#83 SUNY-Buffalo (12-6)

avg: 1320.93  •  sd: 98.32  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
157 Johns Hopkins Loss 5-9 476.78 Mar 1st Oak Creek Challenge 2025
113 Lehigh Loss 5-10 630.34 Mar 1st Oak Creek Challenge 2025
132 Rutgers Loss 1-10 516.55 Mar 1st Oak Creek Challenge 2025
105 Liberty Loss 7-8 1107.91 Mar 2nd Oak Creek Challenge 2025
226 SUNY-Albany Win 10-7 1086.74 Mar 2nd Oak Creek Challenge 2025
153 Carleton University Win 13-8 1541.72 Mar 22nd Salt City Classic
24 Ottawa Loss 7-13 1276.31 Mar 22nd Salt City Classic
151 Rhode Island Win 11-10 1176.19 Mar 22nd Salt City Classic
102 Syracuse Win 11-9 1509.6 Mar 22nd Salt City Classic
80 Rochester Loss 10-12 1102.37 Mar 23rd Salt City Classic
73 Williams Win 12-11 1510.1 Mar 23rd Salt City Classic
98 Boston College Win 11-10 1396.7 Mar 29th East Coast Invite 2025
157 Johns Hopkins Win 10-7 1395.51 Mar 29th East Coast Invite 2025
236 NYU Win 12-6 1228.84 Mar 29th East Coast Invite 2025
116 West Chester Win 13-7 1749.7 Mar 29th East Coast Invite 2025
71 Case Western Reserve Win 9-8 1530.06 Mar 30th East Coast Invite 2025
102 Syracuse Win 12-6 1839.7 Mar 30th East Coast Invite 2025
48 Maryland Win 8-5 2019.27 Mar 30th East Coast Invite 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)