#201 Wisconsin-Eau Claire (9-7)

avg: 932.63  •  sd: 53.95  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
334 Illinois State-B Win 15-4 1030.32 Mar 3rd Midwest Throwdown 2018
306 Carleton College-Hot Karls Win 15-5 1160.36 Mar 3rd Midwest Throwdown 2018
171 Truman State Loss 13-14 913.6 Mar 3rd Midwest Throwdown 2018
261 Drake Win 16-14 955.65 Mar 4th Midwest Throwdown 2018
139 Luther Loss 8-14 632.01 Mar 4th Midwest Throwdown 2018
363 Wisconsin-Oshkosh Win 13-9 751.48 Mar 4th Midwest Throwdown 2018
150 North Carolina-Asheville Loss 5-13 531.08 Mar 17th College Southerns 2018
248 North Georgia Win 13-7 1331.86 Mar 17th College Southerns 2018
207 Florida-B Win 13-12 1045.75 Mar 17th College Southerns 2018
340 Stetson Win 13-7 968.16 Mar 17th College Southerns 2018
207 Florida-B Win 11-9 1169.96 Mar 18th College Southerns 2018
125 Georgia College Loss 12-13 1090.81 Mar 18th College Southerns 2018
123 Nebraska Loss 9-12 905.07 Mar 31st Illinois Invite 2018
190 Northern Iowa Loss 6-9 557.22 Mar 31st Illinois Invite 2018
246 Winona State Win 12-11 904.81 Mar 31st Illinois Invite 2018
118 Wisconsin-Whitewater Loss 6-8 964.33 Mar 31st Illinois Invite 2018
**Blowout Eligible

FAQ

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
  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
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)