#11 Michigan (20-4)

avg: 2110.35  •  sd: 103.68  •  top 16/20: 98.3%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
29 Georgia Win 13-6 2324.96 Feb 15th Queen City Tune Up 2025
118 Northwestern** Win 13-0 1539.61 Ignored Feb 15th Queen City Tune Up 2025
69 North Carolina State** Win 13-2 1893.24 Ignored Feb 15th Queen City Tune Up 2025
29 Georgia Win 11-2 2324.96 Feb 16th Queen City Tune Up 2025
37 William & Mary Win 11-2 2201.64 Feb 16th Queen City Tune Up 2025
6 Oregon Win 12-11 2344.89 Mar 22nd Northwest Challenge 2025
8 Stanford Loss 8-11 1768.41 Mar 22nd Northwest Challenge 2025
18 Western Washington Win 12-9 2311.99 Mar 22nd Northwest Challenge 2025
1 British Columbia Loss 9-12 2219.83 Mar 23rd Northwest Challenge 2025
13 Cal Poly-SLO Win 10-7 2469.54 Mar 23rd Northwest Challenge 2025
7 Washington Win 9-8 2314.3 Mar 23rd Northwest Challenge 2025
5 Vermont Loss 6-11 1739.59 Mar 23rd Northwest Challenge 2025
198 Indiana** Win 13-0 1056.08 Ignored Apr 12th Eastern Great Lakes D I Womens Conferences 2025
244 Notre Dame-B** Win 13-1 636.06 Ignored Apr 12th Eastern Great Lakes D I Womens Conferences 2025
74 Purdue** Win 11-4 1860.76 Ignored Apr 12th Eastern Great Lakes D I Womens Conferences 2025
110 Michigan State** Win 11-1 1605.94 Ignored Apr 13th Eastern Great Lakes D I Womens Conferences 2025
17 Notre Dame Loss 7-8 1844.03 Apr 13th Eastern Great Lakes D I Womens Conferences 2025
135 Grand Valley** Win 13-0 1415.26 Ignored Apr 26th Great Lakes D I Womens Regionals 2025
67 Illinois Win 13-7 1867.12 Apr 26th Great Lakes D I Womens Regionals 2025
121 Loyola-Chicago** Win 13-1 1529.71 Ignored Apr 26th Great Lakes D I Womens Regionals 2025
110 Michigan State** Win 13-0 1605.94 Ignored Apr 26th Great Lakes D I Womens Regionals 2025
62 Chicago Win 13-7 1901.23 Apr 27th Great Lakes D I Womens Regionals 2025
118 Northwestern** Win 13-1 1539.61 Ignored Apr 27th Great Lakes D I Womens Regionals 2025
17 Notre Dame Win 12-10 2207.15 Apr 27th Great Lakes D I Womens Regionals 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)