#167 Indiana Pterodactyl Attack (11-14)

avg: 747.33  •  sd: 61.5  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
212 Chalice Win 13-4 1044.91 Jul 22nd Corny Classic II
116 Jabba Loss 10-13 664.05 Jul 22nd Corny Classic II
209 Mastodon Win 13-9 881.93 Jul 22nd Corny Classic II
165 Prion Win 14-13 886.72 Jul 23rd Corny Classic II
131 Stackcats Win 13-12 1015.78 Jul 23rd Corny Classic II
92 Three Rivers Ultimate Club Loss 11-15 704.37 Jul 23rd Corny Classic II
115 Queen City Gambit Loss 6-13 397.8 Aug 19th Motown Throwdown 2023
136 Skyhawks Win 10-3 1456.02 Aug 19th Motown Throwdown 2023
110 Trex Mix Win 12-11 1138.15 Aug 19th Motown Throwdown 2023
115 Queen City Gambit Loss 7-11 530.91 Aug 20th Motown Throwdown 2023
136 Skyhawks Win 9-8 981.02 Aug 20th Motown Throwdown 2023
231 POW! Win 11-6 806.35 Aug 20th Motown Throwdown 2023
92 Three Rivers Ultimate Club Loss 3-11 485.54 Aug 20th Motown Throwdown 2023
136 Skyhawks Loss 8-15 291.21 Sep 9th 2023 Mixed Central Plains Sectional Championship
27 Chicago Parlay** Loss 3-15 1037.51 Ignored Sep 9th 2023 Mixed Central Plains Sectional Championship
116 Jabba Win 13-12 1117.19 Sep 9th 2023 Mixed Central Plains Sectional Championship
136 Skyhawks Win 11-10 981.02 Sep 10th 2023 Mixed Central Plains Sectional Championship
88 Spectre Loss 7-13 551.09 Sep 10th 2023 Mixed Central Plains Sectional Championship
165 Prion Win 14-9 1235.59 Sep 10th 2023 Mixed Central Plains Sectional Championship
115 Queen City Gambit Loss 5-15 397.8 Sep 23rd 2023 Great Lakes Mixed Regional Championship
165 Prion Loss 10-12 523.6 Sep 23rd 2023 Great Lakes Mixed Regional Championship
131 Stackcats Loss 5-15 290.78 Sep 23rd 2023 Great Lakes Mixed Regional Championship
107 Columbus Chaos Loss 9-14 553.66 Sep 23rd 2023 Great Lakes Mixed Regional Championship
115 Queen City Gambit Loss 11-12 872.8 Sep 24th 2023 Great Lakes Mixed Regional Championship
165 Prion Loss 12-13 636.72 Sep 24th 2023 Great Lakes Mixed Regional Championship
**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)