#121 Iowa State (9-10)

avg: 1155.06  •  sd: 67.27  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
325 Carleton College-Karls-C** Win 13-0 812.24 Ignored Mar 2nd Midwest Throwdown 2024
195 Grinnell Win 9-8 971.06 Mar 2nd Midwest Throwdown 2024
95 Wisconsin-Eau Claire Loss 9-11 1000.82 Mar 2nd Midwest Throwdown 2024
317 Washington University-B** Win 13-4 870.22 Ignored Mar 2nd Midwest Throwdown 2024
78 Carleton College-CHOP Win 11-8 1714.55 Mar 3rd Midwest Throwdown 2024
83 Northwestern Loss 7-10 945.82 Mar 3rd Midwest Throwdown 2024
170 Minnesota-Duluth Win 10-9 1075.77 Mar 3rd Midwest Throwdown 2024
98 Dartmouth Win 8-6 1546.13 Mar 16th College Mens Centex Tier 1
40 Illinois Loss 9-11 1330.48 Mar 16th College Mens Centex Tier 1
31 Middlebury Loss 9-13 1238.56 Mar 16th College Mens Centex Tier 1
14 Texas** Loss 3-13 1336.64 Ignored Mar 16th College Mens Centex Tier 1
128 Colorado College Loss 7-12 615.49 Mar 17th College Mens Centex Tier 1
53 Colorado State Win 11-10 1595.56 Mar 17th College Mens Centex Tier 1
91 Indiana Loss 8-11 905.2 Mar 30th Huck Finn 2024
209 Oklahoma Win 11-6 1330.7 Mar 30th Huck Finn 2024
105 Mississippi State Loss 9-10 1085.79 Mar 30th Huck Finn 2024
132 Arkansas Loss 9-10 986.85 Mar 31st Huck Finn 2024
82 Central Florida Loss 7-12 816.76 Mar 31st Huck Finn 2024
204 Ohio Win 13-2 1409.59 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)