#71 Connecticut College (12-2)

avg: 1351.59  •  sd: 88.44  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
195 Amherst Win 10-5 1329.88 Feb 11th UMass Invite 2023
313 Harvard-B** Win 10-1 685.19 Ignored Feb 11th UMass Invite 2023
92 Vermont-B Win 10-6 1737.73 Feb 11th UMass Invite 2023
139 Wesleyan Win 10-8 1277.13 Feb 11th UMass Invite 2023
165 Tufts-B Win 13-8 1410.78 Feb 12th UMass Invite 2023
139 Wesleyan Win 15-8 1579.27 Feb 12th UMass Invite 2023
92 Vermont-B Loss 11-13 1012.73 Feb 12th UMass Invite 2023
247 SUNY-Albany Win 13-7 1066.83 Feb 25th Bring The Huckus1
119 Rochester Win 13-9 1509.1 Feb 25th Bring The Huckus1
167 SUNY-Cortland Win 13-12 1021.63 Feb 25th Bring The Huckus1
159 Ithaca Loss 9-10 803.89 Feb 25th Bring The Huckus1
98 Massachusetts-B Win 15-9 1716.55 Feb 26th Bring The Huckus1
92 Vermont-B Win 10-8 1504.23 Feb 26th Bring The Huckus1
119 Rochester Win 15-8 1655.34 Feb 26th Bring The Huckus1
**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)