Chicago’s defense has been awesome in the first month of the season. They’re among the best in the league in nearly every category that matters, and are ranked first overall in DVOA. Now I want to look a little more closely at how well they’re performing against both the run and pass in different areas of the field.

Defending The Run

Chicago’s run defense was solid in 2017, but it has been fantastic so far in 2018. They have shut opposing run games down, and they’ve done it pretty much across the board, as we can see below.

Here’s the data for Chicago’s rushing defense by zone, courtesy of the NFL Game Statistics and Information System. The line at the bottom is the line of scrimmage, runs are split into 7 zones, and attempts and yards per carry are listed for each zone, with ranks relative to the rest of the NFL in parentheses. The height of the bar is proportional to yards per carry, and bars are colored green for top 10, red for bottom 10, and yellow for middle 12. Note expected yards per carry varies by region, so the colors are relative to their peers in that region.

A few thoughts:

• That’s a whole lot of green. Awesome. Last year’s version featured a lot more yellow and red. This is a good time to remind you that Khalil Mack is an elite run defender in addition to being one of the best pass rushers in the league.
• Speaking of Khalil Mack, he and Akiem Hicks usually line up opposite the RG and RT. Notice where defenses are running towards? There are 38 runs to the left side – away from Mack and Hicks -compared to 21 towards them on the right.

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Now that we’ve seen Chicago’s new offense play four games, it’s time to examine what exactly it looks like. We’ve seen them run 271 plays, and while that’s still a fairly small sample size, it’s big enough that we can begin to pick up trends, search for predictable patterns that opposing defenses might begin to pick up on, and see if there are any situations their current approach could be improved.

Now we focus on the wide receivers and tight ends, examining how much they’re playing, how effective they’ve been, and how they’re being utilized.

Snap Counts and Predictabilities

First I want to look at how frequently each target is playing, and how their presence on the field impacts the offense’s performance. Data is from The Quant Edge.

A couple things to note about the table below:

• I’m using success rate here instead of yards per play. That is to account for down and distance context. A two-yard play on 1st and 10 is bad, while a two-yard play on 3rd and 1 is good. The general idea is that a successful play keeps you ahead of the chains, but an exact definition is available here if you’re curious.
• I didn’t include Allen Robinson, Taylor Gabriel, or Trey Burton here because they’re almost always on the field; they’re all playing least 83% of the offensive snaps so far. This is more to look at the players who are situational and how they’re impacting the offense.
• Anthony Miller’s data only includes the 3 games for which he was active.

A few thoughts:

• On the surface, it looks like Anthony Miller has hurt the offense. Maybe he has. But he basically only plays in 11 personnel groupings, where there are 1 RB, 1 TE, and 3 WRs on the field, and in general that grouping has been the least efficient passing formation in the NFL. In terms of the run game, I don’t actually know much about Miller as a blocker. It’s possible that he’s not blocking well and that’s hurting the run game, but it’s also possible something else is causing the difference.

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Now that we’ve seen Chicago’s new offense play four games, it’s time to examine what exactly it looks like. We’ve seen them run 271 plays, and while that’s still a fairly small sample size, it’s big enough that we can begin to pick up trends, search for predictable patterns that opposing defenses might begin to pick up on, and see if there are any situations their current approach could be improved.

Today we’re going to focus on running backs Jordan Howard and Tarik Cohen, examining how much they’re playing, how effective they’ve been, and how they’re being utilized.

Snap Counts and Efficiency

First I want to look at how frequently each running back is playing, and how their presence on the field impacts the offense’s performance. Data is from The Quant Edge.

(Note: I’m using success rate here instead of yards per play. That is to account for down and distance context. A two-yard play on 1st and 10 is bad, while a two-yard play on 3rd and 1 is good. The general idea is that a successful play keeps you ahead of the chains, but an exact definition is available here if you’re curious.)

