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Chicago Bears Number Mill: 2018 Free Agent Edge Rushers

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On my ongoing number mill series, I will grind through the bark of NFL statistics in the hopes of turning negative logs into positive planks...constant.

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Seattle Seahawks v Chicago Bears
Technically a free agent, future Hall of Famer Julius Peppers is a statistical anomaly. Here he is at his best dressed.

Previously on Number Mill: Cam Meredith | Markus Wheaton | Dontrelle Inman | Chiefs Offense | FA Receivers 1 | FA Receivers 2 |

Before I start, I have to give a special thanks to WCG community member BOBdaBEAR for creating the terrific windmill graphic you see above. Although I imagined the number mill as a lumber mill, I don’t imagine one could make a lumber mill graphic as cool as this, I’m not a metaphor purest, and I’m not one to turn down free legitimately-elite graphics.


The sack is an elusive, fickle beast. There are clean-up sacks and coverage sacks, and there are unbelievable pass-rush efforts that are narrowly averted by dumb luck. It seems like every year the NFL has a different sack leader, and the all-time sack record has been held for years by a man who may be a better talk show host than he was a pass rusher—not to say that Michael Strahan was not a very good pass rusher, but let’s admit, he is excellent on television.

Using their 12-year database, Pro Football Focus looked at how well a player’s previous sack numbers correlated with the next year’s sacks and reported a very underwhelming correlation coefficient of 0.49 (r-squared 0.24). Since explaining correlation coefficients and r-squared would make me sound prohibitively nerdy, I will just tell you this means that previous years’ sack counts do not correlate well with this year’s sack counts. Pressure counts performed better in their analysis, with a correlation coefficient of 0.71 (r-squared 0.51) and past pressures actually correlated with future sacks better than past sacks did (correlation coefficient 0.55 r-squared 0.30).

With this in mind, when looking at potential free agency targets, it seems prudent to look at pressures as well as sacks. This should help get a more accurate picture of a player’s production and may identify players who are undervalued or overvalued based on sack counts alone. Below, I have listed all projected 2018 edge free agents including their pressure rates (combined hurries, hits, and sacks per pass rush snap) as well as their sack totals and how many pass rushes they attempted for each sack. Pass rush snaps, hit counts, and hurry counts are all courtesy of PFF.

This table is sorted by pressure production over the past three years. Demarcus Lawrence tops the list, but nobody expects him to make it to free agency. He is also probably overvalued, coming off his best year and requiring one of the highest pass rush snap counts to accumulate those numbers. His efficiency on a per rush basis was similar to several others on the list, including Ziggy Ansah and Dwight Freeney, and even some lower-profile players such as Trent Murphy and Aaron Lynch.

More on Sacks vs. Pressures

Pressures are more consistent year to year than sacks, but sacks are undeniably more valuable than pressures. To look into this further, I decided to see if there are any interesting trends in the ratio of sacks to total pressures, so I tracked the % of total pressures that resulted in sacks in all the free agents who had at least one sack over the past three years. Since sacks vary significantly while pressures stay more stable, we would expect this percentage—which I’m calling sack conversion rate (SCR)—to vary year to year for each player. It would make sense, however, that there could be significant variation between players—after all some players must be better at “getting home” “finishing the job” or “suffocatingly smoshing” opposing quarterbacks.

The table below shows sack conversion rates for each of the last three years, as well as each player’s average SCR and the difference between each player’s highest and lowest rates, with averages among all players at the bottom.

First, can we take a second to admire Connor Barwin? As expected, an individual player’s sack conversion rate bounces wildly from year to year. In most cases, the difference between the highest and lowest rate is actually larger than the average rate. In most cases. Except Connor “Strong and Steady” Barwin, who has absolutely no variation between years. It seems very possible that Barwin is a robot who was programmed to get exactly one sack every six pressures. Either that, or he’s the low-end outlier that balances out Kareem Martin, who had one sack on one pass rush snap in 2016 then one sack among 20 pressures in 219 pass rush snaps in 2017. Or perhaps Martin is another robot who was re-calibrated after 2016 because his 100% sack rate raised too much suspicion. We’ll have to check back after 2018 numbers come out to sort this out.

Next, let’s take a second to actually admire former Bear and future Hall-of-Fame edge rusher, Julius Peppers, who single-handedly demonstrates that there is variation in sack conversion rates between players. Peppers’ average conversion of 26%, is almost 10% above the next best pass rusher, and helps explain why he has continued to be such an impressive sack producer despite a worsening pressure percentage in his golden years.

While most of these players convert pressures to sacks at a rate near the 15% average, there are definitely differences between players, and those differences are large enough to have a significant effect on their actual value on the field.

