#220 Genny Lite (2-13)

avg: 273.09  •  sd: 68.09  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
207 Sky Hook Loss 9-11 170.42 Jul 13th Ow My Knee
181 Helots Loss 7-13 15.33 Jul 13th Ow My Knee
226 Fusion Loss 8-9 108.89 Jul 14th Ow My Knee
148 Overcast Loss 5-13 177.22 Jul 14th Ow My Knee
233 Buffalo Open Win 13-8 566.74 Aug 3rd Philly Open 2019
171 Adelphos Loss 10-13 328.66 Aug 3rd Philly Open 2019
35 Tanasi** Loss 1-13 873.63 Ignored Aug 3rd Philly Open 2019
200 NEO Loss 12-13 338.49 Aug 3rd Philly Open 2019
108 Somerville BAG Loss 9-13 579.4 Aug 4th Philly Open 2019
211 Bearproof Loss 7-13 -166.06 Aug 4th Philly Open 2019
148 Overcast Loss 5-13 177.22 Sep 7th Upstate New York Mens Club Sectional Championship 2019
114 Phoenix** Loss 4-13 364.33 Sep 7th Upstate New York Mens Club Sectional Championship 2019
233 Buffalo Open Win 10-3 670.58 Sep 7th Upstate New York Mens Club Sectional Championship 2019
143 Shrike Loss 5-12 207.08 Sep 7th Upstate New York Mens Club Sectional Championship 2019
148 Overcast Loss 4-15 177.22 Sep 8th Upstate New York Mens Club Sectional Championship 2019
**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)