#48 Whitman (16-2)

avg: 1505.02  •  sd: 98.18  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
133 Claremont Win 11-5 1411.23 Feb 8th DIII Grand Prix 2025
52 Oregon State Win 13-7 2029.76 Feb 8th DIII Grand Prix 2025
116 Puget Sound Win 13-3 1543.82 Feb 8th DIII Grand Prix 2025
46 Carleton College-Eclipse Loss 9-12 1193.5 Feb 9th DIII Grand Prix 2025
73 Colorado College Loss 9-13 841.6 Feb 9th DIII Grand Prix 2025
67 Lewis & Clark Win 13-6 1897.81 Feb 9th DIII Grand Prix 2025
79 Portland Win 13-10 1534.9 Feb 9th DIII Grand Prix 2025
106 Montana Win 11-4 1628.43 Mar 1st Big Sky Brawl 2025
167 Montana State** Win 13-2 1222.57 Ignored Mar 1st Big Sky Brawl 2025
142 Utah State Win 8-6 1032.34 Mar 1st Big Sky Brawl 2025
240 Utah-B** Win 13-0 660.9 Ignored Mar 1st Big Sky Brawl 2025
106 Montana Win 9-7 1307.77 Mar 2nd Big Sky Brawl 2025
167 Montana State** Win 11-0 1222.57 Ignored Mar 2nd Big Sky Brawl 2025
240 Utah-B** Win 11-0 660.9 Ignored Mar 2nd Big Sky Brawl 2025
116 Puget Sound Win 13-4 1543.82 Apr 12th Northwest D III Womens Conferences 2025
193 Seattle** Win 13-2 1070.04 Ignored Apr 12th Northwest D III Womens Conferences 2025
79 Portland Win 15-4 1806.76 Apr 13th Northwest D III Womens Conferences 2025
116 Puget Sound Win 15-3 1543.82 Apr 13th Northwest D III Womens Conferences 2025
**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)