A guest post by David Giller. Born and raised in Swampscott, MA, David attended Vanderbilt University where he was the starting longsnapper for the Commodores. He graduated summa cum laude with a degree in economics/corporate finance. David currently works as a business analyst for a Bain Capital Ventures portfolio company.
I would first like to thank Brian for his suggestion to post my study here in an effort to spark some interesting conversation and obtain some valuable takeaways. My post contains the results of a recent study I put together which focuses on the causes of sacks in NFL games. Although it is fairly detailed, I believe there are still areas of further development, some of which have been explored in an appendix to this initial study and will be coming in the second installment of this post.
As a disclaimer, the number of sacks were provided from an official source; however, the timing of the sacks, count of offensive blockers/defensive rushers was determined from my individual film study.The full piece is attached in a link, however, I have included some highlights below.
* The red portion of the trendline represents one standard deviation from the mean, the black dotted line represents the mean of the data set, and the orange dotted line represents the mean drop back and throw time of an NFL QB.
Neutral (N): The number of offensive blockers equals the number of defensive rushers
Non-leveraged (NL): Defensive rushers outnumber offensive blockers
o Of the sacks that occurred in the 2011 season, 77% were in situations where an offensive blocker was beaten physically
• Unfortunately, the reason for the quarterback taking too long to pass the ball is unclear as the data does not show whether or not the extra amount of time taken was due to the superior coverage of the defense downfield or the indecisiveness of the quarterback (a subjective opinion).
• In situations where there is a non-traditional blocking scheme, there are almost twice as many sacks when facing a non-traditional rush than a traditional rush, regardless of whether the offense is leveraged, neutral, or non-leveraged (89% difference). It is unclear what causes this discrepancy, but it would be interesting to find out why so the team can plan accordingly.