#292 Navy (3-14)

avg: 702.9  •  sd: 84.18  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
301 Salisbury Loss 8-13 156.97 Feb 23rd Oak Creek Challenge 2019
174 Cedarville Loss 10-12 829.33 Feb 23rd Oak Creek Challenge 2019
158 Lehigh Loss 6-13 529.08 Feb 23rd Oak Creek Challenge 2019
84 Brandeis** Loss 5-13 831.89 Ignored Feb 23rd Oak Creek Challenge 2019
299 Towson Win 15-3 1282.65 Feb 24th Oak Creek Challenge 2019
188 East Carolina Loss 9-12 685 Feb 24th Oak Creek Challenge 2019
247 Xavier Loss 11-13 645.9 Mar 2nd FCS D III Tune Up 2019
173 Georgia College Loss 11-13 840.27 Mar 2nd FCS D III Tune Up 2019
107 Franciscan Loss 10-13 997.38 Mar 2nd FCS D III Tune Up 2019
300 High Point Win 13-7 1234.67 Mar 2nd FCS D III Tune Up 2019
75 Air Force Loss 11-13 1248.7 Mar 3rd FCS D III Tune Up 2019
208 Berry Loss 5-13 358.78 Mar 3rd FCS D III Tune Up 2019
146 North Carolina-Asheville Loss 4-11 588.17 Mar 3rd FCS D III Tune Up 2019
356 West Virginia Loss 9-11 199.56 Mar 30th Garden State 9
343 Dickinson Loss 10-12 274.17 Mar 30th Garden State 9
335 College of New Jersey Win 12-8 982.37 Mar 30th Garden State 9
239 Slippery Rock Loss 11-14 583.02 Mar 31st Garden State 9
**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)