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Are All Sacks Created Equally? A Closer Look at Mack, Watt, Garrett, and Dumping the Passer

A closer looks at sack statistics, and how they can be improved.

“QB’s are overpaid, overrated, pompous bastards and must be punished… A quarterback has never completed a pass when he was flat on his back.”

– Buddy Ryan

Photo: Jonathan Daniel/Getty Images

From 2017-2019, when the quarterback was kept upright (as in not sacked), NFL offenses scored on 38% of drives. On drives where the quarterback took a sack, the offense scored only 22% of the time. In this installment of Navigating Bear Markets, we are going to look at alternative ways to break out sacks for edge rushers by diving into the stats for edge players that rarely leave the field.

We hear about padding stats in garbage time and against bad teams all the time in regards to QB stats. But why don’t we ever take it into consideration for other positions? I certainly think it matters for sacks, and that’s what we are looking at in this installment of Navigating Bear Markets.

Thought Process

Sacks come in all types of shapes and sizes. Bull rushes, butt fumbles, decapitations, shoestring takedowns, head-on collisions, and blindside takedowns. They all count the same in the stat book: one sack. What about the sacks that come late in the fourth quarter when defending a multi-score lead? How about when the fifth-round rookie QB looks like a deer in the headlights after replacing the injured starter? Then we have the career backups. There is a reason they aren’t starting, and it’s not because the breakout year is right around the corner.

Sacks are often not the fault of the offensive line. If only it were that simple. In fact, sack rates are one of the most consistent stats when a QB changes teams. A QB who takes fewer sacks gets the ball out fast, is decisive, avoids playing hero ball too often, and knows where the ball is supposed to go. These are traits that backup QB’s rarely excel at, and even when they are capable, they often have other limitations that make them more prone to taking sacks.

Which brings me to my next point. When the defense has the lead, there are certain advantages. The passing downs become more identifiable, and the pass rushers are able to tee off toward the QB off the snap. Also, the offenses may not have the luxury of taking their time and running the football, resulting in a need for chunk plays. This means that the QB is more likely to take deeper drops and hold the ball for longer as routes progress, giving the edge rushers more time to get home.

Data Set

For this piece, I am only analyzing edge rushers, more namely, full-time edge rushers. I am not including situational edge players. To qualify for the dataset, the player must have been on the field for 50-plus snaps per game, and 600-plus snaps in total. This resulted in 23 edge rushers for the dataset.

All sack totals were pulled from PFF, with play details pulled from stathead.com. PFF sack totals tend to vary slightly from other sites due to certain specifics in the way they are counted and credited.

Types of Sacks

Sacks are divided into three categories:

Garbage Time Sacks: Sacks that occurred while leading by ten points or more in the fourth quarter, or by 17 points or more in the third quarter.

Backup QB Sacks: Sacks on backup QB’s. For our purposes, when a backup QB was sacked in garbage time, it was excluded from “Backup QB Sacks” and included in “Garbage Time Sacks”.

High Impact Sacks: These are all other sacks. Generally, these are sacks that have a more real impact on the game, and are more comparable league wide.

*Note: QB’s for CHI and WFT were not considered to be “backups” due to the fluid situations for these teams in 2020

Biggest Drop-Offs:

Haason Reddick (ARZ):

  • Reddick totaled five garbage time sacks, with four occurring in the fourth quarter. He added another four sacks on backup QB’s.
  • This results in only four high impact sacks for Reddick on the season, ranking 14th within the data set and accounting for only 31% of his sack total.

Chase Young (WFT):

  • Young had one garbage time sack, up by ten points in the fourth quarter against the Eagles with three minutes remaining. Additionally, Young’s hit list includes three sacks of backup QB’s.
  • This results in only two high impact sacks for Young on the season — a large decrease from his original count of 15, but still tied for fourth-most among the group.

Za’Darius Smith (GB):

  • Smith accumulated five garbage time sacks, with the Packers consistently building large leads early in games. Only two of Smith’s sacks came against backup QB’s.
  • The result is a respectable six high impact sacks on the season, ranking seventh within the data set and making up 46% of his season total.

Biggest Gains:

Khalil Mack (CHI):

  • Mack only had one garbage time sack on the season, and did not have any sacks of backup QB’s. This was largely because the Bears only saw significant snaps by one backup QB on the season (Mike Glennon; JAX).
  • A whopping 90% of Mack’s sacks classify as “High Impact”. He totaled nine high impact sacks on the year, ranking second within the group.

