#5 Cal Poly-SLO (24-4)

avg: 2144.46  •  sd: 42.54  •  top 16/20: 100%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
6 Brigham Young Loss 9-13 1716.17 Jan 25th Santa Barbara Invite 2019
100 California-Santa Cruz Win 13-6 1958.77 Jan 26th Santa Barbara Invite 2019
29 Texas-Dallas Win 13-6 2371.91 Jan 26th Santa Barbara Invite 2019
51 Western Washington Win 13-3 2229.76 Jan 26th Santa Barbara Invite 2019
40 Dartmouth Win 13-8 2182.63 Jan 26th Santa Barbara Invite 2019
42 British Columbia Win 13-9 2092.17 Jan 27th Santa Barbara Invite 2019
10 Washington Win 13-11 2273.35 Jan 27th Santa Barbara Invite 2019
30 Victoria Win 13-7 2323.43 Jan 27th Santa Barbara Invite 2019
56 California-San Diego Win 10-9 1717.76 Feb 16th Presidents Day Invite 2019
45 California-Santa Barbara Win 9-5 2192.31 Feb 16th Presidents Day Invite 2019
76 Utah** Win 10-3 2073.73 Ignored Feb 17th Presidents Day Invite 2019
34 UCLA Win 10-4 2328.73 Feb 17th Presidents Day Invite 2019
21 California Win 10-4 2443.46 Feb 18th Presidents Day Invite 2019
3 Oregon Win 10-9 2313.99 Feb 18th Presidents Day Invite 2019
17 Minnesota Win 10-7 2340.71 Mar 2nd Stanford Invite 2019
8 Colorado Win 11-10 2220.44 Mar 2nd Stanford Invite 2019
12 Texas Loss 10-13 1681.76 Mar 2nd Stanford Invite 2019
2 Brown Loss 10-12 1991.03 Mar 3rd Stanford Invite 2019
30 Victoria Win 13-7 2323.43 Mar 3rd Stanford Invite 2019
3 Oregon Win 13-12 2313.99 Mar 3rd Stanford Invite 2019
42 British Columbia Win 13-6 2273.61 Mar 23rd 2019 NW Challenge Mens Tier 1
58 Whitman Win 13-7 2137.18 Mar 23rd 2019 NW Challenge Mens Tier 1
51 Western Washington Win 13-5 2229.76 Mar 23rd 2019 NW Challenge Mens Tier 1
50 Stanford Win 12-10 1870.86 Mar 24th 2019 NW Challenge Mens Tier 1
30 Victoria Win 13-8 2262.06 Mar 24th 2019 NW Challenge Mens Tier 1
10 Washington Win 13-9 2463.07 Mar 24th 2019 NW Challenge Mens Tier 1
59 Oregon State Win 13-8 2058.35 Mar 25th 2019 NW Challenge Mens Tier 1
6 Brigham Young Loss 9-13 1716.17 Mar 25th 2019 NW Challenge Mens Tier 1
**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)