#152 Rhode Island (14-10)

avg: 1268.42  •  sd: 61.02  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
95 Bowdoin Win 9-8 1605.17 Mar 1st Garden State 2025
262 Brown-B Win 9-4 1429 Mar 1st Garden State 2025
197 Haverford Win 9-4 1678.47 Mar 1st Garden State 2025
210 Penn State-B Win 5-2 1627.54 Mar 1st Garden State 2025
352 Army** Win 13-4 1017.21 Ignored Mar 2nd Garden State 2025
95 Bowdoin Loss 6-11 933.48 Mar 2nd Garden State 2025
210 Penn State-B Win 10-7 1417.2 Mar 2nd Garden State 2025
182 Carleton University Win 13-10 1481.33 Mar 22nd Salt City Classic
30 Ottawa Loss 6-13 1272.88 Mar 22nd Salt City Classic
97 SUNY-Buffalo Loss 10-11 1349.63 Mar 22nd Salt City Classic
99 Syracuse Loss 7-12 947.95 Mar 22nd Salt City Classic
182 Carleton University Loss 7-15 553.19 Mar 23rd Salt City Classic
347 Rensselaer Polytech Win 12-7 981.79 Mar 23rd Salt City Classic
99 Syracuse Win 9-8 1593.46 Mar 23rd Salt City Classic
347 Rensselaer Polytech** Win 10-4 1061.28 Ignored Mar 29th Ocean State Invite 2025
287 Roger Williams Win 9-5 1277.87 Mar 29th Ocean State Invite 2025
134 Maine Loss 10-11 1199.57 Mar 29th Ocean State Invite 2025
206 Tufts-B Win 12-8 1483.46 Mar 30th Ocean State Invite 2025
134 Maine Loss 6-11 777.87 Mar 30th Ocean State Invite 2025
17 Brown** Loss 6-15 1455.26 Ignored Apr 12th Greater New England D I Mens Conferences 2025
385 New Hampshire** Win 15-3 802.59 Ignored Apr 12th Greater New England D I Mens Conferences 2025
20 Vermont** Loss 3-15 1428.48 Ignored Apr 12th Greater New England D I Mens Conferences 2025
37 McGill Loss 8-12 1377.08 Apr 13th Greater New England D I Mens Conferences 2025
134 Maine Win 11-10 1449.57 Apr 13th Greater New England D I Mens Conferences 2025
**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)