#406 Colorado School of Mines - B (4-11)

avg: 187.01  •  sd: 79.88  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
125 Colorado School of Mines** Loss 0-13 678.32 Ignored Feb 23rd Denver Round Robin 2019
273 Colorado State-B Loss 3-13 175.73 Feb 23rd Denver Round Robin 2019
170 Colorado-Denver** Loss 4-13 483.91 Ignored Feb 23rd Denver Round Robin 2019
352 Nebraska-Omaha Loss 7-14 -107.06 Mar 10th Dust Bowl 2019
- Central Arkansas Win 15-13 468.78 Mar 10th Dust Bowl 2019
336 Arkansas State Loss 10-15 87.43 Mar 10th Dust Bowl 2019
67 Oklahoma State** Loss 1-15 933.96 Ignored Mar 10th Dust Bowl 2019
434 Southern California-B Win 12-6 369.02 Mar 23rd Trouble in Vegas 2019
- Ottawa (Arizona)** Win 13-2 -167.82 Ignored Mar 23rd Trouble in Vegas 2019
261 Cal Poly-SLO-B Loss 6-9 402.57 Mar 23rd Trouble in Vegas 2019
272 Arizona State-B Loss 5-13 176.47 Mar 23rd Trouble in Vegas 2019
434 Southern California-B Win 9-2 389.71 Mar 24th Trouble in Vegas 2019
344 California-Irvine Loss 2-13 -93.73 Mar 24th Trouble in Vegas 2019
353 California-San Diego-B Loss 5-8 22.08 Mar 24th Trouble in Vegas 2019
216 Occidental** Loss 5-13 327.34 Ignored 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)