#40 Illinois (14-3)

avg: 1579.68  •  sd: 56.31  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
57 Auburn Win 9-7 1726.53 Feb 10th Golden Triangle Invitational
192 Harding Win 11-5 1451.11 Feb 10th Golden Triangle Invitational
117 Vanderbilt Win 11-7 1646.86 Feb 10th Golden Triangle Invitational
57 Auburn Win 7-0 2047.19 Feb 11th Golden Triangle Invitational
119 Berry Win 12-10 1410.45 Feb 11th Golden Triangle Invitational
87 Tennessee-Chattanooga Win 13-11 1538.82 Feb 11th Golden Triangle Invitational
43 California-San Diego Win 11-10 1687.26 Mar 2nd Stanford Invite 2024
79 Grand Canyon Win 8-6 1641.19 Mar 2nd Stanford Invite 2024
33 Wisconsin Loss 6-11 1098.81 Mar 2nd Stanford Invite 2024
35 California-Santa Cruz Loss 8-9 1512.21 Mar 3rd Stanford Invite 2024
44 Tulane Loss 7-8 1416.68 Mar 3rd Stanford Invite 2024
117 Vanderbilt Win 10-9 1304.97 Mar 3rd Stanford Invite 2024
67 Chicago Win 10-9 1512.02 Mar 16th College Mens Centex Tier 1
41 Florida Win 12-11 1696.02 Mar 16th College Mens Centex Tier 1
121 Iowa State Win 11-9 1404.27 Mar 16th College Mens Centex Tier 1
20 Northeastern Win 13-12 1955.32 Mar 16th College Mens Centex Tier 1
47 Oklahoma Christian Win 12-9 1865.54 Mar 17th College Mens Centex Tier 1
**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)