#138 Gonzaga (6-10)

avg: 1313.2  •  sd: 55.09  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
224 Oregon-B Win 13-11 1205.23 Mar 1st PLU BBQ men
246 Oregon State-B Win 13-8 1393.9 Mar 1st PLU BBQ men
250 Portland Win 15-10 1337.34 Mar 2nd PLU BBQ men
246 Oregon State-B Win 15-8 1462.55 Mar 2nd PLU BBQ men
7 Brigham Young Loss 11-15 1865 Mar 22nd Northwest Challenge 2025 mens
10 British Columbia** Loss 5-15 1551.93 Ignored Mar 22nd Northwest Challenge 2025 mens
31 California-Santa Barbara Loss 6-15 1261.88 Mar 22nd Northwest Challenge 2025 mens
44 Wisconsin Loss 11-15 1396.06 Mar 22nd Northwest Challenge 2025 mens
34 Utah Loss 8-15 1275.34 Mar 23rd Northwest Challenge 2025 mens
54 UCLA Loss 5-15 1104.08 Mar 23rd Northwest Challenge 2025 mens
44 Wisconsin Loss 3-11 1177.22 Mar 23rd Northwest Challenge 2025 mens
7 Brigham Young** Loss 5-15 1646.17 Ignored Apr 19th Big Sky D I Mens Conferences 2025
32 Utah State Loss 7-15 1252.16 Apr 19th Big Sky D I Mens Conferences 2025
289 Montana Win 15-7 1335.93 Apr 19th Big Sky D I Mens Conferences 2025
366 Boise State** Win 15-5 946.35 Ignored Apr 20th Big Sky D I Mens Conferences 2025
166 Montana State Loss 14-15 1086.12 Apr 20th Big Sky D I Mens Conferences 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)