A few thoughts:

• Howard is actually playing typical lead RB snaps for an Andy Reid offense. As I noted this offseason, Kareem Hunt played 65% of the snaps in Kansas City last year. This is in stark contrast to the Philadelphia Eagles style-rotation I thought would make more sense. It’s worth noting the 2 split snaps almost exactly 50/50 in the Tampa Bay game. I wonder if that’s more what we’ll see going forward.
• The run/pass splits for when both of these players are in vs. out of the game are too lopsided. A 30% swing when Howard exits the game and 20% swing when Cohen enters the game should not be the case. This is too predictable and makes it too easy on the defense.
• Some of these numbers are related, since Howard and Cohen basically swap being on the field. They’ve only shared the field on 23 snaps so far this year, so the run game being more effective with Howard off the field is the same as saying the run game gets more effective when Cohen is on the field. Again, I think this might have more to do with defenses gearing up to stop the run when Howard is in the game and not expecting it when Cohen is in.

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Now that we’ve seen Mitchell Trubisky play four games under Matt Nagy’s tutelage, it’s time to examine how he’s doing. We’ve seen him play 269 snaps and throw 130 passes, and while that’s still a fairly small sample size, it’s big enough that we can begin to analyze how he’s performing in a variety of situations.

Growth Through Each “Quarter”

Last offseason I looked at Trubisky’s performance in 4-game snapshots, borrowing the idea of breaking an NFL season down into quarters from Lovie Smith. There I found that Trubisky got progressively better in every “quarter.” Since Trubisky has played 4 games this year, he now has 16 in his career, giving him a full 4 “quarters” that we can track. Let’s take a look.

Well that looks pretty good. I said last offseason that, statistically speaking, Trubisky needed to throw more TDs while keeping everything else the same. Here we see that he has managed to throw more TDs, and everything else has stayed the same or improved. That’s good growth to see from a 2nd year QB.

Of course, four games is a small sample size, and this doesn’t look quite as rosy if we remove the Tampa game from the equation. Then his yards per attempt drops to 5.7, TD percentage to 1.9%, and his INT % (2.9%) and sack % (8.0%) both rise a bit higher than they were late in his rookie year.

Through three weeks, the stats suggested Trubisky was actually playing worse than late in his rookie year. That’s not entirely surprising given that learning a new offense often results in a step back at first.

Adding the TB game in there makes this look good, but now the question is whether the TB game was an aberration or a sign of things to come.

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Now that we’ve seen Chicago’s new offense play four games, it’s time to examine what exactly it looks like. We’ve seen them run 271 plays, and while that’s still a fairly small sample size, it’s big enough that we can begin to pick up trends, search for predictable patterns that opposing defenses might begin to pick up on, and see if there are any situations their current approach could be improved.

Down & Distance

Let’s start by looking at what they’re doing in different down and distance situations. All statistics come from the NFL Game Statistics and Information System unless otherwise noted.

First Down

The offense has been extremely balanced on 1st down so far, with exactly 58 runs and 58 passing plays (passes, sacks, or scrambles).

The passing game has thrived with an average of 7.8 yards per play. According to Pro Football Reference’s Game Play Finder, Mitchell Trubisky is completing 69% of his passes on 1st down, with 6 TD, 2 INT, and a 115.9 passer rating.

The running game, on the other hand, has been extremely ineffective, averaging only 3.0 yards per carry. Most of the running attempts (34) have come from Jordan Howard, who is averaging 3.2 yards per carry, but Tarik Cohen also has 17 carries at only 2.9 yards per clip. It would appear the Bears are either making it obvious when they’re going to run or defenses are worrying about stopping the run first to make Trubisky beat them.

Second Down

When it comes to 2nd down, context is needed. A 3 yard gain is great on 2nd and 2, pretty good on 2nd and 5, and awful on 2nd and 10. With that in mind, I split the data into 4 groups based on the distance required to get a 1st down. The table below shows the results.

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I’ve been writing a bunch of articles lately about how the Bears are expected to improve, so now I want to focus on what level they have to reach in order to make the playoffs.

