#25 Pittsburgh (10-10)

avg: 1962.92  •  sd: 79.25  •  top 16/20: 6.2%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
97 Appalachian State Win 12-7 1740.85 Feb 10th Queen City Tune Up 2024
3 Carleton College** Loss 5-13 2106.55 Ignored Feb 10th Queen City Tune Up 2024
22 Notre Dame Win 11-10 2180.17 Feb 10th Queen City Tune Up 2024
37 Washington University Win 10-8 2031.31 Feb 10th Queen City Tune Up 2024
7 Tufts Loss 7-12 1999.67 Feb 11th Queen City Tune Up 2024
29 Wisconsin Win 14-10 2312.32 Feb 11th Queen City Tune Up 2024
96 Chicago Loss 11-12 1126 Feb 24th Commonwealth Cup Weekend 2 2024
21 Ohio State Win 11-10 2207.16 Feb 24th Commonwealth Cup Weekend 2 2024
52 Yale Win 15-13 1808.23 Feb 24th Commonwealth Cup Weekend 2 2024
16 Georgia Loss 5-11 1554.75 Feb 25th Commonwealth Cup Weekend 2 2024
22 Notre Dame Loss 5-11 1455.17 Feb 25th Commonwealth Cup Weekend 2 2024
35 Ohio Win 7-6 1923.14 Feb 25th Commonwealth Cup Weekend 2 2024
41 SUNY-Binghamton Win 10-3 2303.59 Feb 25th Commonwealth Cup Weekend 2 2024
24 California-Davis Win 9-5 2500.15 Mar 2nd Stanford Invite 2024
9 California-Santa Barbara Loss 4-9 1821.8 Mar 2nd Stanford Invite 2024
2 Vermont** Loss 2-10 2189.63 Ignored Mar 2nd Stanford Invite 2024
10 Washington Win 6-4 2714.39 Mar 2nd Stanford Invite 2024
15 California-San Diego Loss 9-10 2037.55 Mar 3rd Stanford Invite 2024
9 California-Santa Barbara Loss 5-8 1968.2 Mar 3rd Stanford Invite 2024
8 Colorado Loss 5-11 1858.07 Mar 3rd Stanford Invite 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)