#85 Richmond (19-7)

avg: 1429.7  •  sd: 61.61  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
73 Temple Loss 7-11 1013.98 Jan 25th Carolina Kickoff 2019
78 Carleton College-GoP Loss 9-13 1039.15 Jan 26th Carolina Kickoff 2019
62 Duke Win 12-7 2071.52 Jan 26th Carolina Kickoff 2019
1 North Carolina** Loss 4-13 1631.92 Ignored Jan 26th Carolina Kickoff 2019
25 South Carolina Loss 4-15 1186.69 Jan 27th Carolina Kickoff 2019
73 Temple Win 11-10 1605.87 Jan 27th Carolina Kickoff 2019
197 George Mason Win 12-10 1239.52 Feb 2nd Mid Atlantic Warmup 2019
195 George Washington Win 13-6 1603.81 Feb 2nd Mid Atlantic Warmup 2019
158 Lehigh Win 13-7 1686.61 Feb 2nd Mid Atlantic Warmup 2019
151 SUNY-Binghamton Win 13-12 1287.14 Feb 2nd Mid Atlantic Warmup 2019
110 Williams Win 15-12 1616.31 Feb 3rd Mid Atlantic Warmup 2019
39 Vermont Loss 8-15 1140.96 Feb 3rd Mid Atlantic Warmup 2019
88 Tennessee-Chattanooga Loss 9-11 1169.98 Feb 3rd Mid Atlantic Warmup 2019
107 Franciscan Win 13-11 1554.36 Mar 2nd FCS D III Tune Up 2019
251 Samford Win 13-5 1451.32 Mar 2nd FCS D III Tune Up 2019
138 Missouri S&T Win 13-8 1726.25 Mar 2nd FCS D III Tune Up 2019
155 Elon Win 12-8 1590.74 Mar 2nd FCS D III Tune Up 2019
183 Oberlin Win 12-7 1562.47 Mar 3rd FCS D III Tune Up 2019
75 Air Force Win 11-7 1944.43 Mar 3rd FCS D III Tune Up 2019
173 Georgia College Win 9-7 1348.44 Mar 3rd FCS D III Tune Up 2019
32 William & Mary Win 16-14 1954.97 Mar 23rd Virginia Showcase Series 32319
182 Messiah Win 12-11 1167.84 Mar 30th D3 EASTUR 2019
248 Shippensburg Win 12-7 1386.84 Mar 30th D3 EASTUR 2019
320 Ohio State-B** Win 13-5 1192.54 Ignored Mar 30th D3 EASTUR 2019
113 Davidson Loss 5-13 701.9 Mar 31st D3 EASTUR 2019
141 Wesleyan Win 12-11 1340.25 Mar 31st D3 EASTUR 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)