#252 SUNY-Buffalo (1-12)

avg: -863.92  •  sd: 179.51  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
250 Goucher Loss 4-5 -873.45 Feb 22nd UMBC Safari Party 2020
131 MIT** Loss 1-13 241.85 Ignored Feb 22nd UMBC Safari Party 2020
63 Towson** Loss 0-13 724.09 Ignored Feb 22nd UMBC Safari Party 2020
166 West Virginia** Loss 1-13 -44.67 Ignored Feb 23rd UMBC Safari Party 2020
246 Salisbury Loss 2-11 -1174 Feb 23rd UMBC Safari Party 2020
228 Johns Hopkins** Loss 3-10 -655.81 Ignored Mar 7th Country Roads Classic 2020
209 DePaul** Loss 0-13 -396.97 Ignored Mar 7th Country Roads Classic 2020
240 Messiah Loss 0-9 -916.13 Mar 7th Country Roads Classic 2020
205 Allegheny** Loss 3-13 -381.76 Ignored Mar 7th Country Roads Classic 2020
228 Johns Hopkins** Loss 1-9 -655.81 Ignored Mar 8th Country Roads Classic 2020
250 Goucher Win 8-6 -447.96 Mar 8th Country Roads Classic 2020
209 DePaul** Loss 1-11 -396.97 Ignored Mar 8th Country Roads Classic 2020
240 Messiah Loss 0-15 -916.13 Mar 8th Country Roads Classic 2020
**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)