#347 Wright State (4-14)

avg: 527.36  •  sd: 77.23  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
222 Ball State Loss 5-13 443.66 Mar 2nd The Dayton Ultimate Disc Experience The DUDE
402 Case Western Reserve-B Win 13-3 638.41 Mar 2nd The Dayton Ultimate Disc Experience The DUDE
408 Dayton-B** Win 13-2 435.28 Ignored Mar 2nd The Dayton Ultimate Disc Experience The DUDE
157 Miami (Ohio)** Loss 4-13 689.76 Ignored Mar 2nd The Dayton Ultimate Disc Experience The DUDE
271 Cincinnati -B Loss 4-14 257.68 Mar 3rd The Dayton Ultimate Disc Experience The DUDE
182 Dayton** Loss 3-15 590.4 Ignored Mar 3rd The Dayton Ultimate Disc Experience The DUDE
268 Akron Loss 5-13 271.21 Mar 9th Spring Spook 2024
194 Ohio** Loss 3-13 542.62 Ignored Mar 9th Spring Spook 2024
378 SUNY-Buffalo-B Win 13-6 901.69 Mar 9th Spring Spook 2024
237 Carthage Loss 6-12 410.34 Mar 10th Spring Spook 2024
292 Kent State Win 13-8 1243.78 Mar 10th Spring Spook 2024
74 Cincinnati** Loss 1-13 1014 Ignored Apr 20th Ohio D I Mens Conferences 2024
35 Ohio State** Loss 0-13 1303.25 Ignored Apr 20th Ohio D I Mens Conferences 2024
282 Toledo Loss 5-10 244.65 Apr 20th Ohio D I Mens Conferences 2024
268 Akron Loss 6-7 746.21 Apr 21st Ohio D I Mens Conferences 2024
322 Cleveland State Loss 6-9 214.87 Apr 21st Ohio D I Mens Conferences 2024
182 Dayton** Loss 5-15 590.4 Ignored Apr 21st Ohio D I Mens Conferences 2024
194 Ohio** Loss 4-13 542.62 Ignored Apr 21st Ohio D I Mens Conferences 2024
**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)