This is the final installment of a 3-part series looking at Chicago’s 2023 pass rush.

• In part one, we learned that the Bears had one of the worst pass rushes in the NFL, though it improved a bit after trading for Montez Sweat, especially when they were willing to blitz.
• In part two, we saw that Montez Sweat is a good but not great pass rusher, while all of the other defensive ends on the roster are bad at rushing the passer.

Today, we’re going to end the series by exploring Chicago’s defensive tackles.

Overall Efficiency

We’ll start with a season-long look at how Chicago’s main defensive tackles performed when rushing the passer. The table below shows a variety of per-snap metrics, including how they ranked compared to the 98 DTs league-wide who had at least 200 pass rush snaps. A few quick notes:

• All data comes from Pro Football Focus (PFF).
• Win rate is the percentage of snaps where PFF determines that the rusher has beaten the blocker at any point in the snap. This is admittedly subjective, and thus should not be used on its own, but can be a helpful part of a larger picture.
• Pass Rush Productivity is a unique PFF stat that accounts for all sacks, QB hits, and pressures on a per-snap basis, with an added weight given to sacks; a higher value is better.
• True pass sets look only at plays that do not give offensive linemen a built in advantage: no play action, no screens, and the throw time has to be at least 2 seconds. This lets us see how effectively a player rushes the passer when they most likely know they are getting after the QB, and the offense knows they have to block for a while.
• Values in the top 25% are highlighted in green, while those in the bottom 25% are highlighted in red.

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This is the 2nd installment of a 3-part series looking at Chicago’s pass rush from 2023. In part one, we learned that the overall team pass rush was among the worst in the NFL.

Today, we’ll be examining how effectively Chicago’s defensive ends rushed the passer last year.

Overall Efficiency

We’ll start with a season-long look at how Chicago’s main defensive ends performed when rushing the passer. The table below shows a variety of per-snap metrics, including how they ranked compared to the 95 edge rushers league-wide who had at least 200 pass rush snaps. A few quick notes:

• All data comes from Pro Football Focus (PFF).
• Data for Montez Sweat is only for the 9 games he played in Chicago.
• Win rate is the percentage of snaps where PFF determines that the rusher has beaten the blocker at any point in the snap. This is admittedly subjective, and thus should not be used on its own, but can be a helpful part of a larger picture.
• Pass Rush Productivity is a unique PFF stat that accounts for all sacks, QB hits, and pressures on a per-snap basis, with an added weight given to sacks; a higher value is better.
• True pass sets look only at plays that do not give offensive linemen a built in advantage: no play action, no screens, and the throw time has to be at least 2 seconds. This lets us see how effectively a player rushes the passer when they most likely know they are getting after the QB, and the offense knows they have to block for a while.
• Values in the top 25% are highlighted in green, while those in the bottom 25% are highlighted in red.

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This is the start of a 3-part series examining Chicago’s pass rush in 2023 and what expectations should be for 2024. The content covered in each part roughly breaks down as follows:

Part 1: Overall team pass rush, and the impact of trading for Montez Sweat.
Part 2: Defensive end individual pass rushing efficiency.
Part 3: Defensive tackle individual pass rushing efficiency, including rookie progression for Gervon Dexter Sr. and Zacch Pickens.

Let’s dive right in!

Overall results

We’ll start by examining Chicago’s overall team performance rushing the passer last year. The table below shows how the Bears ranked out of 32 NFL teams in generating sacks and pressures, as well as how often they blitzed. All values in the top 25% are highlighted in green, while those in the bottom 25% are in red. All data for this article, unless otherwise noted, is from Pro Football Reference.

Side note: sorry if the tables don’t show up well in the article. You can click on them to view in full on a separate page. 

A few thoughts:

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This is the final installment of a 4-part series looking at Chicago TEs Cole Kmet and Gerald Everett.

• In part one, we explored how each player has been used in the past, and how this might match up with how offensive coordinator Shane Waldron has deployed his tight ends.
• In part two, we examined how frequently and effectively Kmet and Everett were asked to block in both the run and pass games.
• In part three, we saw how they fared as pass catchers in terms of overall efficiency, against man and zone coverage, and in different depths of the field.

