#240 SUNY-Albany (10-13)

avg: 987.78  •  sd: 61.69  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
259 Brandeis Win 7-3 1514.93 Mar 2nd Philly Special 2024
187 College of New Jersey Loss 1-3 563.42 Mar 2nd Philly Special 2024
115 Bowdoin Loss 7-11 970.04 Mar 3rd Philly Special 2024
259 Brandeis Win 10-8 1177.6 Mar 3rd Philly Special 2024
130 Penn State-B Loss 7-13 821.88 Mar 3rd Philly Special 2024
310 Stevens Tech Win 11-9 928.04 Mar 3rd Philly Special 2024
218 Middlebury-B Loss 7-10 665.04 Mar 30th Northeast Classic 2024
245 Skidmore Loss 7-10 588.41 Mar 30th Northeast Classic 2024
378 SUNY-Buffalo-B** Win 13-4 901.69 Ignored Mar 30th Northeast Classic 2024
218 Middlebury-B Loss 8-10 792.04 Mar 31st Northeast Classic 2024
315 Vermont-C Win 10-6 1156.72 Mar 31st Northeast Classic 2024
275 Central Connecticut State Win 9-5 1377.72 Apr 13th Hudson Valley D I Mens Conferences 2024
102 Connecticut Loss 1-13 895.12 Apr 13th Hudson Valley D I Mens Conferences 2024
379 Southern Connecticut State** Win 13-2 900.57 Ignored Apr 13th Hudson Valley D I Mens Conferences 2024
131 Yale Loss 3-13 779.37 Apr 13th Hudson Valley D I Mens Conferences 2024
275 Central Connecticut State Win 11-8 1214.27 Apr 14th Hudson Valley D I Mens Conferences 2024
131 Yale Win 11-10 1504.37 Apr 14th Hudson Valley D I Mens Conferences 2024
275 Central Connecticut State Loss 11-12 723.66 Apr 27th Metro East D I College Mens Regionals 2024
30 Ottawa** Loss 4-15 1340.68 Ignored Apr 27th Metro East D I College Mens Regionals 2024
166 RIT Win 13-11 1496.66 Apr 27th Metro East D I College Mens Regionals 2024
91 SUNY-Buffalo Loss 9-15 1028.27 Apr 27th Metro East D I College Mens Regionals 2024
102 Connecticut Loss 3-15 895.12 Apr 28th Metro East D I College Mens Regionals 2024
191 NYU Loss 8-15 592 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)