#312 Western New England (4-16)

avg: 673.67  •  sd: 65.08  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
279 Amherst Loss 12-15 535.02 Mar 2nd Grand Northeast Kickoff
76 Massachusetts -B** Loss 3-15 1010.5 Ignored Mar 2nd Grand Northeast Kickoff
218 Middlebury-B Loss 7-15 454.71 Mar 2nd Grand Northeast Kickoff
225 Colby Loss 12-15 735.19 Mar 3rd Grand Northeast Kickoff
218 Middlebury-B Loss 11-13 825.87 Mar 3rd Grand Northeast Kickoff
138 Tufts-B Loss 8-15 798.93 Mar 3rd Grand Northeast Kickoff
259 Brandeis Loss 9-10 789.93 Mar 30th New England Open 2024 Open Division
343 Connecticut-B Win 10-6 1045.49 Mar 30th New England Open 2024 Open Division
210 Northeastern-B Loss 2-11 480.66 Mar 30th New England Open 2024 Open Division
138 Tufts-B Loss 5-10 789.84 Mar 30th New England Open 2024 Open Division
279 Amherst Win 10-8 1098.18 Mar 31st New England Open 2024 Open Division
199 Connecticut College Loss 4-13 525.75 Mar 31st New England Open 2024 Open Division
329 Harvard-B Win 13-10 928.3 Mar 31st New England Open 2024 Open Division
279 Amherst Loss 4-12 235.51 Apr 13th South New England D III Mens Conferences 2024
142 Bryant** Loss 5-13 740.78 Ignored Apr 13th South New England D III Mens Conferences 2024
341 Holy Cross Loss 7-10 165.32 Apr 13th South New England D III Mens Conferences 2024
55 Williams** Loss 5-15 1149.57 Ignored Apr 13th South New England D III Mens Conferences 2024
279 Amherst Loss 9-11 586.3 Apr 14th South New England D III Mens Conferences 2024
341 Holy Cross Win 14-5 1154.98 Apr 14th South New England D III Mens Conferences 2024
238 Roger Williams Loss 4-15 389.45 Apr 14th South New England D III Mens Conferences 2024
**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)