#259 Wisconsin-B (4-8)

avg: 560.43  •  sd: 81.03  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
83 Northwestern Loss 7-10 945.82 Mar 2nd Midwest Throwdown 2024
176 Saint Louis Loss 4-12 326.24 Mar 2nd Midwest Throwdown 2024
124 Macalester Loss 7-8 1021.58 Mar 2nd Midwest Throwdown 2024
325 Carleton College-Karls-C Win 8-7 337.24 Mar 3rd Midwest Throwdown 2024
81 Iowa Loss 4-7 841.45 Mar 3rd Midwest Throwdown 2024
283 Knox Win 10-9 555.89 Mar 3rd Midwest Throwdown 2024
102 Davenport** Loss 3-13 617.27 Ignored Mar 16th Grand Rapids College Invite
155 Grace Loss 5-13 422.24 Mar 16th Grand Rapids College Invite
145 Southern Illinois-Edwardsville Loss 7-12 539.9 Mar 16th Grand Rapids College Invite
355 Concordia-Wisconsin Win 13-5 607.19 Mar 17th Grand Rapids College Invite
294 Toledo Loss 6-9 -31.01 Mar 17th Grand Rapids College Invite
287 Wisconsin-Platteville Win 8-6 721.29 Mar 17th Grand Rapids College Invite
**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)