#159 Hellbenders (7-16)

avg: 810.74  •  sd: 62.31  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
215 Free Ride Win 13-6 1092.01 Jul 21st The Royal Experience 18
128 Boomtown Loss 9-13 559.17 Jul 21st The Royal Experience 18
94 Tex Mix Loss 7-10 763.37 Jul 21st The Royal Experience 18
191 Coalition Ultimate Win 16-14 827.97 Jul 22nd The Royal Experience 18
94 Tex Mix Loss 3-15 553.03 Jul 22nd The Royal Experience 18
128 Boomtown Loss 8-15 412.93 Jul 22nd The Royal Experience 18
234 rubber duck ultimate. Win 13-7 813.67 Aug 11th Hootie on the Hill 2018
115 STAX Loss 8-9 912.43 Aug 11th Hootie on the Hill 2018
128 Boomtown Loss 8-10 715.07 Aug 11th Hootie on the Hill 2018
240 Memphis Hustle & Flow Win 11-5 744.49 Aug 11th Hootie on the Hill 2018
130 Impact Loss 8-15 404.02 Aug 12th Hootie on the Hill 2018
135 Blitzkrieg Loss 6-15 357.73 Aug 12th Hootie on the Hill 2018
34 Woodwork Loss 6-13 915.38 Sep 15th West Plains Mixed Sectional Championship 2018
215 Free Ride Win 13-7 1049.54 Sep 15th West Plains Mixed Sectional Championship 2018
111 panIC Loss 11-13 837.65 Sep 15th West Plains Mixed Sectional Championship 2018
70 Chalice Loss 9-13 858.07 Sep 15th West Plains Mixed Sectional Championship 2018
93 Thoroughbred Loss 7-13 599.01 Sep 16th West Plains Mixed Sectional Championship 2018
130 Impact Win 13-11 1197.67 Sep 16th West Plains Mixed Sectional Championship 2018
39 Minnesota Star Power** Loss 5-13 899.53 Ignored Sep 22nd North Central Mixed Regional Championship 2018
20 No Touching!** Loss 5-13 1081.38 Ignored Sep 22nd North Central Mixed Regional Championship 2018
70 Chalice Loss 6-11 729.94 Sep 22nd North Central Mixed Regional Championship 2018
93 Thoroughbred Loss 10-12 918.42 Sep 23rd North Central Mixed Regional Championship 2018
135 Blitzkrieg Win 13-10 1285.88 Sep 23rd North Central Mixed Regional Championship 2018
**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)