#301 Salisbury (8-11)

avg: 653.13  •  sd: 68.3  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
84 Brandeis** Loss 4-13 831.89 Ignored Feb 23rd Oak Creek Challenge 2019
292 Navy Win 13-8 1199.06 Feb 23rd Oak Creek Challenge 2019
158 Lehigh Loss 3-13 529.08 Feb 23rd Oak Creek Challenge 2019
174 Cedarville Loss 1-13 467.46 Feb 23rd Oak Creek Challenge 2019
166 Virginia Commonwealth Loss 5-15 491.83 Feb 24th Oak Creek Challenge 2019
250 Maryland-Baltimore County Loss 10-15 401.65 Feb 24th Oak Creek Challenge 2019
245 Stevens Tech Loss 2-13 276.22 Mar 9th Atlantic City 9
153 SUNY-Albany Loss 1-13 551.01 Mar 9th Atlantic City 9
95 Bates College** Loss 3-13 769.77 Ignored Mar 9th Atlantic City 9
252 SUNY-Cortland Loss 2-13 245.28 Mar 10th Atlantic City 9
397 SUNY-Albany-B Win 9-7 519.83 Mar 10th Atlantic City 9
245 Stevens Tech Loss 5-13 276.22 Mar 10th Atlantic City 9
426 Sacred Heart** Win 13-4 607.92 Ignored Mar 30th Garden State 9
440 Lancaster Bible** Win 13-2 225.84 Ignored Mar 30th Garden State 9
387 Princeton-B Win 13-7 838.93 Mar 30th Garden State 9
335 College of New Jersey Win 13-8 1037.37 Mar 30th Garden State 9
245 Stevens Tech Win 12-11 1001.22 Mar 31st Garden State 9
343 Dickinson Win 12-7 1032.81 Mar 31st Garden State 9
60 Bryant University** Loss 1-13 954.37 Ignored Mar 31st Garden State 9
**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)