#167 SUNY-Buffalo (5-1)

avg: 971.45  •  sd: 155.59  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
280 College of New Jersey Win 13-1 1048.66 Mar 7th The Culture 2020
180 SUNY-Albany Win 11-5 1521.58 Mar 7th The Culture 2020
320 Delaware-B Win 9-6 615.77 Mar 7th The Culture 2020
183 Yale Win 11-7 1378.05 Mar 7th The Culture 2020
296 Slippery Rock Win 12-11 484.94 Mar 8th The Culture 2020
183 Yale Loss 8-9 786.15 Mar 8th The Culture 2020
**Blowout Eligible


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
  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
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)