#118 Michigan Tech (7-8)

avg: 1173.62  •  sd: 67.12  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
226 Embry-Riddle Win 13-10 1058.14 Mar 2nd FCS D III Tune Up 2024
51 Franciscan Loss 10-13 1168.14 Mar 2nd FCS D III Tune Up 2024
217 Kenyon Win 13-6 1358.95 Mar 2nd FCS D III Tune Up 2024
174 North Carolina-Asheville Win 13-7 1494.01 Mar 2nd FCS D III Tune Up 2024
125 Davidson Loss 9-13 728 Mar 3rd FCS D III Tune Up 2024
163 Xavier Win 13-8 1469.63 Mar 3rd FCS D III Tune Up 2024
80 Lewis & Clark Loss 10-13 1011.54 Mar 3rd FCS D III Tune Up 2024
82 Central Florida Win 10-8 1599.94 Mar 30th Huck Finn 2024
67 Chicago Loss 10-11 1262.02 Mar 30th Huck Finn 2024
204 Ohio Win 13-3 1409.59 Mar 30th Huck Finn 2024
83 Northwestern Loss 9-12 990.12 Mar 30th Huck Finn 2024
53 Colorado State Loss 7-13 913.02 Mar 31st Huck Finn 2024
105 Mississippi State Loss 11-12 1085.79 Mar 31st Huck Finn 2024
108 Wisconsin-Milwaukee Win 10-9 1324.7 Mar 31st Huck Finn 2024
76 Purdue Loss 5-13 757.22 Mar 31st Huck Finn 2024
**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)