#112 Wisconsin-Whitewater (15-5)

avg: 1306.21  •  sd: 60.29  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
159 Mississippi State Loss 4-13 525.81 Mar 2nd Mardi Gras XXXII
36 Alabama Loss 6-13 1123.14 Mar 2nd Mardi Gras XXXII
23 Texas Tech Loss 10-13 1502.99 Mar 2nd Mardi Gras XXXII
82 Texas State Loss 11-13 1213.81 Mar 2nd Mardi Gras XXXII
207 North Florida Win 13-9 1384.08 Mar 3rd Mardi Gras XXXII
161 Sul Ross State Win 14-12 1338.86 Mar 3rd Mardi Gras XXXII
346 Marquette-B** Win 13-4 1100.18 Ignored Mar 22nd Meltdown 2019
309 Illinois State-B Win 10-6 1129.38 Mar 22nd Meltdown 2019
329 Northern Illinois Win 11-7 1028.82 Mar 22nd Meltdown 2019
198 Valparaiso Win 11-9 1247.27 Mar 22nd Meltdown 2019
258 Olivet Nazarene Win 13-5 1430.05 Mar 24th Meltdown 2019
203 Wheaton (Illinois) Win 10-8 1234.78 Mar 24th Meltdown 2019
177 Winona State Loss 11-12 937.04 Mar 24th Meltdown 2019
219 Michigan State Win 13-6 1522.83 Mar 30th Illinois Invite 8
124 Wisconsin-Milwaukee Win 11-8 1644.33 Mar 30th Illinois Invite 8
286 Toledo Win 13-1 1322.93 Mar 30th Illinois Invite 8
219 Michigan State Win 11-8 1288.44 Mar 31st Illinois Invite 8
148 Michigan-B Win 11-3 1781.95 Mar 31st Illinois Invite 8
97 Grand Valley State Win 13-12 1488.8 Mar 31st Illinois Invite 8
205 Wisconsin-B Win 8-4 1535.4 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)