#131 MIT (7-7)

avg: 841.85  •  sd: 121.11  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
250 Goucher** Win 13-0 -148.45 Ignored Feb 22nd UMBC Safari Party 2020
252 SUNY-Buffalo** Win 13-1 -263.92 Ignored Feb 22nd UMBC Safari Party 2020
166 West Virginia Win 9-2 1155.33 Feb 22nd UMBC Safari Party 2020
97 Lehigh Loss 5-10 507.34 Feb 23rd UMBC Safari Party 2020
159 Maryland-Baltimore County Win 15-3 1197.06 Feb 23rd UMBC Safari Party 2020
63 Towson Loss 6-11 777.39 Feb 23rd UMBC Safari Party 2020
118 Syracuse Loss 8-11 585.5 Feb 23rd UMBC Safari Party 2020
112 Yale Loss 6-7 889.19 Mar 7th No Sleep Till Brooklyn 2020
82 Oberlin Loss 5-9 688.96 Mar 7th No Sleep Till Brooklyn 2020
102 NYU Loss 5-8 602.88 Mar 7th No Sleep Till Brooklyn 2020
210 Columbia-B** Win 10-3 800.24 Ignored Mar 7th No Sleep Till Brooklyn 2020
89 Brown Loss 6-10 639.83 Mar 8th No Sleep Till Brooklyn 2020
189 Princeton Win 13-2 993.43 Mar 8th No Sleep Till Brooklyn 2020
156 Amherst Win 11-6 1183.92 Mar 8th No Sleep Till Brooklyn 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)