Florida Win 12-10 1829.09 Feb 22nd Mardi Gras XXXVII
193 Miami (Florida)** Win 13-4 1673.38 Ignored Mar 1st Florida Warm Up 2025 Weekend 2
335 Florida-B** Win 13-0 1158.56 Ignored Mar 1st Florida Warm Up 2025 Weekend 2
227 Ave Maria-B** Win 13-4 1546.89 Ignored Mar 2nd Florida Warm Up 2025 Weekend 2
398 South Florida-B** Win 13-0 694.17 Ignored Mar 2nd Florida Warm Up 2025 Weekend 2
227 Ave Maria-B** Win 13-1 1546.89 Ignored Mar 2nd Florida Warm Up 2025 Weekend 2
67 Auburn Win 11-7 2088.69 Mar 15th Tally Classic XIX
130 LSU Win 15-3 1923.15 Mar 15th Tally Classic XIX
128 Central Florida Win 15-6 1927.67 Mar 15th Tally Classic XIX
134 Florida State Win 15-12 1611.26 Apr 12th Florida D I Mens Conferences 2025
146 South Florida Win 15-4 1869.39 Apr 12th Florida D I Mens Conferences 2025
71 Florida Win 15-9 2106.45 Apr 13th Florida D I Mens Conferences 2025
68 Alabama-Huntsville Win 13-12 1735.26 Apr 26th Southeast D I College Mens Regionals 2025
99 Tennessee-Chattanooga Win 15-9 1969.1 Apr 26th Southeast D I College Mens Regionals 2025
130 LSU Win 11-10 1448.15 Apr 26th Southeast D I College Mens Regionals 2025
67 Auburn Loss 10-14 1223.1 Apr 27th Southeast D I College Mens Regionals 2025
47 Emory Win 15-13 1949.66 Apr 27th Southeast D I College Mens Regionals 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)