#58 Davenport (15-1)

avg: 1403.13  •  sd: 79.44  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
141 Catholic** Win 9-1 1334.02 Ignored Feb 15th 2025 Commonwealth Cup Weekend 1
50 Liberty Loss 3-10 889.97 Feb 15th 2025 Commonwealth Cup Weekend 1
84 Richmond Win 10-5 1722.76 Feb 15th 2025 Commonwealth Cup Weekend 1
81 Tennessee Win 9-6 1615.5 Feb 16th 2025 Commonwealth Cup Weekend 1
102 Virginia Tech Win 6-2 1649.35 Feb 16th 2025 Commonwealth Cup Weekend 1
131 Grand Valley Win 10-2 1414.79 Mar 15th Davenport Spring Skirmish
110 Michigan State Win 6-3 1552.72 Mar 15th Davenport Spring Skirmish
199 Oberlin Win 5-4 565.83 Mar 15th Davenport Spring Skirmish
87 Michigan Tech Win 8-6 1434.41 Mar 16th Davenport Spring Skirmish
131 Grand Valley Win 9-1 1414.79 Mar 16th Davenport Spring Skirmish
87 Michigan Tech Win 7-4 1630.08 Mar 16th Davenport Spring Skirmish
127 Butler Win 12-3 1445.17 Apr 12th Great Lakes D III Womens Conferences 2025
231 Kalamazoo** Win 10-0 752.76 Ignored Apr 12th Great Lakes D III Womens Conferences 2025
144 Knox** Win 10-3 1325.69 Ignored Apr 12th Great Lakes D III Womens Conferences 2025
127 Butler Win 13-3 1445.17 Apr 13th Great Lakes D III Womens Conferences 2025
231 Kalamazoo** Win 13-0 752.76 Ignored Apr 13th Great Lakes D III Womens Conferences 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)