#111 Lehigh (9-9)

avg: 918.2  •  sd: 98.07  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
63 Haverford/Bryn Mawr Win 11-7 1743.16 Feb 25th Bring The Huckus1
102 Dartmouth Loss 7-11 506.15 Feb 25th Bring The Huckus1
146 SUNY-Geneseo Win 12-10 888.27 Feb 25th Bring The Huckus1
63 Haverford/Bryn Mawr Loss 4-11 676.27 Feb 26th Bring The Huckus1
113 Ithaca Win 8-7 1030.27 Feb 26th Bring The Huckus1
154 Syracuse Win 9-2 1182.2 Feb 26th Bring The Huckus1
63 Haverford/Bryn Mawr Loss 5-9 747.21 Mar 25th Garden State1
113 Ithaca Win 7-5 1233.41 Mar 25th Garden State1
89 Columbia Loss 6-10 582.5 Mar 25th Garden State1
63 Haverford/Bryn Mawr Loss 2-11 676.27 Mar 26th Garden State1
89 Columbia Win 8-2 1678.66 Mar 26th Garden State1
140 Rochester Win 8-7 805.32 Mar 26th Garden State1
151 Rutgers Loss 3-6 58.82 Apr 1st Shady Encounters
59 Penn State Win 8-7 1426.24 Apr 1st Shady Encounters
61 Vermont-B Loss 5-6 1161.54 Apr 1st Shady Encounters
67 Mount Holyoke Loss 5-8 814.09 Apr 2nd Shady Encounters
97 NYU Loss 6-10 514.05 Apr 2nd Shady Encounters
185 Messiah** Win 13-4 863.48 Ignored Apr 2nd Shady Encounters
**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)