#241 Xavier (2-17)

avg: 899.56  •  sd: 54.65  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
159 Brandeis Loss 6-13 617.2 Mar 1st D III River City Showdown 2025
33 Elon** Loss 4-13 1225.66 Ignored Mar 1st D III River City Showdown 2025
81 Rochester Loss 7-11 1071.61 Mar 1st D III River City Showdown 2025
230 Air Force Win 11-9 1177.11 Mar 2nd D III River City Showdown 2025
143 Davidson Loss 9-10 1153.6 Mar 2nd D III River City Showdown 2025
170 Messiah Loss 6-13 583.27 Mar 2nd D III River City Showdown 2025
129 Asbury Loss 3-13 724.98 Mar 23rd Butler Spring Fling 2025
127 Butler Loss 7-13 777.66 Mar 23rd Butler Spring Fling 2025
112 Hillsdale Loss 7-9 1096.77 Mar 23rd Butler Spring Fling 2025
132 Kenyon Loss 5-15 715.76 Apr 12th Ohio D III Mens Conferences 2025
144 Oberlin Loss 9-11 1021.07 Apr 12th Ohio D III Mens Conferences 2025
212 Cedarville Loss 7-13 457.64 Apr 13th Ohio D III Mens Conferences 2025
212 Cedarville Win 10-8 1277.83 Apr 26th Ohio Valley D III College Mens Regionals 2025
66 Franciscan** Loss 5-13 1023.97 Ignored Apr 26th Ohio Valley D III College Mens Regionals 2025
180 Grove City Loss 8-12 703.92 Apr 26th Ohio Valley D III College Mens Regionals 2025
170 Messiah Loss 11-12 1058.27 Apr 26th Ohio Valley D III College Mens Regionals 2025
196 Haverford Loss 10-13 740.25 Apr 27th Ohio Valley D III College Mens Regionals 2025
170 Messiah Loss 11-12 1058.27 Apr 27th Ohio Valley D III College Mens Regionals 2025
144 Oberlin Loss 11-13 1041.44 Apr 27th Ohio Valley D III College Mens Regionals 2025
**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)