#275 Central Connecticut State (11-13)

avg: 848.66  •  sd: 72.16  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
327 SUNY-Binghamton-B Win 8-4 1179.02 Feb 24th Bring The Huckus 2024
318 Swarthmore Win 8-3 1255.47 Feb 24th Bring The Huckus 2024
331 Rutgers-B Win 9-5 1125.34 Feb 24th Bring The Huckus 2024
244 Dickinson Loss 4-8 414.29 Feb 24th Bring The Huckus 2024
245 Skidmore Win 15-6 1578.07 Feb 25th Bring The Huckus 2024
210 Northeastern-B Loss 5-7 752.52 Mar 23rd Ocean State Invite
189 Worcester Polytechnic Institute Win 7-6 1284.5 Mar 23rd Ocean State Invite
297 Massachusetts-Lowell Win 11-4 1329.5 Mar 23rd Ocean State Invite
159 Rhode Island Loss 3-8 688.15 Mar 23rd Ocean State Invite
331 Rutgers-B Win 13-3 1196.28 Mar 24th Ocean State Invite
159 Rhode Island Loss 7-8 1163.15 Mar 24th Ocean State Invite
317 Northeastern-C Loss 6-9 237.25 Mar 24th Ocean State Invite
131 Yale Loss 6-13 779.37 Apr 13th Hudson Valley D I Mens Conferences 2024
102 Connecticut** Loss 2-13 895.12 Ignored Apr 13th Hudson Valley D I Mens Conferences 2024
240 SUNY-Albany Loss 5-9 458.72 Apr 13th Hudson Valley D I Mens Conferences 2024
379 Southern Connecticut State Win 13-8 796.73 Apr 14th Hudson Valley D I Mens Conferences 2024
240 SUNY-Albany Loss 8-11 622.17 Apr 14th Hudson Valley D I Mens Conferences 2024
379 Southern Connecticut State Win 15-6 900.57 Apr 14th Hudson Valley D I Mens Conferences 2024
240 SUNY-Albany Win 12-11 1112.78 Apr 27th Metro East D I College Mens Regionals 2024
30 Ottawa** Loss 2-15 1340.68 Ignored Apr 27th Metro East D I College Mens Regionals 2024
166 RIT Loss 8-15 703.01 Apr 27th Metro East D I College Mens Regionals 2024
283 Hofstra Loss 13-14 684.27 Apr 28th Metro East D I College Mens Regionals 2024
327 SUNY-Binghamton-B Win 10-9 739.21 Apr 28th Metro East D I College Mens Regionals 2024
272 Rowan Loss 6-11 310.09 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)