#157 Miami (Ohio) (14-5)

avg: 1289.76  •  sd: 74.77  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
222 Ball State Win 10-8 1306.33 Mar 2nd The Dayton Ultimate Disc Experience The DUDE
402 Case Western Reserve-B** Win 13-1 638.41 Ignored Mar 2nd The Dayton Ultimate Disc Experience The DUDE
408 Dayton-B** Win 13-1 435.28 Ignored Mar 2nd The Dayton Ultimate Disc Experience The DUDE
347 Wright State** Win 13-4 1127.36 Ignored Mar 2nd The Dayton Ultimate Disc Experience The DUDE
182 Dayton Win 11-9 1439.61 Mar 3rd The Dayton Ultimate Disc Experience The DUDE
118 Kentucky Loss 9-12 1070.55 Mar 3rd The Dayton Ultimate Disc Experience The DUDE
237 Carthage Win 10-8 1252.32 Mar 9th Spring Spook 2024
292 Kent State Win 11-8 1113.23 Mar 9th Spring Spook 2024
194 Ohio Win 10-9 1267.62 Mar 9th Spring Spook 2024
378 SUNY-Buffalo-B** Win 13-5 901.69 Ignored Mar 9th Spring Spook 2024
268 Akron Win 14-8 1407.25 Mar 10th Spring Spook 2024
322 Cleveland State Win 13-6 1233.44 Apr 20th Ohio D I Mens Conferences 2024
182 Dayton Win 9-8 1315.4 Apr 20th Ohio D I Mens Conferences 2024
79 Case Western Reserve Win 13-12 1720.69 Apr 21st Ohio D I Mens Conferences 2024
79 Case Western Reserve Loss 4-11 995.69 Apr 21st Ohio D I Mens Conferences 2024
74 Cincinnati Loss 7-11 1147.11 Apr 21st Ohio D I Mens Conferences 2024
74 Cincinnati Loss 10-15 1160.4 May 4th Ohio Valley D I College Mens Regionals 2024
170 Villanova Win 13-8 1748.12 May 4th Ohio Valley D I College Mens Regionals 2024
127 Pittsburgh-B Loss 11-14 1075.39 May 4th Ohio Valley D I College Mens Regionals 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)