#209 Mastodon (9-15)

avg: 463.36  •  sd: 56.35  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
179 Frostbite Loss 6-11 99.46 Jul 8th Heavyweights 2023
150 Toast! Loss 7-9 524.29 Jul 8th Heavyweights 2023
116 Jabba Loss 5-13 392.19 Jul 8th Heavyweights 2023
40 UNION** Loss 1-13 891.86 Ignored Jul 8th Heavyweights 2023
231 POW! Win 12-11 384.66 Jul 9th Heavyweights 2023
176 The Force Win 11-10 776.87 Jul 9th Heavyweights 2023
212 Chalice Win 13-11 673.75 Jul 22nd Corny Classic II
167 Indiana Pterodactyl Attack Loss 9-13 328.76 Jul 22nd Corny Classic II
116 Jabba Loss 8-13 496.04 Jul 22nd Corny Classic II
241 PanIC Win 11-10 266.8 Jul 23rd Corny Classic II
165 Prion Loss 4-9 161.72 Jul 23rd Corny Classic II
131 Stackcats Loss 10-12 652.65 Jul 23rd Corny Classic II
225 Arms Race Win 13-6 922.21 Aug 19th Cooler Classic 34
203 Locomotion Loss 5-7 185.41 Aug 19th Cooler Classic 34
236 Mad City Vibes Win 10-6 729.18 Aug 19th Cooler Classic 34
244 Underdogs Win 10-9 209.14 Aug 19th Cooler Classic 34
165 Prion Loss 5-14 161.72 Aug 20th Cooler Classic 34
131 Stackcats Loss 8-13 394.62 Aug 20th Cooler Classic 34
109 Pushovers Loss 7-13 467.98 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
179 Frostbite Win 11-9 895.36 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
76 Bantr** Loss 5-13 584.05 Ignored Sep 9th 2023 Mixed Northwest Plains Sectional Championship
182 Melt Win 11-10 745.06 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
179 Frostbite Loss 5-14 46.15 Sep 10th 2023 Mixed Northwest Plains Sectional Championship
86 Mad Udderburn** Loss 6-15 521.14 Ignored Sep 10th 2023 Mixed Northwest Plains Sectional 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)