#231 Christopher Newport (11-8)

avg: 712.61  •  sd: 59.66  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
163 Xavier Loss 8-13 477.32 Mar 2nd FCS D III Tune Up 2024
226 Embry-Riddle Win 13-12 855 Mar 2nd FCS D III Tune Up 2024
59 Whitman Loss 6-13 836.78 Mar 2nd FCS D III Tune Up 2024
51 Franciscan Loss 7-13 938.75 Mar 2nd FCS D III Tune Up 2024
257 Air Force Win 13-8 1067.52 Mar 3rd FCS D III Tune Up 2024
119 Berry Loss 9-13 753.76 Mar 3rd FCS D III Tune Up 2024
199 Messiah Loss 11-13 603.4 Mar 3rd FCS D III Tune Up 2024
301 Virginia-B Win 9-7 628.58 Mar 23rd Fishbowl
372 William & Mary-B** Win 13-3 328.1 Ignored Mar 23rd Fishbowl
346 George Washington-B Win 10-5 617.76 Mar 23rd Fishbowl
256 Virginia Tech-B Win 9-8 701.62 Mar 23rd Fishbowl
308 James Madison-B Win 13-7 874.12 Mar 24th Fishbowl
256 Virginia Tech-B Win 10-8 839.29 Mar 24th Fishbowl
224 American Loss 7-15 131.75 Mar 30th Atlantic Coast Open 2024
206 George Washington Loss 6-15 203.3 Mar 30th Atlantic Coast Open 2024
126 Lehigh Loss 9-15 629.91 Mar 30th Atlantic Coast Open 2024
252 Dickinson Win 15-14 735.43 Mar 30th Atlantic Coast Open 2024
298 Mary Washington Win 13-6 963.78 Mar 31st Atlantic Coast Open 2024
256 Virginia Tech-B Win 13-8 1072.78 Mar 31st Atlantic Coast Open 2024
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)