#135 Kansas (11-9)

avg: 1107.24  •  sd: 60.62  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
211 Arizona Win 13-10 1100.94 Jan 27th New Year Fest 40
178 Brigham Young-B Win 10-6 1409.05 Jan 27th New Year Fest 40
93 Colorado-B Loss 4-13 666.1 Jan 27th New Year Fest 40
109 Denver Loss 7-12 676.33 Jan 27th New Year Fest 40
45 Utah Valley Loss 5-13 932.9 Jan 28th New Year Fest 40
193 Northern Arizona Win 13-2 1450.58 Jan 28th New Year Fest 40
128 Colorado College Loss 4-10 536 Mar 2nd Snow Melt 2024
263 Colorado-C Win 13-4 1143.59 Mar 2nd Snow Melt 2024
327 Denver-B** Win 13-5 789.75 Ignored Mar 2nd Snow Melt 2024
45 Utah Valley Loss 1-13 932.9 Mar 2nd Snow Melt 2024
128 Colorado College Loss 11-12 1011 Mar 3rd Snow Melt 2024
69 Colorado Mines Loss 10-14 970.7 Mar 3rd Snow Melt 2024
171 Montana State Win 11-7 1414.4 Mar 3rd Snow Melt 2024
188 John Brown Win 13-5 1462.39 Mar 23rd Free State Classic
176 Saint Louis Win 10-8 1188.91 Mar 23rd Free State Classic
161 Truman State Win 11-9 1241.89 Mar 23rd Free State Classic
49 St Olaf Loss 10-11 1378.16 Mar 23rd Free State Classic
188 John Brown Win 11-8 1228 Mar 24th Free State Classic
254 Oklahoma State Win 11-7 1066.42 Mar 24th Free State Classic
49 St Olaf Loss 8-15 938.36 Mar 24th Free State Classic
**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)