Today we’ll wrap up the series by continuing to focus on their impact catching the football, especially on 3rd/4th down, in the red zone, and out of the slot.

3rd + 4th Down

Let’s start by looking at 3rd and 4th down, when stakes are high and players need to produce a first down to move the chains and avoid a punt. The table below shows how frequently and effectively Kmet and Everett were targeted in these high-leverage situations in 2023. Data is from Pro Football Reference’s Game Play Finder, ranks in parentheses are compared to the 26 NFL TEs with 50 or more targets, and ranks in the top 25% are highlighted in green, while those in the bottom 25% are highlighted in red.

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This is part 3 of a 4-part series looking at Chicago TEs Cole Kmet and Gerald Everett.

• In part one, we explored how each player has been used in the past, and how this might match up with how offensive coordinator Shane Waldron has deployed his tight ends.
• In part two, we examined how frequently and effectively Kmet and Everett were asked to block in both the run and pass games.

Today, we’re going to switch gears to focus on the tight ends as pass catchers. We’ll look at overall efficiency, how they performed against zone and man coverage, and how frequently and effectively they were targeted at different depths of the field.

Basic Efficiency Stats

We saw in part 1 that Kmet and Everett both have starting TE volume in the passing game, but volume stats don’t tell you the whole story; we also need to look at how efficient players are with their targets. The table below shows that data for Chicago’s TEs, as well as their ranks compared to 26 TEs with at least 50 targets. Values in the top 25% are highlighted in green, while those in the bottom 25% are in red. NFL best, average, and worst values among those 26 players are also included to help contextualize the data. All data is pulled from Pro Football Reference’s Game Play Finder.

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This is the 2nd installment of a 4-part series looking at Chicago TEs Cole Kmet and Gerald Everett. In part one, we explored how each player has been used in the past, and how this might match up with the way offensive coordinator Shane Waldron has deployed his tight ends. Today, we’re going to focus on blocking, which is an often overlooked part of a tight ends’ role.

Pass Blocking

Let’s start by looking at how frequently and effectively Chicago’s TEs pass blocked. The table below shows some basic pass blocking stats from Pro Football Focus (PFF) for Kmet and Everett in 2023, and their rank compared to 45 NFL TEs with at least 25 pass blocking snaps. Ranks in the top 25% are highlighted in green, while those in the bottom 25% are highlighted in red.

A brief explanation of some of the stats:

• Pass Block % is the % of pass plays where a player is on the field and is asked to block instead of running a route.
• Pass Block Efficiency is a PFF metric that “measures pressure allowed on a per snap basis with a weighting towards sacks.” A higher number is better.

Side note: sorry if there are formatting issues for the tables. You can view them in full by clicking on them. 

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After handing Cole Kmet a big extension last offseason and signing Gerald Everett to a solid contract in free agency this year, the Bears have two starting-caliber tight ends on the roster. Both players were heavily utilized in the passing game in 2023, which can be seen in the table below showing their basic receiving production, with ranks compared to other NFL TEs in parentheses.

Kmet was among the top 10 TEs in every stat, while Everett generally ranked in the 15-25 range, which would put him as roughly an average to below average starter. Their pay checks also reflect the expectation that both players are expected to play starting-type roles, as they currently rank 9th (Kmet) and 21st (Everett) among TEs in average yearly salary. Since both players will be playing important roles in Chicago’s offense in 2024, this week’s series is going to take a detailed look at how each of them could be useful. We’ll split this into four parts:

• Part 1:
  • How new OC Shane Waldron has utilized his TE in the past
  • How this compares to Kmet and Everett’s usage
• Part 2:
  • How frequently and effectively they blocked
• Part 3:
  • How efficient they were overall as pass catchers
  • How they performed against man and zone coverage
  • How frequently and efficiently they were targeted at different depths of the field
• Part 4:
  • 3rd and 4th down production
  • Red zone usage
  • How frequently and efficiently they produced in the slot

Waldron TE Usage

Let’s start with a look at how new offensive coordinator Shane Waldron used his tight ends during his 3 seasons in Seattle. The table below shows information about how much his tight ends played, how frequently they were targeted in the passing game, and where they lined up. TE1-TE3 status for each season is based on total snap counts, and alignment information is pulled from Pro Football Focus (PFF).

