#85 Haverford/Bryn Mawr (9-6)

avg: 1184.08  •  sd: 91.65  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
116 SUNY-Geneseo Loss 5-6 862.55 Feb 22nd Bring The Huckus 10 2020
43 West Chester Loss 7-9 1263.22 Feb 22nd Bring The Huckus 10 2020
41 Skidmore Loss 5-9 1015.46 Feb 22nd Bring The Huckus 10 2020
102 NYU Win 11-5 1656.49 Feb 22nd Bring The Huckus 10 2020
221 Ithaca** Win 13-4 619.11 Ignored Feb 23rd Bring The Huckus 10 2020
108 Wesleyan Win 9-7 1312.99 Feb 23rd Bring The Huckus 10 2020
41 Skidmore Loss 7-11 1077.62 Feb 23rd Bring The Huckus 10 2020
123 Swarthmore Win 10-3 1516.06 Feb 23rd Bring The Huckus 10 2020
155 Vermont-B Win 9-4 1256.74 Mar 7th Mash Up 2020
65 Liberty Win 9-7 1593.57 Mar 7th Mash Up 2020
231 RIT** Win 11-1 463.86 Ignored Mar 7th Mash Up 2020
194 SUNY-Fredonia** Win 12-4 917.47 Ignored Mar 8th Mash Up 2020
170 Rhode Island Win 12-6 1108.15 Mar 8th Mash Up 2020
110 Cincinnati Loss 8-9 897.65 Mar 8th Mash Up 2020
65 Liberty Loss 6-13 714.23 Mar 8th Mash Up 2020
**Blowout Eligible

FAQ

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)