#82 St Olaf (17-8)

avg: 1321  •  sd: 79.19  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
54 Carleton College-CHOP Loss 7-13 980.53 Feb 8th Gopher Dome 2025
178 Minnesota-B Win 13-5 1520.73 Feb 8th Gopher Dome 2025
331 Minnesota-C** Win 13-5 831.6 Ignored Feb 8th Gopher Dome 2025
154 Macalester Loss 10-11 917.94 Feb 8th Gopher Dome 2025
161 Wisconsin-Eau Claire Win 11-7 1451.06 Feb 8th Gopher Dome 2025
306 Carleton College-C** Win 13-1 941.95 Ignored Mar 1st Midwest Throwdown 2025
156 Wisconsin-La Crosse Win 12-5 1618.24 Mar 1st Midwest Throwdown 2025
221 Wisconsin-B** Win 10-3 1310.71 Ignored Mar 1st Midwest Throwdown 2025
107 Iowa Loss 9-10 1097.36 Mar 2nd Midwest Throwdown 2025
77 Iowa State Win 9-6 1768.6 Mar 2nd Midwest Throwdown 2025
309 Washington University-B** Win 13-2 917.98 Ignored Mar 2nd Midwest Throwdown 2025
156 Wisconsin-La Crosse Win 7-4 1514.4 Mar 2nd Midwest Throwdown 2025
384 Carthage** Win 13-0 289.56 Ignored Mar 22nd Meltdown 2025
354 Illinois-Chicago** Win 13-1 661.68 Ignored Mar 22nd Meltdown 2025
145 Kenyon Loss 11-12 934.11 Mar 22nd Meltdown 2025
293 Minnesota State-Mankato** Win 13-5 1000.87 Ignored Mar 22nd Meltdown 2025
220 Winona State Win 11-5 1314.32 Mar 23rd Meltdown 2025
168 Truman State Win 10-6 1460.77 Mar 23rd Meltdown 2025
135 Mississippi State Loss 10-11 986.28 Mar 29th Huck Finn 2025
141 Northwestern Win 14-9 1546.73 Mar 29th Huck Finn 2025
51 Purdue Loss 8-13 1059.7 Mar 29th Huck Finn 2025
154 Macalester Win 13-6 1642.94 Mar 29th Huck Finn 2025
77 Iowa State Win 13-6 1950.03 Mar 30th Huck Finn 2025
84 Ohio State Loss 9-12 974.31 Mar 30th Huck Finn 2025
72 Southern Illinois-Edwardsville Loss 7-9 1117.28 Mar 30th Huck Finn 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)