Valuing sacks and pressures appropriately?

Evaluating a player based on sack production alone is clearly limited, mostly because of how much variation there is in player sack production from year to year. With players that have a small sample-size and a particularly large or small number in the most recent year, this issue can combine with recency bias to lead to some big errors in valuation. But evaluating players on pressures alone is also limited since there is plenty of variation between players on how well they convert pressures to sacks—which are definitely more valuable.

If only someone could create a single metric to incorporate both in a way that makes it easy for the lazy among us to compare pass rushers with one number! PFF tried that with a metric called Pass Rushing Productivity (PRP) but it overvalues hurries and hits (at 75% of a sack) and is extremely limited by its unequivocally lame acronym.

All we need to fix the problems with PRP is to get appropriate values for hits and hurries and come up with a cool acronym. For the first part of this, I had to look no further than—perhaps ironically—a recent PFF tweet:

Eric Eager seems to have done a pretty good analysis here, looking at how much value (in the form of a unit called expected points added) comes from a passing play based on the level of pressure. As you might guess, the negative points are bad for the offense and good for our potential-Bear edge rushers. As the infographic shows, a sack turns a “no pressure” passing play that would give an offense around 0.2 points into a negative play costing the offense around 1.8 points (a roughly 2 point difference). A hurry on the other hand, only drops the value of the play to about 0 points (or a roughly 0.2 point difference). This analysis separates hits based on whether they are both hurried and hit or just hit, but nicely located between those two values is a play that would cause a 0.5 point swing—one quarter the value of a sack.

You see where I’m going right? Based on Eager’s analysis, the value of a hurry as about 1/10th that of a sack, and the value of a hit is about 14 that of a sack. These numbers are nice and even and pass the sniff test for me. And now that we have the ratios, we can ditch the clunky EPA units and just say that a hurry equals 0.1 sack equivalents, a hit equals 0.25 sack equivalents and a sack equals (duh) 1.0 sack equivalents.

Now for the best part: the acronym. Adding up all a players sack equivalents, then dividing those by their number of pass rushes, then multiplying by 100 so we get a better looking number, I present to you a new metric—a player’s sack equivalents per 100 pass rushing snaps: their Sack Attack Quotient (SAQ).

This metric, included in the table below, is in all ways better than the lowly PRP.

Come at me PFF! Seriously. Literally @ me. I need the exposure.

First off—holy sack attack, Dion Jordan! Obviously, that’s a small sample size, but the efficiency is insane and if Seattle doesn’t put a first-round tender on him, I want him doing that in Navy and Orange despite his “bust” status.

Potential Bear Targets?

I think this was the point of the article when I started on it. After a long day at the number mill, you lose track of this sort of thing.

In terms of top tier free agents, it’s really only Ziggy Ansah (assuming Lawrence stays with the Cowboys). There’s no guarantee that Ansah hits the market, but his production is among the best on every metric despite a down year in 2016. He’s older than I expected, but I think he’ll be worth the contract he gets—and I wouldn’t be mad if the Bears could poach him from a division rival.

After Ansah, there are a lot of older players who still have decent production—including current Bear Lamarr Houston—but this isn’t a player profile that has interested Pace much in the past. The Bears already have old-and-decent pass rushers on the roster. The goal in free agency should be to get younger and healthier (with potential upside) at the position.

So who fits that profile? Aaron Lynch stands out as a good value candidate who produced well when given the opportunity and is coming off a down year on a team that just converted from a 3-4 to a 4-3 front. That team has also drafted several edges high in the last few years. Interestingly, that same team (the 49ers if you haven’t guessed it) was running Vic Fangio’s defense when they drafted Lynch, and Fangio may have his eye on bringing him back under his wing.

Jerry Attaochu also stands out as an interesting buy low sleeper. He has has shown good production in limited opportunity due to injuries—I know, scary!—and a crowded depth chart. He might not have a long-term place on his current team sitting behind Joey Bosa and Melvin Ingram. Trent Murphy certainly has promising numbers if Washington lets him walk after his missed 2017 due to injury—him too!?. Alex Okafor doesn’t quite light up the metrics, but he’s also impressive against the run and coming off a career year.

Barkevious Mingo doesn’t have great 3 year numbers, but showed a lot of growth in 2017. Chris Smith is a bargain-bin option with decent production and a terrific sack dance. Finally, restricted free agents Matt Longacre and Chris McCain will be worth a look if they don’t get tendered.

There’s not a lot at the top end of this edge class, but there are a lot of young players who have shown potential and I expect the Bears will be able to land one or two of them on reasonable contracts.

Whoever they are, they will immediately become my favorites.