#257 Wisconsin-B (8-12)

avg: 917.85  •  sd: 67.67  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
106 Northwestern Loss 7-10 1093.24 Mar 2nd Midwest Throwdown 2024
161 Saint Louis Loss 4-12 683.47 Mar 2nd Midwest Throwdown 2024
134 Macalester Loss 7-8 1247.12 Mar 2nd Midwest Throwdown 2024
353 Carleton College-Karls-C Win 8-7 619.35 Mar 3rd Midwest Throwdown 2024
63 Iowa Loss 4-7 1190.53 Mar 3rd Midwest Throwdown 2024
294 Knox Win 10-9 862.81 Mar 3rd Midwest Throwdown 2024
110 Davenport Loss 3-13 867.57 Mar 16th Grand Rapids College Invite
151 Grace Loss 5-13 711.63 Mar 16th Grand Rapids College Invite
145 Southern Illinois-Edwardsville Loss 7-12 811.24 Mar 16th Grand Rapids College Invite
362 Concordia-Wisconsin Win 13-5 1038.12 Mar 17th Grand Rapids College Invite
282 Toledo Loss 6-9 399.98 Mar 17th Grand Rapids College Invite
270 Wisconsin-Platteville Win 8-6 1160.76 Mar 17th Grand Rapids College Invite
299 Minnesota-C Win 11-8 1084.21 Apr 13th North Central Dev Mens Conferences 2024
413 Marquette-B** Win 15-1 180.15 Ignored Apr 13th North Central Dev Mens Conferences 2024
368 Iowa State-B Win 15-8 965.47 Apr 14th North Central Dev Mens Conferences 2024
122 Minnesota-B Loss 6-15 800.63 Apr 14th North Central Dev Mens Conferences 2024
299 Minnesota-C Win 14-8 1254.63 Apr 27th North Central D I College Mens Regionals 2024
36 Wisconsin Loss 8-15 1329.09 Apr 27th North Central D I College Mens Regionals 2024
184 Wisconsin-La Crosse Loss 10-14 787.73 Apr 27th North Central D I College Mens Regionals 2024
243 Nebraska Loss 8-13 487.28 Apr 28th North Central D I College Mens Regionals 2024
**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)