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Advanced Defensive Stats: Pass Rush

| July 14th, 2020

I’m continuing to look at Chicago’s defense using advanced defensive statistics from Pro Football Reference (PFR). I already looked at missed tackles and coverage, and today I want to look at pass rush.


Expected Sacks

In general, sacks are fairly variable from year-to-year due to their small sample size. Accordingly, they are not a very good way to evaluate a pass rusher, just like rushing or receiving touchdowns (which also have a small sample size) are not the main way we evaluate skill position players.

This is where advanced statistics can give us a more helpful overall picture of a pass rusher’s performance. The PFR database tracks total QB pressures, which gives you a larger sample size and thus should be more reflective of the player’s performance.

I was curious about the relationship between total pressures and sacks, so I took the following steps to investigate:

  • I examined all rushers between 2018-19 (the only 2 years this database has) who had at least 15 pressures in a year; I chose this threshold to look only at full-time pass rushers. This gave me a data set of 215 seasons, or roughly 3.4 rushers per team per year.
  • I found that the typical ratio was 3.8 pressures per sack, though this had a very high standard deviation (4.0), highlighting how much it varies from person to person.
  • When I looked only at 30+ pressures in a season (63 samples, so roughly 1 player per team per season), the average stayed virtually identical at 3.7 pressures per sack, but the standard deviation dropped to 1.2. This suggested to me that the typical number of around 3.8 pressures/sack is legitimate, and the high standard deviation with the 15 pressure cutoff was largely due to small sample sizes; you get lots of fluctuation in pressure/sack ratio when the pressure number is small.

Using that 3.8 pressures/sack as the norm, then, you can come up with how many expected sacks a player has for a season. If a player has 38 pressures, they are expected to have 10 sacks (38/3.8). You can then easily get a sack differential; a player with 10 expected sacks who actually posted 7 would have a differential of -3, indicating they were 3 sacks below what they should have normally had.


2019 Bears

I included all DL and OLB who registered pressures in 2019, as well as Robert Quinn and Barkevious Mingo. Players with a sack differential of +1 or better are highlighted in green, while those with a sack differential of -1 or worse are highlighted in red. I also included 2018 data to give you an idea of whether 2019 results were consistent with the year before.

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Four Bold Predictions for the 2018 Chicago Bears: Prediction Three

| September 1st, 2018

They can’t all be positive. Three of the four will be, but not this one.


Prediction Three

The Bears will have ten less sacks in 2018 than 2017.


Why?

  • The 2018 Chicago Bears roster has a glaring hole: edge rusher. The best player at the position is Leonard Floyd and he’s coming off a season where he played 10 games and registered only 4.5 sacks. Couple those stats with the fact that he’s already broken his hand this summer and it’s hard to imagine Floyd having enough impact/consistency to elevate this short-handed group.
  • Bears got 10 sacks last season from the combination of Willie Young, Pernell McPhee and Lamarr Houston. All three of those guys are on the flip sides of their careers but they are bonafide, professional pass rushers. They know how to get to the quarterback and finish. Where are they making up for those numbers? Aaron Lynch? Nope.
  • Bears were ranked T-7 in sacks in 2017. Sacking the QB ten fewer times will land them in the bottom third of the league. It just feels like that’s where this unit is heading.

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