#175 Alabama-Birmingham (5-8)

avg: 932.4  •  sd: 61.05  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
220 North Georgia Win 12-9 1094.66 Feb 8th Chattanooga Classic 2020
49 Alabama-Huntsville Loss 6-13 900.69 Feb 8th Chattanooga Classic 2020
70 Middle Tennessee State Loss 7-13 819.46 Feb 8th Chattanooga Classic 2020
65 Tennessee-Chattanooga Loss 5-13 795.9 Feb 8th Chattanooga Classic 2020
215 Saint Louis Loss 11-13 542.86 Feb 9th Chattanooga Classic 2020
220 North Georgia Loss 10-11 624.3 Feb 9th Chattanooga Classic 2020
124 Sul Ross State University Loss 12-13 1002.33 Feb 29th Mardi Gras XXXIII
139 Texas Tech Loss 11-13 814.71 Feb 29th Mardi Gras XXXIII
341 LSU-B** Win 13-3 600.52 Ignored Feb 29th Mardi Gras XXXIII
62 Florida Loss 10-13 1090.72 Feb 29th Mardi Gras XXXIII
276 Mississippi Win 13-8 973.65 Mar 1st Mardi Gras XXXIII
237 Stephen F. Austin Win 13-3 1306.39 Mar 1st Mardi Gras XXXIII
230 Sam Houston State Win 11-8 1102.46 Mar 1st Mardi Gras XXXIII
**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)