#353 Carleton College-Karls-C (3-9)

avg: 494.35  •  sd: 91.24  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
107 Iowa State** Loss 0-13 876.13 Ignored Mar 2nd Midwest Throwdown 2024
320 Washington University-B Loss 8-10 388.67 Mar 2nd Midwest Throwdown 2024
193 Grinnell** Loss 2-13 554.63 Ignored Mar 2nd Midwest Throwdown 2024
94 Wisconsin-Eau Claire** Loss 1-9 934.71 Ignored Mar 2nd Midwest Throwdown 2024
373 Northwestern-B Win 9-6 750.98 Mar 3rd Midwest Throwdown 2024
161 Saint Louis** Loss 1-11 683.47 Ignored Mar 3rd Midwest Throwdown 2024
257 Wisconsin-B Loss 7-8 792.85 Mar 3rd Midwest Throwdown 2024
391 Bethel Win 9-5 711.77 Apr 13th Northwoods D III Mens Conferences 2024
45 St Olaf** Loss 1-15 1211.34 Ignored Apr 13th Northwoods D III Mens Conferences 2024
227 St John's (Minnesota) Loss 6-13 429.82 Apr 13th Northwoods D III Mens Conferences 2024
391 Bethel Win 10-9 307.71 Apr 14th Northwoods D III Mens Conferences 2024
269 Winona State Loss 5-11 263.91 Apr 14th Northwoods D III Mens Conferences 2024
**Blowout Eligible

FAQ

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
  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
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)