#51 Middlebury (20-2)

avg: 1481.68  •  sd: 70.6  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
104 Amherst Win 9-3 1640.3 Mar 2nd Bam Bam Bonanza
190 Brandeis** Win 13-0 1088.54 Ignored Mar 2nd Bam Bam Bonanza
86 Vermont-B Win 8-3 1739.79 Mar 2nd Bam Bam Bonanza
59 Central Florida Loss 7-9 1117.74 Mar 15th Tally Classic XIX
172 Florida State** Win 14-4 1199.77 Ignored Mar 15th Tally Classic XIX
124 Jacksonville State Win 7-5 1213.89 Mar 15th Tally Classic XIX
136 Massachusetts** Win 13-2 1398.22 Ignored Mar 29th Northeast Classic 2025
112 SUNY-Binghamton Win 10-4 1570.18 Mar 29th Northeast Classic 2025
85 Wellesley Win 8-6 1444.34 Mar 29th Northeast Classic 2025
56 Rochester Win 11-8 1787.35 Mar 29th Northeast Classic 2025
104 Amherst Win 13-8 1536.46 Mar 30th Northeast Classic 2025
86 Vermont-B Win 13-8 1635.95 Mar 30th Northeast Classic 2025
56 Rochester Win 13-3 2021.74 Mar 30th Northeast Classic 2025
157 Bates** Win 11-2 1271.73 Ignored Apr 12th North New England D III Womens Conferences 2025
134 Bowdoin Loss 9-11 555.07 Apr 12th North New England D III Womens Conferences 2025
161 Colby** Win 8-2 1259.88 Ignored Apr 12th North New England D III Womens Conferences 2025
148 Dartmouth Win 8-6 1008.93 Apr 12th North New England D III Womens Conferences 2025
104 Amherst Win 13-7 1597.83 Apr 26th New England D III College Womens Regionals 2025
190 Brandeis** Win 15-1 1088.54 Ignored Apr 26th New England D III College Womens Regionals 2025
148 Dartmouth** Win 15-3 1308.43 Ignored Apr 26th New England D III College Womens Regionals 2025
75 Mount Holyoke Win 10-6 1718.96 Apr 26th New England D III College Womens Regionals 2025
89 Williams Win 12-7 1639.25 Apr 27th New England D III College Womens Regionals 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)