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This is the 2nd part of a 2-part series exploring Chicago’s top trio of WRs, which includes accomplished NFL veterans DJ Moore and Keenan Allen to go with top 10 pick Rome Odunze.

In part one, we examined overall efficiency, production from the slot, and impact against man and zone coverage. Today, we will explore target depth, 3rd/4th down production, and usage in the red zone. Like in part one, data presented is for the NFL only, so Odunze will not be in tables, but I will try to provide context for his performance in these areas when possible.

Targets by Depth

Let’s start by examining how frequently and effectively Moore and Allen were targeted at different depths of the field. The table below shows this data split into four depths: behind the line of scrimmage, 0-9 yards downfield, 10-19 yards downfield, and 20+ yards downfield. A variety of production metrics are given in each depth, along with Moore and Allen’s ranks compared to the 54 WRs with 75+ total targets in 2023. Ranks in the top 25% are highlighted in green, while those in the bottom 25% are highlighted in red, and the high, average, and low values of the 54-player sample are shown for context. All data is from Pro Football Focus (PFF).

(Side note: sorry if the formatting is poor for the graph. You can click on it to see it in a new window in full if it’s not showing up right for you.)

A few thoughts:

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After lacking talent at the wide receiver position for the better part of the last decade, the Bears have completely revamped the room in the last two offseasons with the additions of DJ Moore, Keenan Allen, and Rome Odunze, and they now boast what might be the best WR trio in the NFL.

This week I want to dive into the WRs, with an in-depth look at:

• How efficient they were
• How frequently and efficiently they played in the slot
• How they performed against man and zone coverage
• How frequently and efficiently they were targeted at different depths of the field
• 3rd and 4th down production
• Red zone usage

We’ll examine the first three areas today, with a follow-up piece tomorrow looking at the latter half of the list.

I want to note that the analysis will mostly focus on Moore and Allen, since they have NFL production that is easier to analyze and contextualize. I’ll provide some Odunze stats when relevant, but it’s hard to say for sure how college production and/or usage will translate to the NFL.

Overall Stats

Let’s start with a basic look at overall production in 2023. The table below shows how Moore and Allen ranked compared to all NFL wide receivers in the basic receiving stats.

At first glance, it is easy to see that both players were among the most productive in the NFL in 2023, and that wasn’t a one-year fluke either. Moore is currently averaging over 1000 yards per season in his career, and Allen is as well if you don’t count the season when he only played one game.

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In addition to adding 5 new starters on offense this offseason, the Bears fired offensive coordinator Luke Getsy and replaced him with Shane Waldron, who spent the previous 3 years holding the same position in Seattle.

In order to better understand what Chicago’s offense might look like in 2024, I’ve been digging into data about Waldron’s offenses at his last stop. I looked at down and distance play calling tendencies yesterday, and today want to explore personnel and formation trends.

Today’s data comes from Sumer Sports, which only has information for 2022 and 2023, so nothing from Waldron’s 1st season in Seattle will be included.

Personnel Groupings

Let’s start by looking at common personnel groupings, which looks solely at the listed position of players on the field and not where they are lined up. These groupings are commonly listed by 2 numbers, where the 1st is the number of running backs and the 2nd is the number of tight ends. Since teams play 5 skill position players at a time, the number of wide receivers is then implied. The 2 most common groupings are 11 (1 RB, 1 TE, 3 WR) and 12 (1 RB, 2 TE, 2 WR).

The table below shows how frequently the Seahawks and Bears used and passed out of each grouping on 1st-2nd down in 2023, along with their ranks compared to the rest of the NFL. Values in the top 25% are highlighted in green, while those in the bottom 25% are red. Seattle’s data from 2022 is included as well for comparison.

(side note: if the table gets cut off, click on it to view the full table in a new screen)

A few thoughts:

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