#31 California-Santa Barbara (19-21)

avg: 1861.88  •  sd: 34.46  •  top 16/20: 0.1%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
7 Brigham Young Loss 7-13 1688.63 Jan 24th Santa Barbara Invite 2025
7 Brigham Young Loss 7-13 1688.63 Jan 25th Santa Barbara Invite 2025
6 Cal Poly-SLO Loss 9-13 1849.41 Jan 25th Santa Barbara Invite 2025
41 California-San Diego Loss 11-12 1667.31 Jan 25th Santa Barbara Invite 2025
119 Cal Poly-SLO-B Win 13-5 1967.2 Jan 26th Santa Barbara Invite 2025
42 Colorado State Loss 3-4 1659.76 Jan 26th Santa Barbara Invite 2025
41 California-San Diego Win 7-5 2120.45 Feb 15th Presidents Day Invite 2025
2 Oregon Loss 6-11 1838.53 Feb 15th Presidents Day Invite 2025
11 Oregon State Loss 6-11 1589.04 Feb 15th Presidents Day Invite 2025
8 Washington Loss 10-13 1888.45 Feb 16th Presidents Day Invite 2025
9 California-Santa Cruz Loss 9-13 1766.57 Feb 16th Presidents Day Invite 2025
54 UCLA Loss 9-10 1579.08 Feb 16th Presidents Day Invite 2025
173 California-Davis Win 13-7 1739.89 Feb 17th Presidents Day Invite 2025
25 Victoria Loss 8-13 1462.69 Feb 17th Presidents Day Invite 2025
13 California Loss 8-13 1607.47 Mar 8th Stanford Invite 2025 Mens
23 Western Washington Loss 10-11 1863.28 Mar 8th Stanford Invite 2025 Mens
143 Wisconsin-Milwaukee Win 13-5 1888.58 Mar 8th Stanford Invite 2025 Mens
46 Stanford Loss 12-13 1640.36 Mar 8th Stanford Invite 2025 Mens
84 Southern California Win 13-10 1847.5 Mar 9th Stanford Invite 2025 Mens
43 Whitman Win 13-10 2111.75 Mar 9th Stanford Invite 2025 Mens
7 Brigham Young Loss 11-15 1865 Mar 22nd Northwest Challenge 2025 mens
44 Wisconsin Win 14-10 2175.93 Mar 22nd Northwest Challenge 2025 mens
138 Gonzaga Win 15-6 1913.2 Mar 22nd Northwest Challenge 2025 mens
23 Western Washington Loss 11-15 1607.11 Mar 23rd Northwest Challenge 2025 mens
9 California-Santa Cruz Loss 9-15 1669.66 Mar 23rd Northwest Challenge 2025 mens
32 Utah State Win 15-9 2367.64 Mar 23rd Northwest Challenge 2025 mens
216 Cal Poly-Pomona Win 13-6 1615.56 Apr 12th SoCal D I Mens Conferences 2025
54 UCLA Win 11-10 1829.08 Apr 12th SoCal D I Mens Conferences 2025
84 Southern California Win 12-8 1960.51 Apr 12th SoCal D I Mens Conferences 2025
237 Loyola Marymount** Win 13-4 1525.37 Ignored Apr 12th SoCal D I Mens Conferences 2025
6 Cal Poly-SLO Loss 12-15 1967.48 Apr 13th SoCal D I Mens Conferences 2025
41 California-San Diego Win 15-11 2173.48 Apr 13th SoCal D I Mens Conferences 2025
41 California-San Diego Win 12-7 2312.82 Apr 13th SoCal D I Mens Conferences 2025
173 California-Davis** Win 15-4 1782.36 Ignored Apr 26th Southwest D I College Mens Regionals 2025
41 California-San Diego Win 13-12 1917.31 Apr 26th Southwest D I College Mens Regionals 2025
9 California-Santa Cruz Loss 8-15 1620.33 Apr 26th Southwest D I College Mens Regionals 2025
46 Stanford Win 13-9 2183.93 Apr 26th Southwest D I College Mens Regionals 2025
6 Cal Poly-SLO Loss 6-15 1667.97 Apr 27th Southwest D I College Mens Regionals 2025
13 California Loss 11-13 1874.79 Apr 27th Southwest D I College Mens Regionals 2025
41 California-San Diego Win 14-13 1917.31 Apr 27th Southwest D I College Mens Regionals 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)