#37 Carleton College-Eclipse (19-3)

avg: 1749.41  •  sd: 136.47  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
148 Cal Poly-SLO-B** Win 13-4 1481.05 Ignored Feb 3rd Stanford Open 2024
85 California-San Diego-B Win 7-6 1464.27 Feb 3rd Stanford Open 2024
135 Claremont** Win 13-3 1578.82 Ignored Feb 3rd Stanford Open 2024
43 Portland Loss 5-8 1208 Feb 10th DIII Grand Prix
48 Colorado College Loss 8-10 1350.7 Feb 10th DIII Grand Prix
118 Puget Sound** Win 12-4 1710.05 Ignored Feb 10th DIII Grand Prix
75 Lewis & Clark Win 11-7 1841.97 Feb 10th DIII Grand Prix
46 Whitman Win 10-7 2029.98 Feb 11th DIII Grand Prix
154 Oregon State** Win 10-2 1459.31 Ignored Feb 11th DIII Grand Prix
48 Colorado College Win 6-5 1738.36 Feb 11th DIII Grand Prix
226 Georgia Southern** Win 13-1 798.86 Ignored Mar 16th Southerns 2024
241 Florida-B** Win 13-0 435.05 Ignored Mar 16th Southerns 2024
120 Charleston** Win 13-5 1682.15 Ignored Mar 16th Southerns 2024
225 North Carolina-Wilmington** Win 13-2 817.16 Ignored Mar 16th Southerns 2024
218 Georgia-B** Win 15-0 884.36 Ignored Mar 17th Southerns 2024
120 Charleston** Win 15-6 1682.15 Ignored Mar 17th Southerns 2024
123 East Carolina** Win 15-4 1673.86 Ignored Mar 17th Southerns 2024
245 St Olaf-B** Win 15-0 182.75 Ignored Apr 13th North Central D III Womens Conferences 2024
242 St Thomas** Win 15-4 430.15 Ignored Apr 13th North Central D III Womens Conferences 2024
45 Macalester Loss 7-8 1517.54 Apr 13th North Central D III Womens Conferences 2024
35 St Olaf Win 15-2 2378.48 Apr 14th North Central D III Womens Conferences 2024
128 Grinnell** Win 15-5 1639.8 Ignored Apr 14th North Central D III Womens Conferences 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)