One of the most difficult relationships to evaluate in football is the offensive and defensive lines in the run game. We often settle for using various tackle statistics in order to see which players are making the most plays at or behind the line of scrimmage. There are a few problems with this approach.
First, this gives no credit to defensive players blowing up run design and reroute the ball carrier into a different defender who ends up making the tackle. Much like a sack caused by an initial pressure that flushed the quarterback, the best way to evaluate the play is to identify which player(s) were able to affect the play, even if they didn’t necessarily end up in the box score.
Second, not all positive plays for a run defender will result in a minimal gain for the offense. Much like it is possible for a defender to record a hurry on a pass play that results in a 40-yard gain, sometimes an offense is able to overcome an extraordinary effort by a defender and still deliver a successful play, so without finding a better way to measure that action, we’re not giving that defender credit.
There are even fewer reasonable metrics for evaluating blockers on run plays. The average fan has no ability to determine how good or bad a lineman is at run blocking outside of using their own eyes or relying on a player’s reputation in the media.
These are the issues we’re trying to combat with the run disruption metric. On each rushing play, Stats Perform’s video scouts look at each player on the field and record which defender or defenders were able to go above and beyond their responsibilities to beat the blocking scheme and disrupt the design of the run, as well as the blocker or blockers that allowed said defender to win their matchup.
Players don’t need to make the tackle in order to receive credit for a disruption, and the play doesn’t have to be a loss or short gain from the offense. If Aaron Donald is able to toss his blocker to the ground on an inside zone and force the running back to bounce outside, but no one is able to keep him contained and he gains 15 yards and a first down, Donald is still credited because he disrupted the original run concept the offense was trying to execute.
With this in mind, Stats Perform takes a player’s total number of disruptions and divides that by the number of snaps on which that player was in position to potentially affect the play in order to determine their disruption rate (RD%). Much the same as we previously did with pressure rate, we’ll take a look at how these rates looked among the 25th, 50th, 75th, and 100th percentiles at each position across the defensive line and offensive line in the 2019 season. A reminder, these breakdowns only include a player’s rate in the snaps they were lined up at the given position.
Nose TackleAverage nose tackle RD% is 19.2 with a standard deviation of 5.0%.
|100||Damon Harrison Sr., DET||27.7|
|75||Dexter Lawrence II, NYG||22.0|
|50||Corey Peters, ARI||20.0|
|25||Linval Joseph, MIN||15.9|
Nose tackles are the most impactful players in the run game, with an average disruption rate of 19.2%. Although Damon Harrison was widely considered a disappointment in his single season in Detroit, the current free agent is still one of the best in the league in eating up double teams and disrupting run plays in the middle.
Defensive TackleAverage defensive tackle RD% is 18.1 with a standard deviation of 5.4%.
|100||Johnathan Hankins, OAK||34.6|
|75||Timmy Jernigan, PHI||21.3|
|50||Brent Urban, CHI||18.0|
|25||Corey Peters, ARI||13.7|
Johnathan Hankins spent the majority of his snaps lined up off the center’s shoulder, but he was most effective when lined up over a guard (2-, 2i-, or 3-technique). An honorable mention goes to D.J. Reader, the second most efficient run defender at the DT position. His 33.7 RD% at DT, combined with a 23.5 RD% at NT, made him one of the top run defenders in all of football and helped him score a new free-agent deal to team up with Geno Atkins in Cincinnati.
EdgeAverage edge RD% is 11.2 with a standard deviation of 4.9%.
|100||Calais Campbell, JAX||27.6|
|75||T.J. Watt, PIT||13.9|
|50||Carl Lawson, CIN||10.8|
|25||Bruce Irvin, CAR||7.6|
As logic would indicate, edge defenders are the least impactful players in the run game on the defensive line, with a disruption on a little more than one of every 10 run snaps. Baltimore newcomer Calais Campbell comes in at the top spot among edge disruptors, which is impressive given that he was in the top 75th-percentile of DT run defenders as well. Second best on the edge was Arik Armstead, who helped anchor one of the best defensive lines in the NFL in San Francisco with a 24.7 RD%.
We’ll now switch sides of the ball and look at run disruption allowed (RD-A%).
CenterAverage center RD-A% is 11.1 with a standard deviation of 3.5%.
|100||Alex Mack, ATL||4.3|
|75||Scott Quessenberry, LAC||9.6|
|50||Jason Kelce, PHI||10.9|
|25||Weston Richburg, SF||13.5|
As mentioned in the breakdown of our pressure metrics previously, run blocking is far more important than pass blocking from the center position because they are the ones most often tasked with blocking nose tackles. No one is better at winning his matchups than Falcons’ center Alex Mack, which should make Todd Gurley happy in his new home.
Left GuardAverage left guard RD-A% is 11.1 with a standard deviation of 4.6%.
|100||Ali Marpet, TB||6.5|
|75||Ereck Flowers Sr., WAS||8.7|
|50||Laken Tomlinson, SF||10.7|
|25||Dan Feeney, LAC||14.1|
Right GuardAverage right guard RD-A% is 12.1 with a standard deviation of 4.4%.
|100||Brandon Scherff, WAS||5.0|
|75||Michael Schofield III, LAC||10.1|
|50||Josh Kline, MIN||12.9|
|25||Evan Boehm, MIA||14.8|
Much like NTs and DTs on the other side of the ball, the average RD-A% among guards and centers is extremely similar. Washington was among the strongest teams in the league with its interior run blocking. Brandon Scherff (No. 1 RG), Erick Flowers (No. 10 LG), and Chase Roullier (No. 6 C) were all near the top in their respective positions.
Left TackleAverage left tackle RD-A% is 8.7 with a standard deviation of 3.2%.
|100||Laremy Tunsil, HOU||3.2|
|75||Jason Peters, PHI||7.0|
|50||Kelvin Beachum, NYJ||8.8|
|25||Joe Staley, SF||10.5|
Right TackleAverage right tackle RD-A% is 9.7 with a standard deviation of 3.6%.
|100||Ryan Ramczyk, NO||4.3|
|75||Halapoulivaati Vaitai, PHI||7.3|
|50||Rick Wagner, DET||9.6|
|25||Germain Ifedi, SEA||12.6|
The top tackles in run disruption allowed are of very little surprise to those familiar with offensive line play. Laremy Tunsil and Ryan Ramczyk are followed at their respective positions by Ronnie Stanley (3.4%) and Mitchell Schwartz (5.8%). All four were recognized as first- or second-team All-Pros among various media outlets.
What they see, we quantify.
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