#11 Lochsa (18-6)

avg: 1883.75  •  sd: 75.21  •  top 16/20: 87.2%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
82 Pegasus Win 10-9 1370.6 Jun 15th Northwest Mixer 2019
43 Birdfruit Win 10-8 1780.46 Jun 15th Northwest Mixer 2019
28 Lights Out Win 8-7 1768.61 Jun 15th Northwest Mixer 2019
3 Seattle Mixtape Loss 6-11 1537.02 Jun 15th Northwest Mixer 2019
87 Garbage Win 10-6 1701.52 Jun 15th Northwest Mixer 2019
7 Mischief Loss 6-12 1348.2 Jul 13th TCT Pro Elite Challenge 2019
1 Drag'n Thrust Win 10-9 2321.36 Jul 13th TCT Pro Elite Challenge 2019
30 No Touching! Loss 11-13 1411.89 Jul 13th TCT Pro Elite Challenge 2019
31 XIST Win 12-9 1971.29 Jul 14th TCT Pro Elite Challenge 2019
32 NOISE Win 10-8 1874.47 Jul 14th TCT Pro Elite Challenge 2019
20 Polar Bears Win 12-9 2101.42 Jul 14th TCT Pro Elite Challenge 2019
41 BW Ultimate Loss 12-13 1414.26 Aug 17th TCT Elite Select Challenge 2019
13 Toro Win 15-11 2231.64 Aug 17th TCT Elite Select Challenge 2019
5 Wild Card Loss 13-14 1877.74 Aug 17th TCT Elite Select Challenge 2019
18 Columbus Cocktails Win 10-6 2258.76 Aug 18th TCT Elite Select Challenge 2019
31 XIST Win 8-5 2079.53 Aug 18th TCT Elite Select Challenge 2019
4 Slow White Loss 9-10 1890.39 Aug 18th TCT Elite Select Challenge 2019
15 Loco Win 9-7 2081.67 Aug 18th TCT Elite Select Challenge 2019
63 Bunnies Win 13-7 1908 Sep 7th Big Sky Mixed Club Sectional Championship 2019
24 MOONDOG Win 13-11 1939.27 Sep 7th Big Sky Mixed Club Sectional Championship 2019
166 Wasatch Sasquatch** Win 13-5 1439.19 Ignored Sep 7th Big Sky Mixed Club Sectional Championship 2019
203 Fishpix!** Win 13-2 1291.68 Ignored Sep 7th Big Sky Mixed Club Sectional Championship 2019
262 Bozos** Win 13-5 940.45 Ignored Sep 8th Big Sky Mixed Club Sectional Championship 2019
24 MOONDOG Win 13-9 2129 Sep 8th Big Sky Mixed 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)