#156 Wisconsin-Milwaukee (9-8)

avg: 845.02  •  sd: 66.55  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
- Missouri Win 8-6 1372.18 Mar 2nd Midwest Throwdown 2019
95 Missouri S&T Win 12-11 1302.58 Mar 2nd Midwest Throwdown 2019
167 Knox Loss 6-7 644.94 Mar 2nd Midwest Throwdown 2019
174 Tulsa Win 6-5 845.8 Mar 2nd Midwest Throwdown 2019
155 Appalachian State Win 10-8 1112.74 Mar 16th Bonanza 2019
47 Williams Loss 6-9 1107.85 Mar 16th Bonanza 2019
197 Christopher Newport Win 10-6 1061.28 Mar 16th Bonanza 2019
82 Georgetown Loss 4-10 666.46 Mar 16th Bonanza 2019
56 Pennsylvania** Loss 5-14 887.36 Ignored Mar 17th Bonanza 2019
82 Georgetown Loss 4-12 666.46 Mar 17th Bonanza 2019
137 Illinois Loss 4-7 440.48 Mar 30th Illinois Invite 8
218 Loyola-Chicago Win 8-4 988.04 Mar 30th Illinois Invite 8
148 Marquette Loss 5-6 755.94 Mar 31st Illinois Invite 8
222 Valparaiso Win 3-2 509.15 Mar 31st Illinois Invite 8
218 Loyola-Chicago Win 7-5 751.38 Mar 31st Illinois Invite 8
148 Marquette Loss 7-11 414.04 Mar 31st Illinois Invite 8
208 Wisconsin-Oshkosh Win 6-4 860.55 Mar 31st Illinois Invite 8
**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)