#304 Luther College (5-14)

avg: 694.97  •  sd: 60.48  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
78 Carleton College-CHOP Loss 7-13 1046.7 Mar 16th Southerns 2024
261 Georgia Tech-B Loss 6-13 304.28 Mar 16th Southerns 2024
94 Wisconsin-Eau Claire** Loss 0-13 934.71 Ignored Mar 16th Southerns 2024
78 Carleton College-CHOP** Loss 3-15 1004.23 Ignored Mar 17th Southerns 2024
215 East Carolina Loss 6-12 486.28 Mar 17th Southerns 2024
418 Wisconsin-Eau Claire-B** Win 15-5 600 Ignored Mar 17th Southerns 2024
263 Illinois State Loss 7-13 340.66 Mar 30th Old Capitol Open 2024
368 Iowa State-B Win 11-6 947.36 Mar 30th Old Capitol Open 2024
145 Southern Illinois-Edwardsville** Loss 4-13 731.75 Ignored Mar 30th Old Capitol Open 2024
227 St John's (Minnesota) Loss 7-12 509.31 Mar 30th Old Capitol Open 2024
227 St John's (Minnesota) Loss 4-13 429.82 Mar 31st Old Capitol Open 2024
320 Washington University-B Win 7-6 776.34 Mar 31st Old Capitol Open 2024
193 Grinnell Loss 7-15 554.63 Apr 13th West Plains D III Mens Conferences 2024
78 Carleton College-CHOP** Loss 3-15 1004.23 Ignored Apr 27th North Central D III College Mens Regionals 2024
193 Grinnell Loss 9-11 905.42 Apr 27th North Central D III College Mens Regionals 2024
129 Michigan Tech Loss 7-15 782.05 Apr 27th North Central D III College Mens Regionals 2024
278 St Thomas Loss 9-14 367.26 Apr 27th North Central D III College Mens Regionals 2024
362 Concordia-Wisconsin Win 15-6 1038.12 Apr 28th North Central D III College Mens Regionals 2024
270 Wisconsin-Platteville Win 15-13 1074.45 Apr 28th North Central D III College Mens Regionals 2024
**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)