#143 Foxtrot (7-14)

avg: 495.5  •  sd: 83.87  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
110 Dreadnought Loss 7-13 211.85 Jun 30th Texas Two Finger 2018
129 Prime Loss 4-12 44.69 Jun 30th Texas Two Finger 2018
150 The Bayou Boys Win 11-6 887.94 Jun 30th Texas Two Finger 2018
82 Riverside Loss 8-15 379.6 Jul 1st Texas Two Finger 2018
147 DUCS Loss 10-11 286.7 Jul 1st Texas Two Finger 2018
141 DUPlex Loss 3-7 -82.98 Jul 1st Texas Two Finger 2018
141 DUPlex Loss 7-9 237.68 Aug 4th PBJ 2018
79 Papa Bear Loss 6-13 359.27 Aug 4th PBJ 2018
84 Gaucho Loss 6-13 339.29 Aug 4th PBJ 2018
166 Surrillic Audovice Win 13-3 682.76 Aug 4th PBJ 2018
147 DUCS Loss 8-11 46.1 Aug 5th PBJ 2018
43 Clutch** Loss 4-13 654.73 Ignored Aug 5th PBJ 2018
150 The Bayou Boys Win 15-8 906.06 Aug 5th PBJ 2018
147 DUCS Win 10-7 801.37 Sep 8th Texas Mens Sectional Championship 2018
69 Gamble Loss 4-11 433.45 Sep 8th Texas Mens Sectional Championship 2018
129 Prime Loss 5-8 191.09 Sep 8th Texas Mens Sectional Championship 2018
43 Clutch** Loss 3-10 654.73 Ignored Sep 8th Texas Mens Sectional Championship 2018
82 Riverside Loss 5-11 344.4 Sep 9th Texas Mens Sectional Championship 2018
- Rock Steady Win 10-6 850.1 Sep 9th Texas Mens Sectional Championship 2018
141 DUPlex Win 11-5 1117.02 Sep 9th Texas Mens Sectional Championship 2018
- Shrike Cutters Win 11-3 705.92 Sep 9th Texas Mens Sectional 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)