#91 SUNY-Buffalo (13-10)

avg: 1543.75  •  sd: 64.86  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
85 Cornell Win 13-1 2175.01 Mar 2nd Oak Creek Challenge 2024
289 Drexel** Win 13-2 1369.67 Ignored Mar 2nd Oak Creek Challenge 2024
148 Johns Hopkins Win 13-7 1872.65 Mar 2nd Oak Creek Challenge 2024
72 Appalachian State Loss 9-13 1210.09 Mar 3rd Oak Creek Challenge 2024
166 RIT Win 12-10 1505.95 Mar 3rd Oak Creek Challenge 2024
126 Towson Win 11-10 1514.09 Mar 3rd Oak Creek Challenge 2024
54 Emory Loss 11-12 1630.32 Mar 30th Atlantic Coast Open 2024
44 Virginia Tech Loss 11-12 1689.41 Mar 30th Atlantic Coast Open 2024
56 Temple Loss 8-15 1178.86 Mar 30th Atlantic Coast Open 2024
44 Virginia Tech Loss 7-13 1256.87 Mar 30th Atlantic Coast Open 2024
127 Pittsburgh-B Win 15-9 1904.21 Mar 31st Atlantic Coast Open 2024
56 Temple Loss 12-13 1618.67 Mar 31st Atlantic Coast Open 2024
208 Carleton University Win 15-2 1687.53 Apr 20th Western NY D I Mens Conferences 2024
85 Cornell Loss 9-10 1450.01 Apr 20th Western NY D I Mens Conferences 2024
166 RIT Win 10-8 1530.49 Apr 20th Western NY D I Mens Conferences 2024
103 SUNY-Binghamton Win 9-8 1616.64 Apr 21st Western NY D I Mens Conferences 2024
120 Syracuse Win 13-7 1960.8 Apr 21st Western NY D I Mens Conferences 2024
93 Princeton Loss 13-14 1413.03 Apr 27th Metro East D I College Mens Regionals 2024
240 SUNY-Albany Win 15-9 1503.26 Apr 27th Metro East D I College Mens Regionals 2024
327 SUNY-Binghamton-B** Win 15-3 1214.21 Ignored Apr 27th Metro East D I College Mens Regionals 2024
131 Yale Win 15-7 1979.37 Apr 27th Metro East D I College Mens Regionals 2024
85 Cornell Loss 10-15 1121.41 Apr 28th Metro East D I College Mens Regionals 2024
131 Yale Loss 8-14 843.34 Apr 28th Metro East D I College Mens Regionals 2024
**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)