#401 Siena (0-13)

avg: 39.98  •  sd: 119.01  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
188 Brown-B** Loss 2-11 563.41 Ignored Mar 2nd Philly Special 2024
272 Rowan** Loss 0-7 256.78 Ignored Mar 2nd Philly Special 2024
397 SUNY-Albany-B Loss 3-9 -507.21 Mar 2nd Philly Special 2024
359 Bentley Loss 3-15 -146.04 Mar 3rd Philly Special 2024
343 Connecticut-B Loss 3-15 -50.67 Mar 3rd Philly Special 2024
397 SUNY-Albany-B Loss 8-15 -472.01 Mar 3rd Philly Special 2024
244 Dickinson** Loss 1-13 379.09 Ignored Mar 23rd King of New York 2024
374 New Jersey Tech Loss 6-8 23.21 Mar 24th King of New York 2024
327 SUNY-Binghamton-B Loss 7-9 334.88 Mar 24th King of New York 2024
181 SUNY-Cortland Loss 8-11 827.6 Mar 24th King of New York 2024
136 Wesleyan** Loss 1-13 768.91 Ignored Apr 13th Hudson Valley D III Mens Conferences 2024
- Union (New York) Loss 9-10 39.97 Apr 13th Hudson Valley D III Mens Conferences 2024
245 Skidmore** Loss 1-13 378.07 Ignored Apr 14th Hudson Valley D III Mens Conferences 2024
**Blowout Eligible

FAQ

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
  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
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)