#140 Santa Clara (4-7)

avg: 1076.39  •  sd: 67.81  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
191 Cal Poly-Pomona Win 13-7 1413.21 Feb 1st Pres Day Quals men
280 California-Santa Barbara-B** Win 12-5 1064.59 Ignored Feb 1st Pres Day Quals men
85 Southern California Loss 5-13 717.15 Feb 1st Pres Day Quals men
42 Stanford Loss 5-13 1017.36 Feb 2nd Pres Day Quals men
208 UCLA-B Win 11-7 1232.19 Feb 2nd Pres Day Quals men
12 British Columbia** Loss 2-13 1371.97 Ignored Mar 8th Stanford Invite 2025 Mens
14 California Loss 6-13 1369.23 Mar 8th Stanford Invite 2025 Mens
141 Northwestern Win 10-9 1197.86 Mar 8th Stanford Invite 2025 Mens
42 Stanford Loss 6-13 1017.36 Mar 8th Stanford Invite 2025 Mens
53 Whitman Loss 6-13 948.29 Mar 9th Stanford Invite 2025 Mens
85 Southern California Loss 7-12 796.64 Mar 9th Stanford Invite 2025 Mens
**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)