#222 Mississippi State -B (12-14)

avg: 736.33  •  sd: 51.85  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
64 Georgia State Loss 8-15 847.01 Jan 20th Starkville Qualifiers
192 Harding Win 11-9 1100.31 Jan 20th Starkville Qualifiers
333 LSU-B Win 15-0 751.44 Jan 20th Starkville Qualifiers
268 Alabama-B Win 15-7 1120.94 Jan 21st Starkville Qualifiers
64 Georgia State Loss 6-13 811.82 Jan 21st Starkville Qualifiers
223 Mississippi State-C Win 12-11 858.41 Jan 21st Starkville Qualifiers
268 Alabama-B Win 9-8 645.94 Feb 3rd Black Warrior Classic
201 Alabama-Birmingham Loss 7-11 359.97 Feb 3rd Black Warrior Classic
131 Alabama-C Loss 7-11 647.61 Feb 3rd Black Warrior Classic
264 Jacksonville State Loss 8-10 279.08 Feb 3rd Black Warrior Classic
268 Alabama-B Win 11-7 987.84 Feb 4th Black Warrior Classic
131 Alabama-C Loss 4-11 514.5 Feb 4th Black Warrior Classic
264 Jacksonville State Loss 7-9 262.41 Feb 4th Black Warrior Classic
368 Southern Mississippi** Win 11-3 438.74 Ignored Feb 4th Black Warrior Classic
50 Alabama** Loss 2-13 901.57 Ignored Feb 10th Golden Triangle Invitational
119 Berry Loss 8-10 909.66 Feb 10th Golden Triangle Invitational
264 Jacksonville State Win 11-9 790.95 Feb 10th Golden Triangle Invitational
87 Tennessee-Chattanooga Loss 3-11 709.98 Feb 10th Golden Triangle Invitational
137 Union (Tennessee) Loss 7-15 490.5 Feb 10th Golden Triangle Invitational
117 Vanderbilt Loss 6-13 579.97 Feb 11th Golden Triangle Invitational
268 Alabama-B Win 12-9 866.31 Mar 23rd Magic City Invite 2024
201 Alabama-Birmingham Win 11-10 951.87 Mar 23rd Magic City Invite 2024
119 Berry Loss 5-13 572.32 Mar 23rd Magic City Invite 2024
264 Jacksonville State Win 13-5 1141.75 Mar 23rd Magic City Invite 2024
268 Alabama-B Win 12-7 1041.46 Mar 24th Magic City Invite 2024
201 Alabama-Birmingham Loss 7-13 269.33 Mar 24th Magic City Invite 2024
**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)