#181 SUNY-Cortland (15-5)

avg: 1193.21  •  sd: 90.51  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
284 Marist Win 13-4 1409.2 Mar 23rd King of New York 2024
345 Cornell-B Win 8-7 659.1 Mar 24th King of New York 2024
213 Ithaca Win 6-5 1200.64 Mar 24th King of New York 2024
401 Siena Win 11-8 405.59 Mar 24th King of New York 2024
187 College of New Jersey Win 8-5 1617.03 Mar 30th Northeast Classic 2024
136 Wesleyan Loss 8-9 1243.91 Mar 30th Northeast Classic 2024
108 Vermont-B Loss 7-9 1195.69 Mar 30th Northeast Classic 2024
213 Ithaca Win 9-8 1200.64 Mar 31st Northeast Classic 2024
108 Vermont-B Win 11-10 1600.03 Mar 31st Northeast Classic 2024
136 Wesleyan Win 12-8 1810.06 Mar 31st Northeast Classic 2024
249 Colgate Win 11-5 1560.22 Apr 20th Western NY D III Mens Conferences 2024
376 SUNY-Fredonia** Win 10-2 908.89 Ignored Apr 20th Western NY D III Mens Conferences 2024
267 SUNY-Geneseo Win 11-4 1471.49 Apr 20th Western NY D III Mens Conferences 2024
326 SUNY-Oneonta Win 10-7 1005.28 Apr 20th Western NY D III Mens Conferences 2024
213 Ithaca Win 11-10 1200.64 Apr 21st Western NY D III Mens Conferences 2024
117 Rochester Loss 6-15 827.33 Apr 21st Western NY D III Mens Conferences 2024
139 Army Win 16-10 1844.51 Apr 27th Metro East D III College Mens Regionals 2024
310 Stevens Tech Win 17-10 1207.89 Apr 27th Metro East D III College Mens Regionals 2024
252 Hamilton Loss 11-15 549.68 Apr 28th Metro East D III College Mens Regionals 2024
245 Skidmore Loss 5-7 649.93 Apr 28th Metro East D III 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)