#74 Indiana (11-9)

avg: 1211.97  •  sd: 59.09  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
92 Tennessee Win 14-13 1208.19 Jan 27th Carolina Kickoff 2024
34 South Carolina Loss 6-15 960.75 Jan 27th Carolina Kickoff 2024
25 North Carolina-Wilmington Loss 9-12 1321.78 Jan 27th Carolina Kickoff 2024
76 Georgetown Win 11-10 1330.59 Jan 28th Carolina Kickoff 2024
122 Lehigh Win 11-10 1066.93 Jan 28th Carolina Kickoff 2024
124 Davidson Win 14-6 1531.22 Jan 28th Carolina Kickoff 2024
23 McGill Loss 9-15 1194.09 Feb 10th Queen City Tune Up 2024
58 Virginia Win 11-10 1455.57 Feb 10th Queen City Tune Up 2024
4 North Carolina** Loss 4-15 1513.05 Ignored Feb 10th Queen City Tune Up 2024
25 North Carolina-Wilmington Loss 10-14 1268.44 Feb 10th Queen City Tune Up 2024
76 Georgetown Loss 12-14 984.64 Feb 11th Queen City Tune Up 2024
88 Notre Dame Win 13-8 1608.86 Feb 11th Queen City Tune Up 2024
46 Florida Loss 9-12 1084.49 Feb 24th Mardi Gras XXXVI college
99 LSU Win 11-8 1397.61 Feb 24th Mardi Gras XXXVI college
182 Texas State Win 12-7 1019.95 Feb 24th Mardi Gras XXXVI college
213 Texas Tech** Win 13-3 857.32 Ignored Feb 24th Mardi Gras XXXVI college
86 Florida State Win 13-11 1357.41 Feb 25th Mardi Gras XXXVI college
45 Texas A&M Win 10-9 1555.98 Feb 25th Mardi Gras XXXVI college
52 Tennessee-Chattanooga Loss 4-13 768.39 Feb 25th Mardi Gras XXXVI college
62 Central Florida Loss 2-9 690.18 Feb 25th Mardi Gras XXXVI college
**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)