#241 Washington-B (10-14)

avg: 888.48  •  sd: 81.53  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
402 Oregon State-B Win 13-8 699.16 Jan 26th Flat Tail Open 2019 Mens
116 Nevada-Reno Loss 3-13 693.72 Jan 26th Flat Tail Open 2019 Mens
446 Lewis & Clark-B** Win 15-0 600 Ignored Jan 26th Flat Tail Open 2019 Mens
58 Whitman Loss 7-13 1022.12 Jan 26th Flat Tail Open 2019 Mens
402 Oregon State-B Win 15-7 803 Jan 27th Flat Tail Open 2019 Mens
180 Humboldt State Win 15-13 1272.61 Jan 27th Flat Tail Open 2019 Mens
326 Western Washington University-B Win 15-8 1146.54 Jan 27th Flat Tail Open 2019 Mens
74 Arizona Win 10-8 1741.76 Feb 9th Stanford Open 2019
41 Las Positas** Loss 3-13 1078.54 Ignored Feb 9th Stanford Open 2019
99 Lewis & Clark Loss 5-11 758.77 Feb 9th Stanford Open 2019
100 California-Santa Cruz Loss 5-11 758.77 Feb 9th Stanford Open 2019
192 Gonzaga Loss 8-13 526.38 Mar 2nd 19th Annual PLU BBQ Open
168 Whitworth Win 13-5 1687.23 Mar 2nd 19th Annual PLU BBQ Open
99 Lewis & Clark Loss 9-11 1109.56 Mar 3rd 19th Annual PLU BBQ Open
192 Gonzaga Win 13-7 1580.08 Mar 3rd 19th Annual PLU BBQ Open
104 Portland Loss 5-11 739.16 Mar 30th 2019 NW Challenge Tier 2 3
200 Montana Loss 5-11 384.24 Mar 30th 2019 NW Challenge Tier 2 3
289 Brigham Young-B Win 11-8 1076.63 Mar 30th 2019 NW Challenge Tier 2 3
280 Idaho Loss 7-11 287.34 Mar 30th 2019 NW Challenge Tier 2 3
162 Washington State Loss 10-12 871.37 Mar 30th 2019 NW Challenge Tier 2 3
291 Pacific Lutheran Win 13-1 1303.37 Mar 31st 2019 NW Challenge Tier 2 3
104 Portland Loss 3-13 739.16 Mar 31st 2019 NW Challenge Tier 2 3
200 Montana Loss 8-11 618.63 Mar 31st 2019 NW Challenge Tier 2 3
280 Idaho Loss 8-13 258.07 Mar 31st 2019 NW Challenge Tier 2 3
**Blowout Eligible

FAQ

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
  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
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)