#142 Carleton College-CHOP (12-12)

avg: 993.41  •  sd: 36.44  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
15 North Carolina State** Loss 5-15 1205.28 Ignored Jan 28th Carolina Kickoff
75 Richmond Loss 7-15 712 Jan 28th Carolina Kickoff
17 South Carolina** Loss 6-15 1173.87 Ignored Jan 28th Carolina Kickoff
24 North Carolina-Charlotte Loss 10-15 1246.82 Jan 28th Carolina Kickoff
53 Appalachian State Loss 9-15 917.66 Jan 29th Carolina Kickoff
75 Richmond Loss 8-10 1049.34 Jan 29th Carolina Kickoff
193 Minnesota-B Win 9-8 889.94 Feb 11th Ugly Dome
88 St. Olaf Loss 7-9 975.14 Feb 11th Ugly Dome
287 Winona State Win 13-7 849.13 Feb 11th Ugly Dome
214 Wisconsin-Eau Claire Win 11-8 1030.94 Feb 11th Ugly Dome
309 Minnesota-C** Win 13-5 726.6 Ignored Feb 11th Ugly Dome
263 Illinois-B Win 13-2 1056.04 Mar 4th Midwest Throwdown 2023
77 Wisconsin-Milwaukee Loss 7-13 747.88 Mar 4th Midwest Throwdown 2023
35 Washington University** Loss 4-13 1009.29 Ignored Mar 4th Midwest Throwdown 2023
279 Carleton College-Karls** Win 13-5 943.1 Ignored Mar 5th Midwest Throwdown 2023
198 Illinois State Loss 7-8 620.95 Mar 5th Midwest Throwdown 2023
264 Wisconsin-Platteville Win 11-5 1049.78 Mar 5th Midwest Throwdown 2023
53 Appalachian State Loss 9-12 1087.77 Mar 18th College Southerns XXI
253 Georgia Southern Win 13-7 1049.54 Mar 18th College Southerns XXI
220 Florida-B Win 13-1 1232.88 Mar 18th College Southerns XXI
- Charleston** Win 13-3 913.91 Ignored Mar 18th College Southerns XXI
53 Appalachian State Loss 9-15 917.66 Mar 19th College Southerns XXI
272 Georgia Tech-B Win 12-7 922.03 Mar 19th College Southerns XXI
188 Luther Win 15-8 1361.02 Mar 19th College Southerns XXI
**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)