#62 Massachusetts -B (16-3)

avg: 1431.78  •  sd: 53.73  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
183 Connecticut College Win 10-9 1013.7 Feb 10th UMass Invite 2024
153 Rhode Island Win 10-8 1289.07 Feb 10th UMass Invite 2024
148 Rochester Win 12-7 1557.32 Feb 10th UMass Invite 2024
146 Yale Win 11-5 1660.05 Feb 10th UMass Invite 2024
141 Bryant Win 13-5 1674.31 Feb 11th UMass Invite 2024
100 Vermont-B Win 11-8 1601.15 Feb 11th UMass Invite 2024
46 Williams Loss 11-13 1296.12 Feb 11th UMass Invite 2024
207 Colby** Win 15-3 1395.22 Ignored Mar 2nd Grand Northeast Kickoff
269 Western New England** Win 15-3 1112.32 Ignored Mar 2nd Grand Northeast Kickoff
240 Middlebury-B** Win 11-1 1271.72 Ignored Mar 2nd Grand Northeast Kickoff
251 Amherst** Win 15-3 1212.26 Ignored Mar 3rd Grand Northeast Kickoff
138 Tufts-B Win 15-7 1684.84 Mar 3rd Grand Northeast Kickoff
138 Tufts-B Win 15-8 1649.65 Mar 3rd Grand Northeast Kickoff
224 American** Win 15-4 1331.75 Ignored Mar 30th Atlantic Coast Open 2024
252 Dickinson** Win 15-5 1210.43 Ignored Mar 30th Atlantic Coast Open 2024
58 Maryland Loss 12-14 1222.01 Mar 30th Atlantic Coast Open 2024
60 Temple Win 12-10 1673.15 Mar 30th Atlantic Coast Open 2024
97 Florida State Win 15-13 1461.95 Mar 31st Atlantic Coast Open 2024
52 Virginia Tech Loss 9-15 960.04 Mar 31st Atlantic Coast Open 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)