To get an idea of how effective a LT D'Brickashaw really is I used the data set that I have collected with the tremendous assistance of Keith Goldner. We now have 9 teams in the data set and enough pass attempts to make a first pass at evaluation. In order to evaluate linemen we will borrow from those that came before us at footballoutsiders.com (as well as many others) and compare performance to average. In this case though, what we are going to measure as performance, is the probability that, for a certain length of time, the lineman will be able to successfully hold their block.
Warning: Technical Stats Jargon in Use: Trying to estimate the average probability that a LT can hold a block for 2.5 seconds is tricky because the data is censored data. In this case, the phrase "censored data" means that on any play that a lineman holds his block successfully and the QB throws the ball after 2.5 seconds, we do not know how long the lineman could have held that block. The lineman may have been about to lose the battle, or maybe he could have continued to protect the QB for 2 or 3 more seconds...we will never know. This censoring of the data can lead to a biased estimate of the probability of success. Happily statisticians have built tools to deal with this problem, namely Cox Regression which is used in this first pass. Estimates are done by position.
Ok onto the results. Remember the linemen score reflects the probability that the player adds or subtracts from the estimated average probability of success. The results below are for the Jets offensive line as this is the team that I have the most data for and thus the best estimates. I have also included a consistency score which is the standard deviation of a player's performance on a play-by-play basis (player predicted performance - average performance). Lower consistency scores mean the player is more consistent.
The 2.2% grade for D'Brickashaw is the highest of any linemen in the data set and his consistency score of 0.07 is tied for the best consistency score in the data set. Overall, the interpretation here is that Ferguson (LT) and Moore (RG) are consistently outstanding, Mangold's performance has been about average though highly variable and Slauson and Woody have performed well below average for their positions.
As the data set continues to get bigger, these estimates will be more precise and the effects will be more clear, and more teams and players will be ranked. This analysis as is though suggests that Sanchez gets Blind Side pressure on 2.2% fewer plays than the average QB. I think Jay Cutler is probably jealous.