#72 Southern Illinois-Edwardsville (14-6)

avg: 1396.61  •  sd: 84.69  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
67 Indiana Loss 11-13 1214.4 Feb 8th Bulldog Brawl
183 Kennesaw State Win 13-8 1386.9 Feb 8th Bulldog Brawl
158 Vanderbilt Win 13-9 1421.38 Feb 8th Bulldog Brawl
110 Berry Win 15-14 1332.55 Feb 9th Bulldog Brawl
67 Indiana Loss 7-15 843.25 Feb 9th Bulldog Brawl
194 Saint Louis Win 15-6 1452 Feb 9th Bulldog Brawl
250 Illinois State Win 9-5 1141.64 Mar 1st Midwest Throwdown 2025
107 Iowa Win 9-6 1640.93 Mar 1st Midwest Throwdown 2025
385 Wisconsin-Eau Claire-B** Win 13-1 265.55 Ignored Mar 1st Midwest Throwdown 2025
253 DePaul** Win 13-4 1188.06 Ignored Mar 2nd Midwest Throwdown 2025
100 Missouri Loss 8-11 899.74 Mar 2nd Midwest Throwdown 2025
154 Macalester Win 12-8 1484.1 Mar 2nd Midwest Throwdown 2025
86 Marquette Loss 9-11 1063.32 Mar 2nd Midwest Throwdown 2025
104 Alabama Win 15-6 1838.96 Mar 29th Huck Finn 2025
39 Cincinnati Loss 8-15 1065.23 Mar 29th Huck Finn 2025
150 Kentucky Win 12-7 1572.77 Mar 29th Huck Finn 2025
90 Missouri S&T Win 15-11 1676.48 Mar 29th Huck Finn 2025
44 Emory Loss 8-11 1242.58 Mar 30th Huck Finn 2025
74 Oklahoma Christian Win 13-8 1874.25 Mar 30th Huck Finn 2025
82 St Olaf Win 9-7 1600.34 Mar 30th Huck Finn 2025
**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)