By Brian Burke
As a measure of production I used Expected Points Added (EPA)--actually EPA per game to account for injury shortened seasons. For the measure of player value, I used cap hit. Cap value is useful because it boils down the complexity of many NFL contracts into one number. It can be tricky, though, as many contracts can be quite uneven from year to year in terms of cap value. For cap management and player-incentive purposes a 4-yr/$40M will often diverge far from a steady $10M per year cap hit. To account for this, I averaged each players' per year cap hit for the full period ('06-'12) and plotted against each player's EPA/G. The purpose of doing this is to see what level of production teams expect per $1M of salary. Is there a solid connection between true production and salary?
There are assumptions and limitations inherent in this analysis. Player production is dependent on the abilities of their teammates. WRs and TEs rely on their QBs to get them the ball, and some will have better passers and some will have worse, and vice versa. RBs are dependent on their line and scheme. But over the league as a whole, these considerations would (ideally) balance out. Put simply, for every Larry Fitzgerald being victimized by the offense around him, there's a Brandon Lloyd benefitting from being on a great offense.
The chart below plots offense skill position production by annual average cap hit. Each position is color coded.
The trend lines show that the offensive skill positions have different connections between production and salary than others. The more diagonal the line, the stronger the connection. The order is QB, TE, WR, and RB. (Note: I set the minimum avg cap value to $500k and minimum game appearances to 7 per season to focus on the players meant to be starters. Raising the minimum cap value up through $2M doesn't change the general results above. Above that there are so few players that the results become spurious.)
This result points to how consistent a player's abilities can be assessed and predicted at each position. Perhaps QBs can be evaluated and assessed more accurately than the other positions.
It may also say something about how heavily dependent a position's production is on factors beyond his control. RB production may be so overwhelmingly dependent on line and scheme that a player's underlying ability is swamped.
Random factors may affect the positions in different ways. For instance, a few extra lost fumbles can erase an entire season's worth of production for a RB. Or perhaps injuries, which are largely random, affect positions in different ways.
The correlations are as follows:
All the correlation values are significant at the .01 level except for the RBs, which was not significant.
This is just a first cut, but I wanted to document things at this stage. Next, I'd like to eliminate all the seasons for which a player was under his rookie contract, leaving only the relatively free market of free agents in the data. As an aside, it's interesting to see how stark the pay differences are between the top QB picks like Ryan and Sanchez, who had their rookie contracts done prior to the new CBA, and more recent picks such as Luck, Griffin, and Newton. And if we didn't already know it, Russell Wilson appears to be quite the steal.