#162 Saint Louis (11-8)

avg: 1079.75  •  sd: 70.67  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
89 John Brown Loss 6-10 886.15 Feb 24th Dust Bowl 2018
123 Nebraska Loss 5-10 676.54 Feb 24th Dust Bowl 2018
200 Rice Win 9-8 1057.65 Feb 24th Dust Bowl 2018
112 Texas Tech Loss 6-9 866.52 Feb 24th Dust Bowl 2018
96 Missouri State Loss 7-15 750.5 Feb 25th Dust Bowl 2018
139 Luther Loss 9-15 652.56 Feb 25th Dust Bowl 2018
200 Rice Win 11-7 1399.55 Feb 25th Dust Bowl 2018
128 Colorado School of Mines Win 15-13 1418.04 Feb 25th Dust Bowl 2018
334 Illinois State-B Win 13-7 987.85 Mar 10th Last Call 9
422 Illinois-C** Win 13-1 402.48 Ignored Mar 10th Last Call 9
337 DePaul** Win 10-4 1012.99 Ignored Mar 10th Last Call 9
398 Rose-Hulman** Win 13-3 689.95 Ignored Mar 10th Last Call 9
346 Illinois-Chicago** Win 13-3 988.64 Ignored Mar 11th Last Call 9
144 Dayton Win 11-8 1519.14 Mar 11th Last Call 9
246 Winona State Win 12-4 1379.81 Mar 11th Last Call 9
246 Winona State Win 13-6 1379.81 Mar 11th Last Call 9
49 Marquette Loss 9-15 1032.88 Mar 31st Huck Finn 2018
91 Penn State Loss 14-16 1165.61 Mar 31st Huck Finn 2018
81 Florida State Loss 9-15 893.24 Mar 31st Huck Finn 2018
**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)