#58 Brown (6-11)

avg: 1667.49  •  sd: 46.87  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
23 Pennsylvania Loss 7-10 1856.18 Feb 22nd 2025 Commonwealth Cup Weekend 2
19 Notre Dame Loss 5-10 1712.19 Feb 22nd 2025 Commonwealth Cup Weekend 2
20 Virginia Loss 6-12 1689.62 Feb 22nd 2025 Commonwealth Cup Weekend 2
34 Ohio Loss 4-10 1358.56 Feb 23rd 2025 Commonwealth Cup Weekend 2
36 MIT Loss 8-9 1774.22 Feb 23rd 2025 Commonwealth Cup Weekend 2
32 Georgetown Loss 5-11 1407.01 Feb 23rd 2025 Commonwealth Cup Weekend 2
13 Stanford** Loss 4-13 1875.08 Ignored Mar 1st Stanford Invite 2025 Womens
14 Cal Poly-SLO** Loss 4-13 1843.09 Ignored Mar 1st Stanford Invite 2025 Womens
30 Wisconsin Loss 6-8 1722.48 Mar 1st Stanford Invite 2025 Womens
68 Santa Clara Loss 7-8 1462.55 Mar 2nd Stanford Invite 2025 Womens
46 Texas-Dallas Loss 5-9 1293.22 Mar 2nd Stanford Invite 2025 Womens
145 Boston College** Win 13-0 1586.95 Ignored Mar 22nd Jersey Devil 2025
144 RIT Win 13-6 1598.58 Mar 22nd Jersey Devil 2025
117 Swarthmore Win 13-4 1795.07 Mar 22nd Jersey Devil 2025
95 Williams Win 8-4 1903.43 Mar 22nd Jersey Devil 2025
145 Boston College** Win 12-1 1586.95 Ignored Mar 23rd Jersey Devil 2025
95 Williams Win 15-6 1938.62 Mar 23rd Jersey Devil 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)