#52 Harvard (8-12)

avg: 1536.01  •  sd: 56.48  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
93 Cincinnati Win 13-11 1592.26 Feb 16th Warm Up A Florida Affair 2018
14 Florida Loss 11-13 1657.98 Feb 16th Warm Up A Florida Affair 2018
168 South Florida Win 11-10 1188.99 Feb 16th Warm Up A Florida Affair 2018
4 Minnesota Loss 8-13 1573.76 Feb 16th Warm Up A Florida Affair 2018
30 Auburn Win 13-12 1834.26 Feb 17th Warm Up A Florida Affair 2018
10 Virginia Tech Loss 11-12 1798.3 Feb 17th Warm Up A Florida Affair 2018
31 LSU Loss 12-15 1399.07 Feb 17th Warm Up A Florida Affair 2018
21 Texas A&M Loss 10-15 1368.46 Feb 18th Warm Up A Florida Affair 2018
39 Northwestern Loss 15-16 1503.7 Feb 18th Warm Up A Florida Affair 2018
23 Georgia Tech Win 15-9 2259.45 Mar 10th Tally Classic XIII
98 Clemson Win 13-12 1463.04 Mar 10th Tally Classic XIII
120 Mississippi State Win 13-10 1589.44 Mar 10th Tally Classic XIII
272 Miami** Win 13-5 1301.69 Ignored Mar 10th Tally Classic XIII
9 Georgia Loss 11-13 1720.44 Mar 10th Tally Classic XIII
16 North Carolina-Wilmington Loss 12-15 1584.02 Mar 11th Tally Classic XIII
8 Massachusetts Loss 8-15 1398.96 Mar 11th Tally Classic XIII
47 Iowa State Loss 9-13 1149.68 Mar 31st Huck Finn 2018
58 Kansas Loss 10-12 1262.74 Mar 31st Huck Finn 2018
11 Emory Loss 4-15 1320.68 Mar 31st Huck Finn 2018
49 Marquette Win 13-12 1673.36 Mar 31st Huck Finn 2018
**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)