#281 Edinboro (8-11)

avg: 450.84  •  sd: 58.56  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
104 Dayton** Loss 3-13 614.61 Ignored Feb 3rd Huckin in the Hills X
361 Ohio-B Win 13-8 449.18 Feb 3rd Huckin in the Hills X
130 Towson** Loss 3-13 516.83 Ignored Feb 3rd Huckin in the Hills X
104 Dayton** Loss 4-15 614.61 Ignored Feb 4th Huckin in the Hills X
204 Ohio Loss 2-15 209.59 Feb 4th Huckin in the Hills X
361 Ohio-B Win 12-6 532.33 Feb 4th Huckin in the Hills X
187 Salisbury Loss 9-13 445.11 Feb 24th Bring The Huckus 2024
277 Stevens Tech Loss 7-11 30.56 Feb 24th Bring The Huckus 2024
344 Lehigh-B Win 9-4 686.14 Feb 24th Bring The Huckus 2024
233 Skidmore Loss 3-9 104.52 Feb 24th Bring The Huckus 2024
312 Rutgers-B Win 15-9 803.77 Feb 25th Bring The Huckus 2024
306 Swarthmore Win 11-10 449.08 Feb 25th Bring The Huckus 2024
374 West Chester-B** Win 13-0 267.76 Ignored Mar 23rd Garden State 2024
277 Stevens Tech Win 11-4 1097.45 Mar 23rd Garden State 2024
197 Haverford Loss 4-7 340.03 Mar 23rd Garden State 2024
344 Lehigh-B Win 11-4 686.14 Mar 24th Garden State 2024
270 Rowan Loss 6-8 211.47 Mar 24th Garden State 2024
203 West Virginia Loss 4-10 219.37 Mar 24th Garden State 2024
166 Villanova Loss 5-11 358.54 Mar 24th Garden State 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)