#78 Carleton College-CHOP (19-6)

avg: 1348.94  •  sd: 67.29  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
36 North Carolina-Charlotte Loss 4-15 1018.26 Jan 27th Carolina Kickoff 2024
126 Lehigh Win 15-11 1526.56 Jan 27th Carolina Kickoff 2024
38 Duke Win 15-14 1715.76 Jan 27th Carolina Kickoff 2024
92 Tennessee Win 15-11 1648.27 Jan 28th Carolina Kickoff 2024
72 Georgetown Loss 9-14 891.83 Jan 28th Carolina Kickoff 2024
125 Davidson Win 15-8 1711.38 Jan 28th Carolina Kickoff 2024
140 Minnesota-B Loss 11-12 953.04 Feb 10th Ugly Dome 2024
124 Macalester Win 12-8 1587.73 Feb 10th Ugly Dome 2024
95 Wisconsin-Eau Claire Win 11-10 1375.03 Feb 10th Ugly Dome 2024
49 St Olaf Win 13-10 1831.31 Feb 10th Ugly Dome 2024
299 Minnesota-C** Win 13-3 957.54 Ignored Feb 10th Ugly Dome 2024
283 Knox** Win 13-4 1030.89 Ignored Mar 2nd Midwest Throwdown 2024
161 Truman State Win 11-3 1592.69 Mar 2nd Midwest Throwdown 2024
48 Missouri Loss 7-10 1125.1 Mar 2nd Midwest Throwdown 2024
255 St John's (Minnesota)** Win 13-1 1184.96 Ignored Mar 2nd Midwest Throwdown 2024
49 St Olaf Loss 6-11 956.47 Mar 3rd Midwest Throwdown 2024
124 Macalester Win 8-5 1600.18 Mar 3rd Midwest Throwdown 2024
121 Iowa State Loss 8-11 789.45 Mar 3rd Midwest Throwdown 2024
322 Luther Win 13-7 805.59 Mar 16th Southerns 2024
250 Georgia Tech-B** Win 13-3 1227.86 Ignored Mar 16th Southerns 2024
95 Wisconsin-Eau Claire Win 13-8 1746.19 Mar 16th Southerns 2024
244 Georgia Southern** Win 13-5 1250.55 Ignored Mar 16th Southerns 2024
322 Luther** Win 15-3 848.06 Ignored Mar 17th Southerns 2024
191 Georgia-B Win 15-3 1456.08 Mar 17th Southerns 2024
95 Wisconsin-Eau Claire Win 13-11 1478.87 Mar 17th Southerns 2024
**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)