#321 Idaho (2-10)

avg: 640.22  •  sd: 95.85  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
371 Boise State Win 13-10 684.9 Feb 24th Palouse Open 2024
154 Gonzaga** Loss 3-15 701.37 Feb 24th Palouse Open 2024
160 Washington State** Loss 4-15 683.92 Ignored Feb 24th Palouse Open 2024
276 Whitworth Loss 7-9 566.79 Feb 24th Palouse Open 2024
371 Boise State Win 11-6 903.45 Feb 25th Palouse Open 2024
154 Gonzaga** Loss 5-15 701.37 Feb 25th Palouse Open 2024
180 Brigham Young-B Loss 7-15 594.94 Apr 13th Big Sky D I Mens Conferences 2024
58 Utah Valley** Loss 2-15 1137.54 Ignored Apr 13th Big Sky D I Mens Conferences 2024
32 Utah State** Loss 2-15 1308.9 Ignored Apr 13th Big Sky D I Mens Conferences 2024
29 Utah** Loss 0-15 1347.07 Ignored Apr 13th Big Sky D I Mens Conferences 2024
149 Montana State** Loss 6-15 715.09 Ignored Apr 14th Big Sky D I Mens Conferences 2024
288 Montana Loss 10-13 452.71 Apr 14th Big Sky D I Mens Conferences 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)