#169 Chico State (12-5)

avg: 1084.3  •  sd: 89.12  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
444 California-Irvine-B** Win 13-0 12.99 Ignored Feb 2nd Presidents Day Qualifiers Men
414 UCLA-B** Win 13-1 731.49 Ignored Feb 2nd Presidents Day Qualifiers Men
407 California-Santa Barbara-B** Win 13-2 784.86 Ignored Feb 2nd Presidents Day Qualifiers Men
244 Colorado-B Win 9-8 1002.2 Feb 2nd Presidents Day Qualifiers Men
164 Arizona State Win 8-6 1403.72 Feb 3rd Presidents Day Qualifiers Men
272 Arizona State-B Win 11-9 1025.68 Feb 3rd Presidents Day Qualifiers Men
100 California-Santa Cruz Loss 8-11 993.16 Feb 3rd Presidents Day Qualifiers Men
- Stanford-B** Win 13-2 600 Ignored Feb 9th Stanford Open 2019
93 California-Davis Loss 7-10 987.88 Feb 9th Stanford Open 2019
175 North Texas Loss 9-11 817.89 Feb 9th Stanford Open 2019
191 Montana State Win 10-7 1414.62 Mar 23rd Trouble in Vegas 2019
361 Miami Win 10-5 996.41 Mar 23rd Trouble in Vegas 2019
202 Northern Arizona Loss 10-13 644.92 Mar 23rd Trouble in Vegas 2019
344 California-Irvine Win 13-4 1106.27 Mar 23rd Trouble in Vegas 2019
254 Cal Poly-Pomona Win 13-4 1440.19 Mar 24th Trouble in Vegas 2019
65 Florida Loss 4-13 935.75 Mar 24th Trouble in Vegas 2019
184 California-B Win 11-9 1281.72 Mar 24th Trouble in Vegas 2019
**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)