#297 Knox (6-10)

avg: 710.94  •  sd: 99.5  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
257 DePaul Loss 9-12 511.66 Mar 1st Midwest Throwdown 2025
135 Wisconsin-Eau Claire Loss 7-12 800.88 Mar 1st Midwest Throwdown 2025
103 Marquette** Loss 4-13 853.26 Ignored Mar 1st Midwest Throwdown 2025
288 Carleton College-C Loss 8-9 614.46 Mar 2nd Midwest Throwdown 2025
351 Purdue-B Loss 2-13 -170.71 Mar 2nd Midwest Throwdown 2025
292 Ball State Loss 7-10 340.76 Mar 29th Corny Classic College 2025
403 Notre Dame-B** Win 13-2 600.68 Ignored Mar 29th Corny Classic College 2025
346 Wright State Win 11-7 937.13 Mar 29th Corny Classic College 2025
260 Toledo Loss 6-11 290.52 Mar 30th Corny Classic College 2025
390 Bradley Win 15-4 780.35 Apr 12th Illinois D III Mens Conferences 2025
345 North Park Win 15-8 1038.45 Apr 12th Illinois D III Mens Conferences 2025
129 Asbury** Loss 2-15 740.47 Ignored Apr 26th Great Lakes D III Mens Regionals 2025
125 Butler** Loss 4-15 751.62 Ignored Apr 26th Great Lakes D III Mens Regionals 2025
240 Kalamazoo Win 11-8 1282.82 Apr 26th Great Lakes D III Mens Regionals 2025
338 Rose-Hulman Loss 10-14 144.06 Apr 26th Great Lakes D III Mens Regionals 2025
242 Grace Win 14-8 1445.74 Apr 27th Great Lakes D III Mens Regionals 2025
**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)