#75 Air Force (14-3)

avg: 1477.54  •  sd: 67.62  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
- Sonoma State** Win 13-5 1110.53 Ignored Feb 9th Stanford Open 2019
116 Nevada-Reno Win 13-6 1893.72 Feb 9th Stanford Open 2019
216 Occidental Win 13-4 1527.34 Feb 9th Stanford Open 2019
199 Claremont Win 7-1 1596.34 Feb 10th Stanford Open 2019
21 California Loss 8-9 1718.46 Feb 10th Stanford Open 2019
182 Messiah Win 13-8 1539 Mar 2nd FCS D III Tune Up 2019
35 Middlebury Loss 13-14 1601.5 Mar 2nd FCS D III Tune Up 2019
310 Campbell Win 13-9 1046.75 Mar 2nd FCS D III Tune Up 2019
113 Davidson Win 12-9 1647.26 Mar 2nd FCS D III Tune Up 2019
234 Florida Tech Win 13-8 1402.42 Mar 2nd FCS D III Tune Up 2019
85 Richmond Loss 7-11 962.81 Mar 3rd FCS D III Tune Up 2019
292 Navy Win 13-11 931.74 Mar 3rd FCS D III Tune Up 2019
125 Colorado School of Mines Win 13-10 1606.47 Mar 16th Air Force Invite 2019
170 Colorado-Denver Win 13-6 1683.91 Mar 16th Air Force Invite 2019
123 New Mexico Win 12-9 1624.78 Mar 17th Air Force Invite 2019
244 Colorado-B** Win 13-4 1477.2 Ignored Mar 17th Air Force Invite 2019
307 Colorado Mesa** Win 13-0 1240.69 Ignored Mar 17th Air Force Invite 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)