#72 Sawtooth (15-10)

avg: 1188.67  •  sd: 61.38  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
136 Syndicate Win 13-6 1456.08 Jun 22nd Eugene Summer Solstice 2019
65 Dohrk Stor Win 11-9 1494.47 Jun 22nd Eugene Summer Solstice 2019
110 Oregon Eruption! Loss 8-10 726.33 Jun 22nd Eugene Summer Solstice 2019
19 Voodoo Loss 6-13 1135.56 Jun 22nd Eugene Summer Solstice 2019
53 Ghost Train Loss 11-13 1082.01 Jun 23rd Eugene Summer Solstice 2019
121 Green River Swordfish Win 15-11 1321.35 Jun 23rd Eugene Summer Solstice 2019
23 CLE Smokestack Loss 4-15 1035.66 Jul 13th TCT Select Flight Invite West 2019
41 MKE Loss 10-12 1172.71 Jul 13th TCT Select Flight Invite West 2019
51 Turbine Loss 7-15 732.69 Jul 13th TCT Select Flight Invite West 2019
176 Daybreak Win 12-11 761.59 Jul 14th TCT Select Flight Invite West 2019
67 UpRoar Loss 10-12 974.2 Jul 14th TCT Select Flight Invite West 2019
73 ISO Atmo Win 11-9 1436.91 Jul 14th TCT Select Flight Invite West 2019
90 Choice City Hops Win 13-11 1332.44 Aug 24th Ski Town Classic 2019
61 Sundowners Win 11-7 1734.96 Aug 24th Ski Town Classic 2019
165 OC Crows Win 13-2 1295.41 Aug 24th Ski Town Classic 2019
46 The Killjoys Loss 8-13 871.36 Aug 24th Ski Town Classic 2019
156 Cojones Win 13-6 1342.9 Aug 25th Ski Town Classic 2019
54 Battery Win 10-8 1570.15 Aug 25th Ski Town Classic 2019
73 ISO Atmo Win 11-9 1436.91 Aug 25th Ski Town Classic 2019
170 Sandbaggers Win 13-6 1261.73 Sep 7th Big Sky Mens Club Sectional Championship 2019
46 The Killjoys Loss 9-13 948.95 Sep 7th Big Sky Mens Club Sectional Championship 2019
- Old Ephraim Win 13-7 1225.43 Sep 7th Big Sky Mens Club Sectional Championship 2019
97 PowderHogs Win 13-11 1292.95 Sep 7th Big Sky Mens Club Sectional Championship 2019
109 Low Point Loss 4-10 390.66 Sep 8th Big Sky Mens Club Sectional Championship 2019
109 Low Point Win 13-9 1409.23 Sep 8th Big Sky Mens 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)