#112 Illinois (7-14)

avg: 1315.98  •  sd: 63.25  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
19 Georgia** Loss 5-13 1350.85 Ignored Feb 3rd Florida Warm Up 2023
23 Wisconsin Loss 6-13 1294.52 Feb 3rd Florida Warm Up 2023
2 Brigham Young** Loss 2-13 1718.3 Ignored Feb 4th Florida Warm Up 2023
77 Temple Loss 8-9 1355.32 Feb 4th Florida Warm Up 2023
147 Connecticut Win 13-6 1762.48 Feb 4th Florida Warm Up 2023
104 Florida State Loss 7-8 1220.01 Feb 4th Florida Warm Up 2023
79 Texas A&M Loss 12-13 1348.68 Feb 5th Florida Warm Up 2023
201 South Florida Win 9-2 1537.69 Feb 5th Florida Warm Up 2023
47 Colorado State Loss 6-13 1047.22 Mar 18th Centex 2023
86 Dartmouth Loss 8-12 995.81 Mar 18th Centex 2023
91 Tulane Loss 8-9 1305.19 Mar 18th Centex 2023
60 Middlebury Loss 8-15 1013.22 Mar 19th Centex 2023
86 Dartmouth Win 12-11 1561.97 Mar 19th Centex 2023
91 Tulane Win 15-10 1883.8 Mar 19th Centex 2023
115 Michigan State Win 9-8 1435.66 Apr 1st Huck Finn1
92 Missouri S&T Win 8-7 1554.82 Apr 1st Huck Finn1
98 Kentucky Loss 6-7 1291.81 Apr 1st Huck Finn1
64 St. Olaf Loss 6-11 1021.3 Apr 1st Huck Finn1
163 Boston University Win 10-3 1701.13 Apr 2nd Huck Finn1
90 Chicago Loss 8-10 1171.11 Apr 2nd Huck Finn1
131 Georgia State Loss 5-9 713.52 Apr 2nd Huck Finn1
**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)