#84 Brandeis (16-3)

avg: 1431.89  •  sd: 59.98  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
301 Salisbury** Win 13-4 1253.13 Ignored Feb 23rd Oak Creek Challenge 2019
292 Navy** Win 13-5 1302.9 Ignored Feb 23rd Oak Creek Challenge 2019
174 Cedarville Win 13-6 1667.46 Feb 23rd Oak Creek Challenge 2019
158 Lehigh Win 10-3 1729.08 Feb 23rd Oak Creek Challenge 2019
142 Princeton Win 11-9 1458.91 Feb 24th Oak Creek Challenge 2019
206 West Chester Win 12-8 1407.4 Feb 24th Oak Creek Challenge 2019
114 Liberty Loss 8-9 1175.11 Feb 24th Oak Creek Challenge 2019
302 Rose-Hulman Win 13-6 1252.23 Mar 9th D III Midwestern Invite 2019
177 Winona State Win 9-8 1187.04 Mar 9th D III Midwestern Invite 2019
183 Oberlin Win 12-10 1280.08 Mar 9th D III Midwestern Invite 2019
70 St Olaf Loss 6-8 1200.04 Mar 10th D III Midwestern Invite 2019
291 Pacific Lutheran** Win 9-3 1303.37 Ignored Mar 10th D III Midwestern Invite 2019
176 Bentley Win 13-5 1665.27 Mar 30th Layout Pigout 2019
282 Catholic Win 13-6 1341.95 Mar 30th Layout Pigout 2019
107 Franciscan Win 10-8 1588.18 Mar 30th Layout Pigout 2019
95 Bates College Win 12-6 1949.08 Mar 30th Layout Pigout 2019
96 Bowdoin Loss 6-13 767.81 Mar 31st Layout Pigout 2019
163 SUNY-Geneseo Win 13-9 1525.14 Mar 31st Layout Pigout 2019
107 Franciscan Win 13-10 1653.66 Mar 31st Layout Pigout 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)