#176 Saint Louis (11-9)

avg: 926.24  •  sd: 72.78  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
192 Harding Loss 4-10 251.11 Feb 17th Dust Bowl 2024
314 Kansas-B Win 10-8 545.61 Feb 17th Dust Bowl 2024
161 Truman State Win 9-6 1411.25 Feb 17th Dust Bowl 2024
188 John Brown Loss 10-13 534.24 Feb 18th Dust Bowl 2024
253 Nebraska Win 12-11 730.68 Feb 18th Dust Bowl 2024
317 Washington University-B Win 13-7 827.75 Feb 18th Dust Bowl 2024
83 Northwestern Loss 9-10 1210.48 Mar 2nd Midwest Throwdown 2024
124 Macalester Loss 5-9 617.52 Mar 2nd Midwest Throwdown 2024
259 Wisconsin-B Win 12-4 1160.43 Mar 2nd Midwest Throwdown 2024
325 Carleton College-Karls-C** Win 11-1 812.24 Ignored Mar 3rd Midwest Throwdown 2024
195 Grinnell Win 9-6 1264.63 Mar 3rd Midwest Throwdown 2024
81 Iowa Loss 7-10 947.94 Mar 3rd Midwest Throwdown 2024
255 St John's (Minnesota) Win 9-6 1003.53 Mar 3rd Midwest Throwdown 2024
188 John Brown Loss 7-9 583.05 Mar 23rd Free State Classic
135 Kansas Loss 8-10 844.57 Mar 23rd Free State Classic
161 Truman State Win 11-7 1459.58 Mar 23rd Free State Classic
49 St Olaf Loss 8-11 1137.56 Mar 23rd Free State Classic
188 John Brown Loss 9-10 737.39 Mar 24th Free State Classic
254 Oklahoma State Win 12-11 724.53 Mar 24th Free State Classic
161 Truman State Win 11-8 1358.3 Mar 24th Free State Classic
**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)