#182 Messiah (9-7)

avg: 1042.84  •  sd: 90.15  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
138 Missouri S&T Win 13-12 1355.09 Mar 2nd FCS D III Tune Up 2019
146 North Carolina-Asheville Loss 10-11 1063.17 Mar 2nd FCS D III Tune Up 2019
75 Air Force Loss 8-13 981.38 Mar 2nd FCS D III Tune Up 2019
253 Anderson Win 13-5 1443.09 Mar 2nd FCS D III Tune Up 2019
223 Rensselaer Polytech Win 13-10 1244.75 Mar 3rd FCS D III Tune Up 2019
251 Samford Win 12-10 1089.45 Mar 3rd FCS D III Tune Up 2019
155 Elon Loss 9-12 804.22 Mar 3rd FCS D III Tune Up 2019
266 Penn State-B Win 12-7 1318.85 Mar 16th Squirrely Cuts Only 2018 DIIIB team tournament
437 Towson -B** Win 13-0 372.21 Ignored Mar 16th Squirrely Cuts Only 2018 DIIIB team tournament
373 Edinboro Win 11-8 725.84 Mar 16th Squirrely Cuts Only 2018 DIIIB team tournament
349 William & Mary-B Win 13-1 1085.45 Mar 16th Squirrely Cuts Only 2018 DIIIB team tournament
85 Richmond Loss 11-12 1304.7 Mar 30th D3 EASTUR 2019
248 Shippensburg Win 12-6 1445.64 Mar 30th D3 EASTUR 2019
113 Davidson Loss 8-10 1039.23 Mar 30th D3 EASTUR 2019
141 Wesleyan Loss 8-13 719.09 Mar 31st D3 EASTUR 2019
320 Ohio State-B Loss 9-13 173.97 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)