#251 Amherst (4-8)

avg: 612.26  •  sd: 88.05  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
138 Tufts-B Loss 9-15 569.36 Mar 2nd Grand Northeast Kickoff
207 Colby Loss 13-14 670.22 Mar 2nd Grand Northeast Kickoff
269 Western New England Win 15-12 812.82 Mar 2nd Grand Northeast Kickoff
240 Middlebury-B Win 15-9 1187.21 Mar 3rd Grand Northeast Kickoff
62 Massachusetts -B** Loss 3-15 831.78 Ignored Mar 3rd Grand Northeast Kickoff
207 Colby Loss 12-14 574.26 Mar 3rd Grand Northeast Kickoff
103 Bowdoin** Loss 3-13 616 Ignored Mar 30th New England Open 2024 Open Division
266 Maine Win 9-3 1133.76 Mar 30th New England Open 2024 Open Division
365 New Hampshire** Win 11-4 532.19 Ignored Mar 30th New England Open 2024 Open Division
207 Colby Loss 5-10 221.32 Mar 30th New England Open 2024 Open Division
266 Maine Loss 7-9 254.43 Mar 31st New England Open 2024 Open Division
269 Western New England Loss 8-10 249.66 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)