#242 Butler (5-9)

avg: 668.37  •  sd: 73.1  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
257 Air Force Loss 11-13 342.52 Mar 2nd FCS D III Tune Up 2024
217 Kenyon Loss 10-12 520.83 Mar 2nd FCS D III Tune Up 2024
199 Messiah Loss 11-13 603.4 Mar 2nd FCS D III Tune Up 2024
163 Xavier Loss 6-13 373.48 Mar 2nd FCS D III Tune Up 2024
150 Navy Loss 6-13 434.29 Mar 3rd FCS D III Tune Up 2024
99 Elon Loss 6-13 642.51 Mar 3rd FCS D III Tune Up 2024
59 Whitman** Loss 0-13 836.78 Ignored Mar 3rd FCS D III Tune Up 2024
305 Penn State-Behrend Win 13-3 929.4 Mar 23rd Butler Spring Fling
318 Rose-Hulman Win 11-6 813.83 Mar 23rd Butler Spring Fling
163 Xavier Loss 10-12 735.35 Mar 23rd Butler Spring Fling
205 Ball State Win 9-6 1224.36 Mar 24th Butler Spring Fling
155 Grace Loss 7-13 464.7 Mar 24th Butler Spring Fling
262 Loyola-Chicago Win 10-4 1145.98 Mar 24th Butler Spring Fling
354 Indiana-B Win 10-7 399.97 Mar 24th Butler Spring Fling
**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)