#292 Kent State (6-16)

avg: 747.63  •  sd: 70.99  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
68 Franciscan** Loss 4-13 1060.48 Ignored Feb 3rd Huckin in the Hills X
212 West Virginia Loss 5-13 479.5 Feb 3rd Huckin in the Hills X
194 Ohio Loss 9-13 724.06 Feb 3rd Huckin in the Hills X
212 West Virginia Loss 8-15 514.69 Feb 4th Huckin in the Hills X
387 Ohio-B Win 15-4 842.5 Feb 4th Huckin in the Hills X
194 Ohio Loss 9-13 724.06 Feb 4th Huckin in the Hills X
237 Carthage Loss 6-9 571.09 Mar 9th Spring Spook 2024
194 Ohio Loss 6-13 542.62 Mar 9th Spring Spook 2024
157 Miami (Ohio) Loss 8-11 924.15 Mar 9th Spring Spook 2024
378 SUNY-Buffalo-B Win 12-6 881 Mar 10th Spring Spook 2024
347 Wright State Loss 8-13 31.2 Mar 10th Spring Spook 2024
268 Akron Win 11-10 996.21 Apr 20th Ohio D I Mens Conferences 2024
79 Case Western Reserve Loss 7-12 1075.18 Apr 20th Ohio D I Mens Conferences 2024
322 Cleveland State Win 11-8 999.05 Apr 20th Ohio D I Mens Conferences 2024
268 Akron Win 10-9 996.21 Apr 21st Ohio D I Mens Conferences 2024
194 Ohio Loss 4-15 542.62 Apr 21st Ohio D I Mens Conferences 2024
282 Toledo Win 13-12 943.55 Apr 21st Ohio D I Mens Conferences 2024
6 Pittsburgh** Loss 4-15 1732.82 Ignored May 4th Ohio Valley D I College Mens Regionals 2024
130 Penn State-B Loss 11-14 1066.08 May 4th Ohio Valley D I College Mens Regionals 2024
212 West Virginia Loss 6-15 479.5 May 4th Ohio Valley D I College Mens Regionals 2024
194 Ohio Loss 6-14 542.62 May 5th Ohio Valley D I College Mens Regionals 2024
170 Villanova Loss 5-15 651.96 May 5th 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)