I've been doing some research and regressions and have come up with a few formulas that look promising.
The first is winning percentage which has an r-squared of .77 - the inputs for this are offensive big play % (runs of 20+, receptions of 30+, KR of 40+, PR of 20+), defensive big play %, turnover margin per game, offensive yards per play (including KR, PR), defensive yards per play.
Next is winning percentage to winning margin which has an r-squared of .84 - the only input is winning percentage.
Last is a simple points predictor which has an r-squared of .85. The only inputs for this are offensive yards per play and turnover margin per game.
All of these correlations work using 2010 and 2011 stats. The formulas have been scaled to maximize results using 2011 stats, but the r-squared difference is negligible for each year.
Right now, I'm using a spreadsheet to compare team A's stats to their opponent's and then dividing by overall average. ex: (Ox*Dx)/Ax where Ox is offense, Dx is defense and Ax is the average. This gives me the projections for each game in each category I need (thank god for excel here, there are something like 50 different calculations to come up with those numbers).
Once I've calculated a winning percentage, I calculate a margin which I compare to the actual line. A five point difference is a 1 unit play, 10 points is 2, etc. I used this during the last couple weeks and the bowl season and ended up at just 55%, but up 16.2 units for an ROI of 17%. One unit plays were 7-15 (-9.5 net), two unit plays were 8-7 (.6), three unit plays were 6-1 (14.7), and four unit plays were 2-0 (8). I also experimented with O/U plays based on the points correlation and went 7-2 (2.4 - .5 unit plays) so I'm thinking there may be something there.
My question to you all is, is there a better way to use these numbers? And, considering the correlations, do you think this will prove to be profitable?
Thanks for reading.
The first is winning percentage which has an r-squared of .77 - the inputs for this are offensive big play % (runs of 20+, receptions of 30+, KR of 40+, PR of 20+), defensive big play %, turnover margin per game, offensive yards per play (including KR, PR), defensive yards per play.
Next is winning percentage to winning margin which has an r-squared of .84 - the only input is winning percentage.
Last is a simple points predictor which has an r-squared of .85. The only inputs for this are offensive yards per play and turnover margin per game.
All of these correlations work using 2010 and 2011 stats. The formulas have been scaled to maximize results using 2011 stats, but the r-squared difference is negligible for each year.
Right now, I'm using a spreadsheet to compare team A's stats to their opponent's and then dividing by overall average. ex: (Ox*Dx)/Ax where Ox is offense, Dx is defense and Ax is the average. This gives me the projections for each game in each category I need (thank god for excel here, there are something like 50 different calculations to come up with those numbers).
Once I've calculated a winning percentage, I calculate a margin which I compare to the actual line. A five point difference is a 1 unit play, 10 points is 2, etc. I used this during the last couple weeks and the bowl season and ended up at just 55%, but up 16.2 units for an ROI of 17%. One unit plays were 7-15 (-9.5 net), two unit plays were 8-7 (.6), three unit plays were 6-1 (14.7), and four unit plays were 2-0 (8). I also experimented with O/U plays based on the points correlation and went 7-2 (2.4 - .5 unit plays) so I'm thinking there may be something there.
My question to you all is, is there a better way to use these numbers? And, considering the correlations, do you think this will prove to be profitable?
Thanks for reading.
