#320 Mississippi State-B (5-12)

avg: 603.09  •  sd: 53.48  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
101 Berry** Loss 2-13 862.45 Ignored Feb 8th Bulldog Brawl
87 Missouri S&T** Loss 2-13 907.58 Ignored Feb 8th Bulldog Brawl
303 Tennessee Tech Loss 9-10 546.79 Feb 8th Bulldog Brawl
122 Clemson** Loss 2-13 761.6 Ignored Feb 9th Bulldog Brawl
284 Harding Loss 5-15 161.43 Feb 9th Bulldog Brawl
190 Vanderbilt Loss 3-9 506.32 Feb 9th Bulldog Brawl
319 Mississippi Win 9-8 737.05 Feb 22nd Mardi Gras XXXVII
280 Texas-San Antonio Loss 8-10 514.6 Feb 22nd Mardi Gras XXXVII
305 Sam Houston Win 8-7 792.7 Feb 22nd Mardi Gras XXXVII
373 LSU-B Win 9-6 710.69 Feb 22nd Mardi Gras XXXVII
339 Alabama-B Loss 10-13 205.65 Mar 22nd 2025 Annual Magic City Invite
171 Alabama-Birmingham Loss 6-13 592.55 Mar 22nd 2025 Annual Magic City Invite
319 Mississippi Win 13-10 940.19 Mar 22nd 2025 Annual Magic City Invite
185 Union (Tennessee) Loss 4-13 529.2 Mar 22nd 2025 Annual Magic City Invite
171 Alabama-Birmingham Loss 10-15 738.94 Mar 23rd 2025 Annual Magic City Invite
324 Samford Win 11-9 847.11 Mar 23rd 2025 Annual Magic City Invite
185 Union (Tennessee) Loss 4-11 529.2 Mar 23rd 2025 Annual Magic City Invite
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)