The issue with offensive linemen is that beyond the proverbial "I know it when I see it" there is very little known about how to quantify their performance and understand their true value to a team. Clearly the 'skins would not have won the the Super Bowl, or even many games with Rypien at QB without the exceptional line play (the next season with a banged up offensive line Rypien tossed 13 TDs and 17 interceptions while being sacked a more normal 23 times). But what contribution did each of these players make individually to the team?
I have begun to tackle this question before and would like to dig deeper into the data that I have now, and expand this data set, so that we can be as confident in the results as possible. Below I will begin to further probe the data set that exists to try and understand the right directions to take, but the data collection provides the stumbling block.
One of the most important jobs of the offensive line is to provide the QB with a safe pocket in which he has plenty of time to make the right decisions. Clearly the longer a QB has to watch his receivers develop their routes, without being harassed by 350 lbs defensive ends trying to take his head off, the better his decisions are going to be, and more likely it is that the receivers will get open. I based that not on any data analysis (though the analysis does support it) but rather the knowledge that I make better decisions when I do not have 350lbs of DE rushing towards me.
This implies that to understand the value of each offensive linemen, we need to know how well they provide this safe haven for their QB. Which is exactly what I set out to do in my original stab at this problem. At the time I (with the help of my then intern Jesse Weinstein-Gould, put a stop watch on every pass play for a small group of teams, to get an idea of how long linemen could hold their blocks - how long did QBs have in their safe pocket. While this is a very time consuming project, in certainly yielded some clear results on how variability in the quality of an offensive line could effect the completion percentage of a teams' passing attack. This was done for 5 teams for the first four weeks of the 2007-08 season.
Now, looking to expand the data set, I will again (with the help my current intern Keith Goldner) put a stopwatch on every pass play (both offense and defense this time) for two teams over the course of the entire season. I will be charting the Jets and Giants all year and gathering all of the data that was originally tracked, plus some additional variables on formation and play type that will help further inform the analysis. Some of that work will appear here and some will be over at the Wall Street Journal but the goal of all of it is to enter into a massive study of the effect of individual linemen on a teams' passing attack.
As I have discussed here previously the dominant thought in the NFL is that LTs are by far the most valuable of offensive linemen (as implied by their significantly higher salaries) and therefore must have the biggest impact on a team. According to the Blind Side Hypothesis, this takes the form mostly of insurance. The LT protects the blind side of the QB (assuming he is right handed) and so keeps the QB safe (or not) from what he cannot see. As the story goes, Joe Theisman had not chance to avoid Lawrence Taylor because he could not see him coming. Thus, the data should indicate that when a LT fails to hold his assigned block, it results in a sack more often than when any other offensive linemen does.
Once we control for actual time in the pocket, this is exactly what the data shows. When a Left Tackle fails, the odds that a QB is sacked increases by over 20%. In contrast, when a Right Guard fails, the odds that a QB is sacked increase by only 9.2%.
|Probability of a Sack|
These results suggest that there is a significant difference between failures and sack totals, but does that translate into an effect on completion percentage? There the data appears to suggest that no, failure is failure when it comes to completing passes, so the higher salaries may be attributable solely to the insurance aspect: we don't want our QB getting hit too much. The differences in salary for LTs relative to other linemen and other players on the team though seem too great to be explained just by insurance. Many teams, for example, pay their left tackles more than their QB, you would not pay $1mil to insure a $500,000 asset - so it seems like their needs to be some team performance element to the salary differences.
These are just preliminary results though, as the data set currently includes only 478 plays from five different teams. As the data set grows and number of teams covered expands, the data set will be more robust which should lead to clearer results. Once we can fully evaluate the contribution of each linemen, then hopefully we will be able to at least better understand the salary structure for linemen in the NFL.