Hi Mad,

The program I am using is a form of least square regression where i input equations into my program in the form a-b=c. An example of this would be
Denver - Kansas City = 20 . This was the score differential between these two teams in Week 3. After week 3 there is 46 equations of this type which are inputed into the program. The computer then assigns numbers to each of the 32 variables (the 32 NFL teams) and then alters these values to minimise the error. Home ground advantage is taken into account as the average winning margin of home sides this season (about 6.5 at the moment). So the above equation would be changed to Denver - Kansas City = 13.5. If for example the model fitted Denver with a rating of 40 and Kansas City 20 then the error margin would be 20-13.5=6.5. The program minimises these error values across all equations. As you could imagine the R-squared value would be low and the p-value would be high suggesting a bad fit but im sure these values will improve as more equations are added.

Hope this makes sense.

Cheers
ATC