#183 Oberlin (8-11)

avg: 1041.96  •  sd: 74.51  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
138 Missouri S&T Loss 8-13 733.93 Mar 2nd FCS D III Tune Up 2019
155 Elon Loss 11-13 920.74 Mar 2nd FCS D III Tune Up 2019
91 Mary Washington Loss 9-10 1257.51 Mar 2nd FCS D III Tune Up 2019
146 North Carolina-Asheville Loss 9-11 938.96 Mar 2nd FCS D III Tune Up 2019
223 Rensselaer Polytech Loss 6-13 316.61 Mar 3rd FCS D III Tune Up 2019
85 Richmond Loss 7-12 909.19 Mar 3rd FCS D III Tune Up 2019
300 High Point Win 13-7 1234.67 Mar 3rd FCS D III Tune Up 2019
302 Rose-Hulman Win 7-5 980.37 Mar 9th D III Midwestern Invite 2019
84 Brandeis Loss 10-12 1193.77 Mar 9th D III Midwestern Invite 2019
177 Winona State Loss 5-6 937.04 Mar 9th D III Midwestern Invite 2019
186 Macalester Loss 6-10 535.46 Mar 10th D III Midwestern Invite 2019
331 Kenyon Win 13-6 1159.98 Mar 23rd CWRUL Memorial 2019
231 Knox Win 10-9 1035.52 Mar 23rd CWRUL Memorial 2019
347 Wright State Win 13-6 1091.16 Mar 23rd CWRUL Memorial 2019
154 Syracuse Loss 7-13 593.04 Mar 23rd CWRUL Memorial 2019
171 RIT Win 11-7 1548.54 Mar 24th CWRUL Memorial 2019
38 Purdue Loss 8-15 1142.23 Mar 24th CWRUL Memorial 2019
158 Lehigh Win 13-11 1357.92 Mar 24th CWRUL Memorial 2019
145 Dayton Win 11-7 1656.57 Mar 24th CWRUL Memorial 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)