#49 St Olaf (22-3)

avg: 1503.16  •  sd: 69.17  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
78 Carleton College-CHOP Loss 10-13 1020.8 Feb 10th Ugly Dome 2024
140 Minnesota-B Win 12-10 1316.16 Feb 10th Ugly Dome 2024
299 Minnesota-C** Win 13-3 957.54 Ignored Feb 10th Ugly Dome 2024
95 Wisconsin-Eau Claire Win 13-10 1578.17 Feb 10th Ugly Dome 2024
124 Macalester Win 10-9 1271.58 Feb 10th Ugly Dome 2024
81 Iowa Win 12-8 1778.76 Mar 2nd Midwest Throwdown 2024
170 Minnesota-Duluth Win 13-3 1550.77 Mar 2nd Midwest Throwdown 2024
370 Northwestern-B** Win 13-4 394.7 Ignored Mar 2nd Midwest Throwdown 2024
78 Carleton College-CHOP Win 11-6 1895.64 Mar 3rd Midwest Throwdown 2024
48 Missouri Win 9-8 1639.77 Mar 3rd Midwest Throwdown 2024
95 Wisconsin-Eau Claire Win 9-5 1779.09 Mar 3rd Midwest Throwdown 2024
188 John Brown Win 12-9 1207.75 Mar 23rd Free State Classic
135 Kansas Win 11-10 1232.24 Mar 23rd Free State Classic
176 Saint Louis Win 11-8 1291.85 Mar 23rd Free State Classic
161 Truman State Win 9-7 1272.02 Mar 23rd Free State Classic
135 Kansas Win 15-8 1672.05 Mar 24th Free State Classic
179 Missouri S&T Win 14-12 1125.06 Mar 24th Free State Classic
180 Wisconsin-La Crosse** Win 15-4 1498.16 Ignored Mar 24th Free State Classic
50 Alabama Win 13-9 1920.13 Mar 30th Huck Finn 2024
76 Purdue Win 11-10 1482.22 Mar 30th Huck Finn 2024
66 Virginia Win 10-7 1783.83 Mar 30th Huck Finn 2024
19 Washington University Loss 9-12 1519.81 Mar 30th Huck Finn 2024
91 Indiana Win 12-7 1791.32 Mar 31st Huck Finn 2024
83 Northwestern Win 12-10 1573.6 Mar 31st Huck Finn 2024
19 Washington University Loss 7-13 1307.64 Mar 31st Huck Finn 2024
**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)