#73 St. Olaf (16-4)

avg: 1226.89  •  sd: 74.47  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
183 Indiana** Win 11-1 871.27 Ignored Mar 4th Midwest Throwdown 2023
165 Truman State** Win 11-1 1082.35 Ignored Mar 4th Midwest Throwdown 2023
207 Northwestern-B** Win 11-0 610.56 Ignored Mar 4th Midwest Throwdown 2023
122 Purdue Win 8-4 1393.16 Mar 4th Midwest Throwdown 2023
106 Marquette Win 10-6 1447.9 Mar 5th Midwest Throwdown 2023
45 Washington University Loss 1-13 879.26 Mar 5th Midwest Throwdown 2023
122 Purdue Win 8-4 1393.16 Mar 5th Midwest Throwdown 2023
56 Tennessee Loss 6-13 740.42 Mar 25th Needle in a Ho Stack2
94 Boston College Win 8-6 1338.99 Mar 25th Needle in a Ho Stack2
186 Richmond** Win 13-1 861.23 Ignored Mar 25th Needle in a Ho Stack2
114 Union (Tennessee) Win 6-5 1024.39 Mar 25th Needle in a Ho Stack2
201 Wake Forest** Win 13-0 662.67 Ignored Mar 26th Needle in a Ho Stack2
16 Middlebury Loss 8-9 1710.84 Mar 26th Needle in a Ho Stack2
171 Illinois Win 7-4 905.14 Apr 1st Illinois Invite1
123 Denver Win 4-2 1317.18 Apr 1st Illinois Invite1
165 Truman State** Win 13-0 1082.35 Ignored Apr 1st Illinois Invite1
106 Marquette Loss 5-6 826.74 Apr 1st Illinois Invite1
174 Wheaton (Illinois)** Win 13-2 994.94 Ignored Apr 2nd Illinois Invite1
123 Denver Win 9-3 1421.02 Apr 2nd Illinois Invite1
106 Marquette Win 13-1 1551.74 Apr 2nd Illinois Invite1
**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)