#139 Army (15-6)

avg: 1348.35  •  sd: 76.21  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
234 Haverford Win 13-6 1599.52 Feb 24th Bring The Huckus 2024
225 Colby Win 10-5 1609.58 Feb 24th Bring The Huckus 2024
108 Vermont-B Loss 11-12 1350.03 Feb 24th Bring The Huckus 2024
267 SUNY-Geneseo Win 9-4 1471.49 Feb 24th Bring The Huckus 2024
256 Salisbury Loss 11-15 538.63 Feb 25th Bring The Huckus 2024
171 Scranton Win 13-10 1566.33 Mar 16th Free Tournament
126 Towson Win 10-9 1514.09 Mar 16th Free Tournament
364 Rensselaer Polytech** Win 10-4 1032.24 Ignored Mar 16th Free Tournament
130 Penn State-B Win 11-9 1628.62 Mar 16th Free Tournament
374 New Jersey Tech** Win 15-3 923.7 Ignored Mar 17th Free Tournament
171 Scranton Win 13-8 1734.35 Mar 17th Free Tournament
130 Penn State-B Loss 6-15 779.42 Mar 17th Free Tournament
199 Connecticut College Win 10-6 1621.91 Apr 13th Hudson Valley D III Mens Conferences 2024
364 Rensselaer Polytech** Win 13-5 1032.24 Ignored Apr 13th Hudson Valley D III Mens Conferences 2024
260 Hartford Win 13-3 1509.61 Apr 14th Hudson Valley D III Mens Conferences 2024
205 Vassar Win 15-4 1705.54 Apr 14th Hudson Valley D III Mens Conferences 2024
136 Wesleyan Loss 12-15 1068.42 Apr 14th Hudson Valley D III Mens Conferences 2024
310 Stevens Tech Win 15-7 1278.83 Apr 27th Metro East D III College Mens Regionals 2024
181 SUNY-Cortland Loss 10-16 697.05 Apr 27th Metro East D III College Mens Regionals 2024
267 SUNY-Geneseo Win 15-5 1471.49 Apr 27th Metro East D III College Mens Regionals 2024
117 Rochester Loss 11-12 1302.33 Apr 28th Metro East D III College Mens Regionals 2024
**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)