#162 Colby (4-10)

avg: 659.76  •  sd: 75.18  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
104 Yale Loss 2-5 440.63 Mar 1st Garden State 2025
235 Cornell-B Win 6-2 720.28 Mar 1st Garden State 2025
93 NYU Loss 2-5 511.44 Mar 1st Garden State 2025
138 Massachusetts Loss 3-5 379.55 Mar 2nd Garden State 2025
56 Rochester** Loss 1-8 821.56 Ignored Mar 2nd Garden State 2025
174 New Hampshire Loss 3-4 456.82 Mar 2nd Garden State 2025
158 Bates Win 8-7 796.71 Mar 9th Too Hot to Handle
48 McGill** Loss 3-13 908.46 Ignored Mar 9th Too Hot to Handle
174 New Hampshire Win 8-4 1146.63 Mar 9th Too Hot to Handle
86 Wellesley Loss 6-10 647.55 Mar 9th Too Hot to Handle
158 Bates Win 8-5 1125.31 Apr 12th North New England D III Womens Conferences 2025
137 Bowdoin Loss 6-7 679.27 Apr 12th North New England D III Womens Conferences 2025
149 Dartmouth Loss 3-8 108.35 Apr 12th North New England D III Womens Conferences 2025
51 Middlebury** Loss 2-8 881.55 Ignored Apr 12th North New England D III Womens Conferences 2025
**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)