#100 Vermont-B (15-4)

avg: 1235.55  •  sd: 44.46  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
141 Bryant Win 8-5 1527.92 Feb 10th UMass Invite 2024
270 Rowan** Win 13-5 1111.96 Ignored Feb 10th UMass Invite 2024
162 Wesleyan Win 10-7 1375.31 Feb 10th UMass Invite 2024
46 Williams Loss 8-9 1399.96 Feb 10th UMass Invite 2024
183 Connecticut College Win 15-4 1488.7 Feb 11th UMass Invite 2024
62 Massachusetts -B Loss 8-11 1066.17 Feb 11th UMass Invite 2024
148 Rochester Win 10-7 1426.48 Feb 11th UMass Invite 2024
120 Army Win 12-11 1285.57 Feb 24th Bring The Huckus 2024
207 Colby Win 13-3 1395.22 Feb 24th Bring The Huckus 2024
197 Haverford Win 13-1 1436.18 Feb 24th Bring The Huckus 2024
247 SUNY-Geneseo Win 13-4 1237.5 Feb 24th Bring The Huckus 2024
207 Colby Win 15-8 1360.03 Feb 25th Bring The Huckus 2024
197 Haverford Win 13-7 1393.72 Feb 25th Bring The Huckus 2024
277 Stevens Tech Win 15-7 1097.45 Feb 25th Bring The Huckus 2024
147 SUNY-Cortland Win 9-7 1327.82 Mar 30th Northeast Classic 2024
162 Wesleyan Win 9-8 1110.64 Mar 30th Northeast Classic 2024
127 College of New Jersey Loss 9-11 895.22 Mar 31st Northeast Classic 2024
233 Skidmore Win 10-8 967.18 Mar 31st Northeast Classic 2024
147 SUNY-Cortland Loss 10-11 923.48 Mar 31st Northeast Classic 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)