#124 Macalester (11-8)

avg: 1146.58  •  sd: 70.76  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
78 Carleton College-CHOP Loss 8-12 907.79 Feb 10th Ugly Dome 2024
140 Minnesota-B Win 12-10 1316.16 Feb 10th Ugly Dome 2024
299 Minnesota-C Win 10-7 747.21 Feb 10th Ugly Dome 2024
49 St Olaf Loss 9-10 1378.16 Feb 10th Ugly Dome 2024
95 Wisconsin-Eau Claire Loss 4-13 650.03 Feb 10th Ugly Dome 2024
83 Northwestern Loss 8-11 969.87 Mar 2nd Midwest Throwdown 2024
176 Saint Louis Win 9-5 1455.3 Mar 2nd Midwest Throwdown 2024
259 Wisconsin-B Win 8-7 685.43 Mar 2nd Midwest Throwdown 2024
78 Carleton College-CHOP Loss 5-8 895.34 Mar 3rd Midwest Throwdown 2024
170 Minnesota-Duluth Loss 3-4 825.77 Mar 3rd Midwest Throwdown 2024
161 Truman State Win 8-6 1293.18 Mar 3rd Midwest Throwdown 2024
95 Wisconsin-Eau Claire Loss 6-9 831.46 Mar 3rd Midwest Throwdown 2024
140 Minnesota-B Win 7-6 1203.04 Mar 23rd Minneapolis Makeup
265 Eastern Michigan Win 9-4 1133.93 Mar 30th Old Capitol Open 2024
255 St John's (Minnesota) Win 13-6 1184.96 Mar 30th Old Capitol Open 2024
180 Wisconsin-La Crosse Win 10-3 1498.16 Mar 30th Old Capitol Open 2024
69 Colorado Mines Win 8-7 1494.4 Mar 31st Old Capitol Open 2024
93 Colorado-B Win 10-6 1762.26 Mar 31st Old Capitol Open 2024
81 Iowa Loss 7-9 1058.27 Mar 31st Old Capitol Open 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)