#59 Greater Baltimore Anthem (13-8)

avg: 1309.03  •  sd: 62.09  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
141 PS Win 13-8 1340.73 Jun 24th LVU’s Disc Days of Summer 2023
183 Starfire Win 11-6 1149.66 Jun 24th LVU’s Disc Days of Summer 2023
84 Buffalo Lake Effect Loss 8-10 867.55 Jun 24th LVU’s Disc Days of Summer 2023
149 ColorBomb Win 12-7 1325.82 Jun 24th LVU’s Disc Days of Summer 2023
55 Garbage Plates Loss 7-8 1217.27 Jun 25th LVU’s Disc Days of Summer 2023
119 Mashed Win 10-9 1108.99 Jun 25th LVU’s Disc Days of Summer 2023
13 Slow Loss 6-13 1249.58 Jul 15th Boston Invite 2023
45 Wild Card Loss 9-11 1208.33 Jul 15th Boston Invite 2023
65 League of Shadows Win 10-5 1822.59 Jul 15th Boston Invite 2023
68 Heat Wave Win 10-9 1361.17 Jul 15th Boston Invite 2023
141 PS Win 15-8 1409.38 Aug 19th Philly Invite 2023
155 NY Swipes Win 15-5 1390.42 Aug 19th Philly Invite 2023
65 League of Shadows Loss 8-12 807.53 Aug 19th Philly Invite 2023
78 Deadweight Win 11-10 1286.64 Aug 20th Philly Invite 2023
55 Garbage Plates Loss 13-15 1128.09 Aug 20th Philly Invite 2023
66 HVAC Loss 13-14 1119.45 Aug 20th Philly Invite 2023
195 Swampbenders** Win 15-6 1148.56 Ignored Sep 9th 2023 Mixed Capital Sectional Championship
234 Voltage** Win 15-1 841.9 Ignored Sep 9th 2023 Mixed Capital Sectional Championship
14 Rally Loss 4-15 1233.74 Sep 10th 2023 Mixed Capital Sectional Championship
46 Revival Win 15-6 2036.06 Sep 10th 2023 Mixed Capital Sectional Championship
106 Ant Madness Win 11-7 1494.79 Sep 10th 2023 Mixed Capital Sectional Championship
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)