#142 Carleton College-CHOP (12-12)

avg: 1183.5  •  sd: 39.14  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
20 North Carolina State** Loss 5-15 1345.4 Ignored Jan 28th Carolina Kickoff
84 Richmond Loss 7-15 849.92 Jan 28th Carolina Kickoff
27 South Carolina** Loss 6-15 1248.18 Ignored Jan 28th Carolina Kickoff
24 North Carolina-Charlotte Loss 10-15 1440.88 Jan 28th Carolina Kickoff
52 Appalachian State Loss 9-15 1118.57 Jan 29th Carolina Kickoff
84 Richmond Loss 8-10 1187.25 Jan 29th Carolina Kickoff
183 Minnesota-B Win 9-8 1135.96 Feb 11th Ugly Dome
64 St. Olaf Loss 7-9 1288.66 Feb 11th Ugly Dome
294 Winona State Win 13-7 1063.36 Feb 11th Ugly Dome
210 Wisconsin-Eau Claire Win 11-8 1261.91 Feb 11th Ugly Dome
321 Minnesota-C** Win 13-5 904.01 Ignored Feb 11th Ugly Dome
313 Illinois-B** Win 13-2 954.3 Ignored Mar 4th Midwest Throwdown 2023
68 Wisconsin-Milwaukee Loss 7-13 992.4 Mar 4th Midwest Throwdown 2023
22 Washington University** Loss 4-13 1305.32 Ignored Mar 4th Midwest Throwdown 2023
318 Carleton College-Karls-C** Win 13-5 925.43 Ignored Mar 5th Midwest Throwdown 2023
207 Illinois State Loss 7-8 785.86 Mar 5th Midwest Throwdown 2023
279 Wisconsin-Platteville Win 11-5 1185.54 Mar 5th Midwest Throwdown 2023
52 Appalachian State Loss 9-12 1288.68 Mar 18th College Southerns XXI
268 Georgia Southern Win 13-7 1208.94 Mar 18th College Southerns XXI
233 Florida-B Win 13-1 1379.91 Mar 18th College Southerns XXI
- Charleston** Win 13-3 1014.86 Ignored Mar 18th College Southerns XXI
52 Appalachian State Loss 9-15 1118.57 Mar 19th College Southerns XXI
276 Georgia Tech-B Win 12-7 1112.94 Mar 19th College Southerns XXI
189 Luther Win 15-8 1559.85 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)