#207 Colby (11-9)

avg: 795.22  •  sd: 56.04  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
120 Army Loss 5-10 586.68 Feb 24th Bring The Huckus 2024
197 Haverford Win 10-8 1098.85 Feb 24th Bring The Huckus 2024
247 SUNY-Geneseo Win 10-9 762.5 Feb 24th Bring The Huckus 2024
100 Vermont-B Loss 3-13 635.55 Feb 24th Bring The Huckus 2024
252 Dickinson Win 15-10 1064.03 Feb 25th Bring The Huckus 2024
187 Salisbury Win 15-10 1317.28 Feb 25th Bring The Huckus 2024
100 Vermont-B Loss 8-15 670.74 Feb 25th Bring The Huckus 2024
251 Amherst Win 14-13 737.26 Mar 2nd Grand Northeast Kickoff
62 Massachusetts -B** Loss 3-15 831.78 Ignored Mar 2nd Grand Northeast Kickoff
138 Tufts-B Loss 9-15 569.36 Mar 2nd Grand Northeast Kickoff
251 Amherst Win 14-12 833.22 Mar 3rd Grand Northeast Kickoff
269 Western New England Win 15-12 812.82 Mar 3rd Grand Northeast Kickoff
240 Middlebury-B Win 14-10 1070.43 Mar 3rd Grand Northeast Kickoff
251 Amherst Win 10-5 1186.16 Mar 30th New England Open 2024 Open Division
86 Bates Loss 4-9 717.07 Mar 30th New England Open 2024 Open Division
295 Harvard-B Win 8-6 670.07 Mar 30th New England Open 2024 Open Division
182 Worcester Polytechnic Institute Loss 2-9 290.83 Mar 30th New England Open 2024 Open Division
141 Bryant Loss 5-13 474.31 Mar 31st New England Open 2024 Open Division
138 Tufts-B Loss 6-9 666.27 Mar 31st New England Open 2024 Open Division
181 Northeastern-B Win 8-7 1023.07 Mar 31st New England Open 2024 Open Division
**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)