#300 Wisconsin-Stevens Point (2-9)

avg: 681.61  •  sd: 88.34  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
242 Grace Loss 7-11 442.81 Mar 22nd Meltdown 2025
163 Truman State Loss 5-13 622.22 Mar 22nd Meltdown 2025
296 Loyola-Chicago Win 10-6 1213.2 Mar 22nd Meltdown 2025
242 Grace Loss 3-7 309.7 Mar 23rd Meltdown 2025
176 Northern Iowa Loss 5-10 596.93 Mar 23rd Meltdown 2025
103 Marquette** Loss 6-15 853.26 Ignored Apr 12th Lake Superior D I Mens Conferences 2025
44 Wisconsin** Loss 3-15 1177.22 Ignored Apr 12th Lake Superior D I Mens Conferences 2025
135 Wisconsin-Eau Claire Loss 6-13 721.39 Apr 12th Lake Superior D I Mens Conferences 2025
155 Wisconsin-La Crosse Loss 10-12 1014.75 Apr 12th Lake Superior D I Mens Conferences 2025
423 Northern Michigan** Win 15-4 600 Ignored Apr 13th Lake Superior D I Mens Conferences 2025
208 Wisconsin-Whitewater Loss 5-15 434.01 Apr 13th Lake Superior D I Mens Conferences 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)