#210 Florida Tech (3-9)

avg: -87.42  •  sd: 222.16  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
46 Florida State** Loss 0-13 873.72 Ignored Jan 28th Florida Winter Classic 2023
216 Florida-B Win 8-4 301.3 Jan 28th Florida Winter Classic 2023
203 Miami (Florida) Loss 4-8 -519.09 Jan 28th Florida Winter Classic 2023
10 Northeastern** Loss 0-13 1534.33 Ignored Jan 28th Florida Winter Classic 2023
82 Central Florida** Loss 0-13 530.12 Ignored Jan 29th Florida Winter Classic 2023
47 Florida** Loss 0-13 867.9 Ignored Jan 29th Florida Winter Classic 2023
204 South Florida Win 4-3 159.44 Mar 11th Tally Classic XVII
86 Clemson** Loss 2-12 486.5 Ignored Mar 11th Tally Classic XVII
167 Jacksonville State Loss 4-10 -150.67 Mar 11th Tally Classic XVII
26 Notre Dame** Loss 0-13 1088.33 Ignored Mar 11th Tally Classic XVII
204 South Florida Win 6-5 159.44 Mar 12th Tally Classic XVII
193 Minnesota-Duluth Loss 5-10 -378.09 Mar 12th Tally Classic XVII
**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)