#340 Lehigh-B (2-11)

avg: 171.65  •  sd: 70.42  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
330 Edinboro Loss 7-8 144.37 Feb 25th Bring The Huckus1
359 Pennsylvania-B Win 11-7 333.54 Feb 25th Bring The Huckus1
300 Rutgers-B Loss 6-9 27.01 Feb 25th Bring The Huckus1
220 Dickinson** Loss 5-12 257.63 Ignored Feb 25th Bring The Huckus1
357 SUNY-Albany-B Loss 7-8 -238.64 Feb 26th Bring The Huckus1
267 Vermont-C Loss 1-9 51.42 Mar 4th Philly Special1
295 Muhlenberg Loss 4-8 -62.12 Mar 4th Philly Special1
295 Muhlenberg Loss 6-11 -44.01 Mar 5th Philly Special1
132 Ave Maria** Loss 4-13 642.39 Apr 1st 2023 B team Brodown
165 Penn State-B** Loss 4-11 498.45 Ignored Apr 1st 2023 B team Brodown
250 Shippensburg Loss 3-12 132.94 Apr 1st 2023 B team Brodown
355 Case Western Reserve-B Win 13-5 551.98 Apr 2nd 2023 B team Brodown
273 Michigan-B Loss 3-15 15.56 Apr 2nd 2023 B team Brodown
**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)