#127 SUNY-Stony Brook (8-4)

avg: 1007.41  •  sd: 125.13  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
233 SUNY Cortland Win 8-6 579.31 Mar 9th No Sleep Till Brooklyn
159 SUNY-Albany Loss 6-7 699.44 Mar 9th No Sleep Till Brooklyn
130 Connecticut Loss 4-7 496.29 Mar 9th No Sleep Till Brooklyn
33 Bates** Loss 1-13 1106.49 Ignored Mar 9th No Sleep Till Brooklyn
171 NYU Win 9-3 1335.1 Mar 10th No Sleep Till Brooklyn
183 Marist Win 7-4 1122.32 Mar 10th No Sleep Till Brooklyn
282 Boston University-B** Win 13-0 162.79 Ignored Mar 30th Strong Island Invitational 2019
100 Wellesley Loss 7-9 847.02 Mar 30th Strong Island Invitational 2019
253 Wellesley-B** Win 9-3 719.54 Ignored Mar 30th Strong Island Invitational 2019
132 Boston University Win 7-6 1104.62 Mar 31st Strong Island Invitational 2019
268 Hofstra** Win 12-0 484.49 Ignored Mar 31st Strong Island Invitational 2019
100 Wellesley Win 10-5 1700.25 Mar 31st Strong Island Invitational 2019
**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)