#129 Claremont (12-8)

avg: 1195.86  •  sd: 77.08  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
141 Boston College Win 12-11 1291.16 Feb 10th Stanford Open 2018
121 Puget Sound Win 10-5 1830.81 Feb 10th Stanford Open 2018
26 Texas-Dallas Loss 7-12 1208.51 Feb 10th Stanford Open 2018
158 Lewis & Clark Loss 6-10 605.97 Feb 11th Stanford Open 2018
90 Northern Arizona Loss 9-11 1128.4 Feb 11th Stanford Open 2018
131 Chico State Loss 10-13 860.5 Feb 11th Stanford Open 2018
69 Carleton College-GoP Loss 11-12 1324.46 Feb 11th Stanford Open 2018
208 Occidental Win 11-9 1169.71 Feb 24th SoCal Mixer 2018
332 California-San Diego-B** Win 11-4 1042.18 Ignored Feb 24th SoCal Mixer 2018
394 California-San Diego-C** Win 11-2 722.22 Ignored Feb 24th SoCal Mixer 2018
320 Caltech Win 11-6 1051.55 Feb 24th SoCal Mixer 2018
382 UCLA-B** Win 11-2 815.18 Ignored Feb 24th SoCal Mixer 2018
100 Arizona Loss 7-13 777.95 Mar 24th Trouble in Vegas 2018
130 North Texas Loss 6-11 645.44 Mar 24th Trouble in Vegas 2018
225 California-B Win 9-6 1272.17 Mar 24th Trouble in Vegas 2018
202 Utah Valley Win 13-9 1350.66 Mar 24th Trouble in Vegas 2018
67 Utah Loss 6-10 961.81 Mar 24th Trouble in Vegas 2018
90 Northern Arizona Win 9-8 1502.6 Mar 25th Trouble in Vegas 2018
156 Colorado-Denver Win 15-8 1671.72 Mar 25th Trouble in Vegas 2018
176 Colorado State-B Win 11-5 1626.62 Mar 25th Trouble in Vegas 2018
**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)