#49 Trainwreck (11-8)

avg: 934.06  •  sd: 58.41  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
71 Jackwagon Win 11-4 1097.72 Jun 24th Colorado Summer Solstice 2023
85 Colorado Cutthroat: Youth Club U-20 Girls** Win 10-2 853.81 Ignored Jun 24th Colorado Summer Solstice 2023
- Molly Blue Loss 3-15 715.87 Jun 24th Colorado Summer Solstice 2023
52 Void Cat Rewind Loss 7-9 614.25 Aug 19th Ski Town Classic 2023
79 Swell Win 13-3 949.65 Aug 19th Ski Town Classic 2023
84 Seattle Soul** Win 13-5 869.19 Ignored Aug 19th Ski Town Classic 2023
52 Void Cat Rewind Loss 7-8 768.58 Aug 20th Ski Town Classic 2023
20 Wildfire Loss 8-13 1064.45 Aug 20th Ski Town Classic 2023
58 Fiasco Win 8-7 914.62 Aug 20th Ski Town Classic 2023
25 Colorado Small Batch Loss 8-11 1093.86 Sep 9th 2023 Womens Rocky Mountain Sectional Championship
70 COSMOS Win 13-2 1102.32 Sep 9th 2023 Womens Rocky Mountain Sectional Championship
71 Jackwagon Win 13-1 1097.72 Sep 9th 2023 Womens Rocky Mountain Sectional Championship
85 Colorado Cutthroat: Youth Club U-20 Girls** Win 13-3 853.81 Ignored Sep 9th 2023 Womens Rocky Mountain Sectional Championship
70 COSMOS Win 7-3 1102.32 Sep 23rd 2023 South Central Womens Regional
91 Firewheel** Win 12-4 674.38 Ignored Sep 23rd 2023 South Central Womens Regional
4 Molly Brown** Loss 0-15 1734.03 Ignored Sep 23rd 2023 South Central Womens Regional
25 Colorado Small Batch Loss 3-14 859.47 Sep 24th 2023 South Central Womens Regional
40 Hayride Loss 5-9 548.68 Sep 24th 2023 South Central Womens Regional
46 San Antonio Problems Win 6-5 1084.3 Sep 24th 2023 South Central Womens Regional
**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)