#35 Chicago (11-8)

avg: 1654.33  •  sd: 76.88  •  top 16/20: 0.4%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
17 Tufts Win 13-12 2022.01 Feb 15th Queen City Tune Up 2025
48 Maryland Win 13-7 2123.2 Feb 15th Queen City Tune Up 2025
52 William & Mary Win 13-12 1676.49 Feb 15th Queen City Tune Up 2025
61 Alabama-Huntsville Win 7-5 1792.49 Feb 16th Queen City Tune Up 2025
17 Tufts Loss 0-11 1297.01 Feb 16th Queen City Tune Up 2025
62 Tulane Win 12-8 1903.51 Mar 15th Mens Centex 2025
29 Utah Valley Win 10-9 1877.25 Mar 15th Mens Centex 2025
13 Texas Loss 8-11 1605.24 Mar 15th Mens Centex 2025
40 Wisconsin Win 12-8 2069.16 Mar 15th Mens Centex 2025
76 Colorado College Win 15-10 1823.31 Mar 16th Mens Centex 2025
17 Tufts Loss 8-13 1400.85 Mar 16th Mens Centex 2025
40 Wisconsin Loss 10-15 1174.4 Mar 16th Mens Centex 2025
11 Davenport Loss 8-12 1539.79 Mar 29th Huck Finn 2025
67 Indiana Win 15-6 2043.25 Mar 29th Huck Finn 2025
42 Stanford Win 8-6 1917.86 Mar 29th Huck Finn 2025
15 Washington University Loss 7-15 1351.63 Mar 29th Huck Finn 2025
63 Notre Dame Loss 8-12 1018.31 Mar 30th Huck Finn 2025
42 Stanford Win 10-8 1880.03 Mar 30th Huck Finn 2025
39 Cincinnati Loss 7-11 1163.15 Mar 30th Huck Finn 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)