#241 Michigan-B (5-11)

avg: 642.3  •  sd: 86.52  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
149 Davidson Loss 3-13 454.75 Feb 15th 2025 Commonwealth Cup Weekend 1
131 Pittsburgh-B Loss 8-13 625.14 Feb 15th 2025 Commonwealth Cup Weekend 1
255 Wake Forest Loss 7-8 461.48 Feb 15th 2025 Commonwealth Cup Weekend 1
256 Illinois-B Loss 6-9 161.97 Feb 16th 2025 Commonwealth Cup Weekend 1
164 Ohio Loss 4-10 376.87 Feb 16th 2025 Commonwealth Cup Weekend 1
187 North Carolina-B Win 9-8 989.39 Feb 16th 2025 Commonwealth Cup Weekend 1
142 Grand Valley Loss 6-12 487.17 Mar 15th Grand Rapids Invite 2025
221 Wisconsin-B Loss 8-10 448.04 Mar 15th Grand Rapids Invite 2025
281 Wisconsin-Platteville Win 8-7 575.87 Mar 15th Grand Rapids Invite 2025
212 Eastern Michigan Win 15-8 1315.13 Mar 16th Grand Rapids Invite 2025
142 Grand Valley Loss 9-12 721.12 Mar 16th Grand Rapids Invite 2025
292 Western Michigan Loss 11-12 281.21 Mar 16th Grand Rapids Invite 2025
212 Eastern Michigan Loss 8-9 625.33 Mar 29th King of the Hill 2025
204 Hillsdale Loss 6-13 185.37 Mar 29th King of the Hill 2025
288 Michigan State-B Win 13-3 1021.05 Mar 29th King of the Hill 2025
229 Valparaiso Win 11-5 1289.37 Mar 29th King of the Hill 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)