Maxx Crosby (LVR):

  • Crosby only accumulated one garbage time sack. The Raiders hung around on the scoreboard in most games thanks to their eighth-ranked scoring offense, creating little opportunity for garbage time sacks. He had no sacks of backup QB’s.
  • 89% of Crosby’s sacks are defined as “High Impact”. He totaled six high impact sacks on the season, ranking seventh within the data set.

Myles Garrett (CLE):

  • Garrett notched three garbage time sacks due to the Browns’ propensity to jump out to large leads. He did not have a single sack against backup QB’s.
  • Garrett led the group in high impact sacks with ten. This accounted for 77% of his sacks on the season.

*Note: Olivier Vernon ranked second in high impact sack rate, however, due to him being the #2 edge rusher on the roster and Myles Garrett leading the group in high impact sacks, Garrett was bumped up.

Leading, Tied, or Trailing

In order to account for point differential, I looked at whether each team was leading, tied, or trailing when each sack occurred. Next, I looked up each team’s snap counts against the pass when leading, tied, or trailing. I used these two inputs to determine each players sack rate (sacks divided by pass snaps) in each situation.

Equal Snap Sacks:

Through my accumulation of data, I was able to determine that the average player in the group played 165 pass snaps when trailing, 99 pass snaps when tied, and 336 pass snaps when leading. Using this information, combined with each individual player’s sack rates when leading, tied, or trailing, I was able to generate a stat that I am calling “Equal Snap Sacks”. This is projecting sack totals if all snaps when leading, tied, or trailing were equal across the group of players.

Point Differential Factor:

Additionally, this stat gave me the idea to think the difference between Total Sacks and “Equal Snap Sacks” as being a point differential factor. For example, Bradley Chubb was involved in eight sacks in 2020. “Equal Snap Sacks” indicates that he would have generated 9.4 sacks had he had opportunities equal to the group average. Therefore, the “PD Factor” (PD standing for Point Differential) for Chubb comes in at -1.4.

This translates to the failures of the offense costing Chubb 1.4 sacks on the stat sheet. Alternatively, Preston Smith had a “PD Factor” of +1.3. This means that the Packers offensive production garnered him 1.3 more sacks than he would have otherwise generated in an average situation.

Negated Sacks:

Finally, we get to “Negated Sacks”. These are sacks that were negated due to penalties called against the edge rushers teammates. This stat does not include sacks that were negated by penalties called against the edge rusher himself.

Sack Index:

The combination of “Equal Snap Sacks” and “Negated Sacks” results in what we are calling “Sack Index”. This represents the edge rusher’s sack total had it not been for the offense’s inability to pull its weight and the penalties that the edge rusher had no control over.

Biggest Dropoffs

Preston Smith (GB): -1.39 Sacks

Jason Pierre-Paul (TB): -0.99 Sacks

Frank Clark (KC): -0.82 Sacks

Biggest Gains:

Khalil Mack (CHI): +3.88 Sacks

Bradley Chubb (DEN): +1.41 Sacks

Leonard Floyd (LAR): +0.941 Sacks

Other Metrics

There are two final stats that I want to touch on:

  • Percent of Games with a Sack: This metric is pretty simple. Basically turning sacks into a binary stat. Take how many games that each player was involved in a sack in any capacity, and divide it by the total games played that season. This helps us to understand how consistent each player is in getting home at least once per game. It also helps to divide out the games where a rookie sixth-round pick was starting at left tackle, or an edge rusher just had a dominant advantage that does not typically exist.
  • Percent of the team’s total sacks: This helps us to understand how much help the edge rusher has around them. Edge players who have a higher percentage of their team’s sacks are dominating the game despite being the largest threat on the field by a longshot. Players who have a lower percentage of their teams sacks may be a second- or third-best pass rusher on the team, and not see double teams or chips as often.

Most Consistent Week to Week:

  • TJ Watt (PIT): Had a sack in 73% of games played.
  • Myles Garrett (CLE): 71%
  • Bud Dupree (PIT): 64%
  • Jason Pierre-Paul (TB): 63%
  • Za’Darius Smith (GB): 63%
  • Khalil Mack (CHI): 56%

Most Dominant on Team:

  • Brian Burns (CAR): Accounted for 34.5% of his teams sacks.
  • Myles Garrett (CLE): 34.2%
  • Maxx Crosby (LVR): 33.3%
  • Za’Darius Smith (GB): 31.7%
  • Khalil Mack (CHI): 28.6%

Final Sack-Man Rankings

Rankings are simply based on the average rank for each category discussed above. I chose not to do any weighting on the averages to keep it transparent.

You can check out previous installments of Navigating Bear Markets HERE, and follow me @ButkusStats for more nerdy spreadsheets, @BearsOnTap for more Bears coverage, and @OnTapSportsNet for coverage of all Chicago sports.


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