Last week, the Predictor was 10-6 That puts me at 129-79 on the season, which is 62.0%. Still strong.
Here are the picks for Week 15:
Win % | Away | Home | Win % |
14.7% | New Orleans | Chicago | 85.3% |
29.0% | Tampa Bay | Atlanta | 71.0% |
54.1% | Washington | Cincinnati | 45.9% |
11.9% | San Francisco | Miami | 88.1% |
70.0% | Tennessee | Houston | 30.0% |
15.5% | Detroit | Indianapolis | 84.5% |
35.8% | Green Bay | Jacksonville | 64.2% |
32.7% | San Diego | Kansas City | 67.3% |
10.5% | Buffalo | N.Y. Jets | 89.5% |
75.2% | Seattle | St. Louis | 24.8% |
97.8% | Minnesota | Arizona | 2.2% |
27.5% | Denver | Carolina | 72.5% |
37.6% | New England | Oakland | 62.4% |
23.4% | Pittsburgh | Baltimore | 77.6% |
70.0% | N.Y. Giants | Dallas | 30.0% |
49.0% | Cleveland | Philadelphia | 51.0% |
Nideak asked a question last week about where I get the probabilities from, and I didn't see it until today, so I thought I'd answer him here. Basically I've taken every major stat over the past 6 years, created 4 "levels" for each one, and loaded them into a Bayesian Network, created by an algorithm that I don't remember the name of. I then enter in predicted data, which I base off of the prior 7 weeks.
One of the stats loaded into the network is "Winner", so it "knows", based on old data, what has the best chance of winning a game. Once I get all the data in for each of the categories, other than "Winner", I get a probability for each team to win, and that's what I report here.
If interested, I talked a little bit more about it here and here. Feel free to fire more questions away.