#97 SUNY-Buffalo (14-11)

avg: 1474.63  •  sd: 78.42  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
154 Johns Hopkins Loss 5-9 727.28 Mar 1st Oak Creek Challenge 2025
94 Lehigh Loss 5-10 906.92 Mar 1st Oak Creek Challenge 2025
149 Rutgers Loss 1-10 678.67 Mar 1st Oak Creek Challenge 2025
112 Liberty Loss 7-8 1280.59 Mar 2nd Oak Creek Challenge 2025
212 SUNY-Albany Win 10-7 1413.11 Mar 2nd Oak Creek Challenge 2025
182 Carleton University Win 13-8 1649.35 Mar 22nd Salt City Classic
30 Ottawa Loss 7-13 1315.35 Mar 22nd Salt City Classic
152 Rhode Island Win 11-10 1393.42 Mar 22nd Salt City Classic
99 Syracuse Win 11-9 1717.66 Mar 22nd Salt City Classic
81 Rochester Loss 10-12 1317 Mar 23rd Salt City Classic
76 Williams Win 12-11 1717.52 Mar 23rd Salt City Classic
85 Boston College Win 11-10 1641.2 Mar 29th East Coast Invite 2025
154 Johns Hopkins Win 10-7 1646 Mar 29th East Coast Invite 2025
248 NYU Win 12-6 1467.33 Mar 29th East Coast Invite 2025
113 West Chester Win 13-7 1950.17 Mar 29th East Coast Invite 2025
80 Case Western Reserve Win 9-8 1687.39 Mar 30th East Coast Invite 2025
99 Syracuse Win 12-6 2047.77 Mar 30th East Coast Invite 2025
55 Maryland Win 8-5 2148.67 Mar 30th East Coast Invite 2025
30 Ottawa Loss 7-15 1272.88 Apr 12th Western NY D I Mens Conferences 2025
115 RIT Loss 12-13 1259.22 Apr 12th Western NY D I Mens Conferences 2025
147 Toronto Win 12-10 1518.23 Apr 12th Western NY D I Mens Conferences 2025
99 Syracuse Win 15-4 2068.46 Apr 12th Western NY D I Mens Conferences 2025
30 Ottawa Loss 7-9 1593.54 Apr 13th Western NY D I Mens Conferences 2025
147 Toronto Loss 8-10 1017.44 Apr 13th Western NY D I Mens Conferences 2025
99 Syracuse Loss 6-11 921.76 Apr 13th Western NY D I Mens Conferences 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)