#12 Rhino Slam (36-9)

avg: 1779.67  •  sd: 68.87  •  top 16/20: 91.1%

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# Opponent Result Game Rating Status Date Event
22 Voodoo Win 13-7 2062.01 Jun 22nd Eugene Summer Solstice 40
- Ham Win 13-7 1701.8 Jun 23rd Eugene Summer Solstice 40
- Whitefish** Win 13-2 941.91 Ignored Jun 23rd Eugene Summer Solstice 40
88 PowderHogs** Win 13-3 1508.48 Ignored Jun 23rd Eugene Summer Solstice 40
78 Rip City Ultimate** Win 13-3 1575.79 Ignored Jun 24th Eugene Summer Solstice 40
38 Dark Star Win 12-7 1800.43 Jun 24th Eugene Summer Solstice 40
6 Furious George Win 13-10 2197.26 Jun 24th Eugene Summer Solstice 40
13 Johnny Bravo Loss 7-13 1218.93 Jul 7th TCT Pro Elite Challenge 2018
11 DiG Win 10-8 2059.91 Jul 7th TCT Pro Elite Challenge 2018
17 SoCal Condors Win 13-8 2177.18 Jul 7th TCT Pro Elite Challenge 2018
20 Patrol Loss 10-13 1212.56 Jul 8th TCT Pro Elite Challenge 2018
25 Medicine Men Win 13-9 1824.15 Jul 8th TCT Pro Elite Challenge 2018
16 Madison Club Loss 9-11 1443.31 Jul 8th TCT Pro Elite Challenge 2018
21 Prairie Fire Win 13-4 2108.18 Jul 27th TCT Select Flight Invite 2018
63 Sawtooth Win 13-8 1552.72 Jul 28th TCT Select Flight Invite 2018
69 Gamble Win 13-8 1529.61 Jul 28th TCT Select Flight Invite 2018
39 Mad Men Win 13-4 1878.97 Jul 28th TCT Select Flight Invite 2018
38 Dark Star Win 13-10 1608.06 Jul 29th TCT Select Flight Invite 2018
19 Guerrilla Win 13-8 2044.05 Jul 29th TCT Select Flight Invite 2018
6 Furious George Win 15-14 1994.11 Jul 29th TCT Select Flight Invite 2018
40 Streetgang Win 13-4 1875.1 Aug 25th CBR Memorial 2018
2 Sockeye Win 11-9 2284.37 Aug 25th CBR Memorial 2018
86 Green River Swordfish** Win 13-4 1522.11 Ignored Aug 25th CBR Memorial 2018
78 Rip City Ultimate Win 13-7 1533.33 Aug 25th CBR Memorial 2018
6 Furious George Win 11-9 2118.32 Aug 26th CBR Memorial 2018
38 Dark Star Win 13-8 1776.08 Aug 26th CBR Memorial 2018
38 Dark Star Win 13-7 1837.45 Sep 8th Oregon Mens Sectional Championship 2018
155 NANO** Win 13-4 901.41 Ignored Sep 8th Oregon Mens Sectional Championship 2018
- HIPPO** Win 13-4 1427.02 Ignored Sep 8th Oregon Mens Sectional Championship 2018
78 Rip City Ultimate Win 13-8 1471.95 Sep 8th Oregon Mens Sectional Championship 2018
38 Dark Star Win 13-9 1698.49 Sep 9th Oregon Mens Sectional Championship 2018
46 Ghost Train Win 13-7 1783.36 Sep 22nd Northwest Mens Regional Championship 2018
63 Sawtooth** Win 13-4 1656.56 Ignored Sep 22nd Northwest Mens Regional Championship 2018
6 Furious George Loss 8-13 1372.95 Sep 22nd Northwest Mens Regional Championship 2018
38 Dark Star Win 13-4 1879.92 Sep 22nd Northwest Mens Regional Championship 2018
2 Sockeye Loss 9-13 1616.6 Sep 23rd Northwest Mens Regional Championship 2018
46 Ghost Train Win 13-5 1825.83 Sep 23rd Northwest Mens Regional Championship 2018
22 Voodoo Win 14-12 1725.43 Sep 23rd Northwest Mens Regional Championship 2018
3 PoNY Loss 11-13 1802.46 Oct 18th USA Ultimate National Championships 2018
5 Truck Stop Loss 10-15 1483.26 Oct 18th USA Ultimate National Championships 2018
13 Johnny Bravo Loss 13-14 1651.46 Oct 18th USA Ultimate National Championships 2018
18 Pittsburgh Temper Win 15-9 2186.88 Oct 19th USA Ultimate National Championships 2018
9 HIGH FIVE Loss 8-15 1249.05 Oct 19th USA Ultimate National Championships 2018
15 Chain Lightning Win 15-13 1906.92 Oct 19th USA Ultimate National Championships 2018
16 Madison Club Win 15-6 2292.51 Oct 20th USA Ultimate National Championships 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)