#203 Spring Hill (3-10)

avg: 1113.28  •  sd: 79.27  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
133 Arizona State Loss 7-10 985.43 Feb 24th Mardi Gras XXXVI college
82 Mississippi State Win 11-8 1948.51 Feb 24th Mardi Gras XXXVI college
370 LSU-B** Win 13-1 958.46 Ignored Feb 24th Mardi Gras XXXVI college
69 Central Florida Loss 4-13 1038.53 Feb 25th Mardi Gras XXXVI college
89 Florida State Loss 4-7 1055.12 Feb 25th Mardi Gras XXXVI college
286 Sam Houston Loss 11-12 664.48 Feb 25th Mardi Gras XXXVI college
73 Ave Maria Loss 7-13 1057.17 Mar 16th Tally Classic XVIII
69 Central Florida Loss 3-13 1038.53 Mar 16th Tally Classic XVIII
96 Notre Dame Loss 9-11 1281.78 Mar 16th Tally Classic XVIII
183 South Florida Loss 9-10 1061.53 Mar 16th Tally Classic XVIII
146 Clemson Loss 12-13 1193.35 Mar 17th Tally Classic XVIII
372 North Florida** Win 13-4 955.74 Ignored Mar 17th Tally Classic XVIII
183 South Florida Loss 7-9 907.19 Mar 17th Tally Classic XVIII
**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)