#254 Oklahoma State (6-13)

avg: 599.53  •  sd: 58.73  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
179 Missouri S&T Loss 8-10 641.44 Feb 17th Dust Bowl 2024
253 Nebraska Loss 7-11 138.78 Feb 17th Dust Bowl 2024
209 Oklahoma Loss 5-11 184 Feb 17th Dust Bowl 2024
188 John Brown Loss 10-15 408.78 Feb 18th Dust Bowl 2024
253 Nebraska Loss 8-10 343.01 Feb 18th Dust Bowl 2024
229 Northern Iowa Win 10-8 978.46 Feb 18th Dust Bowl 2024
274 Trinity Win 13-1 1103.96 Mar 9th Centex Tier 2 2024
230 Texas State Loss 7-8 589.51 Mar 9th Centex Tier 2 2024
300 Texas A&M-B Win 13-9 770.37 Mar 9th Centex Tier 2 2024
136 Houston Loss 12-15 806.71 Mar 10th Centex Tier 2 2024
172 Texas-San Antonio Loss 8-15 375.49 Mar 10th Centex Tier 2 2024
230 Texas State Loss 12-15 414.02 Mar 10th Centex Tier 2 2024
351 Kansas State Win 13-4 623.87 Mar 23rd Free State Classic
179 Missouri S&T Loss 7-12 383.59 Mar 23rd Free State Classic
180 Wisconsin-La Crosse Loss 6-10 402 Mar 23rd Free State Classic
335 Wichita State Win 13-4 721.02 Mar 23rd Free State Classic
135 Kansas Loss 7-11 640.34 Mar 24th Free State Classic
229 Northern Iowa Win 11-10 840.79 Mar 24th Free State Classic
176 Saint Louis Loss 11-12 801.24 Mar 24th Free State Classic
**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)