#177 Rochester (10-9)

avg: 1040.19  •  sd: 83.42  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
80 Connecticut College Loss 9-13 1053.7 Feb 25th Bring The Huckus1
170 Ithaca Win 13-4 1678.23 Feb 25th Bring The Huckus1
245 SUNY-Albany Win 11-4 1349.92 Feb 25th Bring The Huckus1
205 SUNY-Cortland Win 10-7 1318.04 Feb 25th Bring The Huckus1
80 Connecticut College Loss 8-15 907.46 Feb 26th Bring The Huckus1
165 Penn State-B Win 7-6 1223.45 Feb 26th Bring The Huckus1
205 SUNY-Cortland Win 12-4 1528.38 Feb 26th Bring The Huckus1
37 McGill** Loss 6-15 1173.37 Ignored Mar 25th Carousel City Classic
70 Lehigh Loss 4-12 926.73 Mar 25th Carousel City Classic
62 Harvard Loss 7-13 1011.37 Mar 25th Carousel City Classic
134 Carnegie Mellon Win 10-9 1361.31 Mar 26th Carousel City Classic
176 Syracuse Win 11-7 1514.68 Mar 26th Carousel City Classic
153 Columbia Win 11-10 1265.62 Mar 26th Carousel City Classic
355 Case Western Reserve-B** Win 10-2 551.98 Ignored Apr 1st 2023 B team Brodown
173 Pittsburgh-B Loss 8-12 620.15 Apr 1st 2023 B team Brodown
350 SUNY-Fredonia Win 8-5 491.76 Apr 1st 2023 B team Brodown
130 Messiah Loss 5-15 652.29 Apr 2nd 2023 B team Brodown
126 Franciscan Loss 3-15 667.6 Apr 2nd 2023 B team Brodown
261 Ohio State Loss 8-9 563.78 Apr 2nd 2023 B team Brodown
**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)