#284 Pacific Lutheran (4-9)

avg: 430.87  •  sd: 67.83  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
286 Reed Win 9-8 547.14 Feb 10th DIII Grand Prix
59 Whitman** Loss 2-13 836.78 Ignored Feb 10th DIII Grand Prix
190 Portland Loss 6-11 315.06 Feb 10th DIII Grand Prix
163 Xavier Loss 4-13 373.48 Feb 10th DIII Grand Prix
234 Claremont Loss 9-10 578.14 Feb 11th DIII Grand Prix
279 Whitworth Loss 8-10 217.04 Feb 11th DIII Grand Prix
80 Lewis & Clark** Loss 4-11 739.69 Ignored Feb 11th DIII Grand Prix
356 Oregon State-B Win 10-7 381.17 Mar 2nd PLU Mens BBQ
345 Seattle Win 11-7 521.79 Mar 2nd PLU Mens BBQ
168 Washington State Loss 4-13 353.98 Mar 2nd PLU Mens BBQ
339 Portland State Win 13-4 705.28 Mar 2nd PLU Mens BBQ
94 Puget Sound** Loss 4-13 660.79 Ignored Mar 3rd PLU Mens BBQ
190 Portland Loss 4-9 261.75 Mar 3rd PLU Mens BBQ
**Blowout Eligible

FAQ

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
  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
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)