#20 Patrol (10-15)

avg: 1540.7  •  sd: 75.13  •  top 16/20: 3.6%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
7 Chicago Machine Loss 7-13 1287.4 Jul 7th TCT Pro Elite Challenge 2018
5 Truck Stop Win 13-7 2494.4 Jul 7th TCT Pro Elite Challenge 2018
19 Guerrilla Win 13-11 1776.73 Jul 7th TCT Pro Elite Challenge 2018
12 Rhino Slam Win 13-10 2107.81 Jul 8th TCT Pro Elite Challenge 2018
10 Doublewide Loss 6-13 1212.48 Jul 8th TCT Pro Elite Challenge 2018
2 Sockeye Loss 9-13 1616.6 Jul 8th TCT Pro Elite Challenge 2018
11 DiG Loss 7-9 1517.91 Jul 8th TCT Pro Elite Challenge 2018
27 Turbine Win 13-12 1517.19 Aug 18th TCT Elite Select Challenge 2018
17 SoCal Condors Loss 11-13 1452.18 Aug 18th TCT Elite Select Challenge 2018
18 Pittsburgh Temper Loss 10-13 1343.25 Aug 18th TCT Elite Select Challenge 2018
9 HIGH FIVE Loss 8-13 1317.7 Aug 19th TCT Elite Select Challenge 2018
21 Prairie Fire Win 13-7 2065.71 Aug 19th TCT Elite Select Challenge 2018
4 Ring of Fire Loss 11-15 1612.57 Sep 1st TCT Pro Championships 2018
7 Chicago Machine Loss 11-15 1463.77 Sep 1st TCT Pro Championships 2018
13 Johnny Bravo Loss 9-15 1260.98 Sep 1st TCT Pro Championships 2018
3 PoNY Loss 10-15 1577.7 Sep 1st TCT Pro Championships 2018
7 Chicago Machine Loss 11-14 1531.59 Sep 2nd TCT Pro Championships 2018
8 Sub Zero Loss 9-15 1314.29 Sep 2nd TCT Pro Championships 2018
118 Adelphos** Win 13-3 1318.38 Ignored Sep 22nd Mid Atlantic Mens Regional Championship 2018
5 Truck Stop Loss 7-15 1336.86 Sep 22nd Mid Atlantic Mens Regional Championship 2018
52 Oakgrove Boys Win 13-10 1515.07 Sep 22nd Mid Atlantic Mens Regional Championship 2018
109 JAWN Win 13-6 1369.86 Sep 22nd Mid Atlantic Mens Regional Championship 2018
30 Garden State Ultimate Win 13-10 1678.7 Sep 23rd Mid Atlantic Mens Regional Championship 2018
25 Medicine Men Win 14-13 1530.58 Sep 23rd Mid Atlantic Mens Regional Championship 2018
18 Pittsburgh Temper Loss 13-14 1546.4 Sep 23rd Mid Atlantic Mens Regional 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)