#177 Wisconsin-La Crosse (5-10)

avg: 669  •  sd: 68.45  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
215 Olivet Nazarene Loss 5-6 308.06 Mar 23rd Meltdown 2019
267 Illinois-Chicago Win 8-5 339.77 Mar 23rd Meltdown 2019
126 North Park Loss 3-8 412.13 Mar 23rd Meltdown 2019
222 Valparaiso Win 11-2 984.15 Mar 23rd Meltdown 2019
125 St Benedict Loss 1-11 412.69 Mar 23rd Meltdown 2019
78 Winona State** Loss 4-13 678.15 Ignored Mar 24th Meltdown 2019
218 Loyola-Chicago Win 12-4 1023.24 Mar 24th Meltdown 2019
148 Marquette Loss 7-8 755.94 Mar 24th Meltdown 2019
172 Northern Iowa Loss 7-8 599.75 Mar 30th Old Capitol Open 2019
89 Iowa State Loss 6-7 1098.1 Mar 30th Old Capitol Open 2019
193 Drake Win 5-4 698.3 Mar 30th Old Capitol Open 2019
149 Luther Loss 8-9 744.27 Mar 30th Old Capitol Open 2019
141 Iowa Loss 2-15 306.31 Mar 31st Old Capitol Open 2019
219 Cornell College Win 13-0 1005.19 Mar 31st Old Capitol Open 2019
111 Michigan State Loss 6-10 562.08 Mar 31st Old Capitol Open 2019
**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)