#54 Carleton College-CHOP (13-4)

avg: 1538.06  •  sd: 82.2  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
81 North Carolina-Charlotte Loss 11-13 1093.42 Feb 1st Carolina Kickoff mens 2025
49 North Carolina State Loss 11-13 1335.96 Feb 1st Carolina Kickoff mens 2025
87 Temple Win 13-9 1729.49 Feb 1st Carolina Kickoff mens 2025
96 Appalachian State Win 15-7 1874.42 Feb 2nd Carolina Kickoff mens 2025
71 Case Western Reserve Loss 12-15 1104.57 Feb 2nd Carolina Kickoff mens 2025
87 Temple Win 15-10 1764.52 Feb 2nd Carolina Kickoff mens 2025
178 Minnesota-B Win 12-6 1500.04 Feb 8th Gopher Dome 2025
161 Wisconsin-Eau Claire Win 13-4 1584.17 Feb 8th Gopher Dome 2025
154 Macalester Win 13-3 1642.94 Feb 8th Gopher Dome 2025
331 Minnesota-C** Win 13-1 831.6 Ignored Feb 8th Gopher Dome 2025
82 St Olaf Win 13-7 1878.54 Feb 8th Gopher Dome 2025
213 Air Force** Win 13-2 1346.86 Ignored Mar 1st D III River City Showdown 2025
298 Navy** Win 13-2 988.51 Ignored Mar 1st D III River City Showdown 2025
99 Oberlin Win 13-6 1866.1 Mar 1st D III River City Showdown 2025
89 North Carolina-Asheville Loss 9-11 1052.92 Mar 2nd D III River City Showdown 2025
78 Richmond Win 11-10 1473.03 Mar 2nd D III River City Showdown 2025
125 Puget Sound Win 13-8 1636.77 Mar 2nd D III River City Showdown 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)