As I’ve said before, there is some precedent to teams who have been as bad as the Bears over the last few years going straight to the playoffs in recent NFL history, but not many make that big of a jump. I still think it’s more likely that the Bears end up somewhere around average this year and are poised to make a playoff push in 2019.

But if they are to be one of the few that jump directly to the playoffs, what type of improvement will they have to show? In an effort to answer this question, I looked at the offensive and defensive rankings in terms of points per game for every team from 2008-17. I then looked at what those profiles looked like for playoff teams.

Crunching the Data

Unsurprisingly, teams that had better offenses and defenses made the playoffs more often. I generally split the rankings into quartiles (1-8, 9-16, 17-24, and 25-32) and grouped teams based on their combination of stronger and weaker unit. We’ll tentatively call 1-8 good, 9-16 above average, 17-24 below average, and 25-32 bad. The results can be seen in the table below, or full raw data can be viewed here.

So we basically have four different categories of teams that consistently make the playoffs.

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Now that Ryan Pace has been here for a while, we can start to look at his past drafts to see what lessons we can learn from his approach. This can help us cautiously look ahead to the 2018 draft to see what he might be thinking.

With that goal in mind, I’m going to spend the next three weeks looking at how Pace has approached the three days of the draft, and then applying that approach to 2018 to see what players are likely being considered for the Bears this year. We’re starting today at the top of the draft. Let’s look first at the history, and then we’ll examine lessons learned.

Draft History

2015: Kevin White, WR, 7th overall

2016: Leonard Floyd, OLB, 9th overall (trade up from 11)

2017: Mitchell Trubisky, QB, 2nd overall (trade up from 3)

Trend 1: Go get your guy

The first thing we should observe is that Ryan Pace is not shy about trading up in round 1 to get the player he has identified as his main target. So keep that in mind as we look at mock drafts with players who might be good fits for the Bears but are projected to go higher than #8.

It’s worth noting that these have all been relatively minor trades just moving up a few spots, which keeps the cost down. Despite reportedly exploring moving up to the top of the draft for Marcus Mariota in 2015, Pace has not been willing to give up multiple high picks in these moves.

Trading up becomes a bit more difficult this year because the Bears are already without a third round pick due to trading up for Trubisky last year, but they do have an extra fourth round pick they could use.

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The Bears have picks near the top of days one, two and three of the draft this year. (The picks themselves are in rounds one, two and four.) With several positions of need, the team needs to weigh the value of a position and the depth of players at that position on their board.

One must factor how many players typically get drafted at certain positions in certain parts of the draft. If they don’t draft, say, an edge rusher in round one, how many will likely be gone before they pick again in round two? And if they pass again in round two, how many will typically be gone by the time they’re up again at the top of round four?

With those questions in mind, I looked at the last ten drafts to see how many players were drafted at positions of interest in each round. I looked mainly at positions which are clear needs for the Bears this year, which in my book are edge rusher*, interior OL, cornerback, and offensive tackle. I also looked at wide receivers, tight ends and running backs, because I think the Bears might continue adding more weapons around Mitch Trubisky.

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I recently looked at Trubisky’s rookie performance in “quarters” – four-game sets – and found that he showed continual growth in both usage and efficiency (in all areas but throwing touchdowns) as the season progressed.

Now I want to look at how that growth compares to other recent quarterbacks in their rookie seasons. Do quarterbacks who are going to be good show more growth during their rookie season? Do those who stay the same, or get worse, tend to bust?

The Set-Up

I looked at all QBs drafted in the 1st round who played at least twelve games of their rookie season within the last 10 years and tracked their progress in four-game samples. All data was compiled using the Pro Football Reference game play finder. Allow me a brief explanation of my 3 limits:

• 1st Round Picks. I wanted players similar to Trubisky, who were drafted with the expectation of playing early. Later round picks often have to earn the job so I didn’t want to include them and skew the data.
• In the Last 10 years. The NFL passing game continues to evolve, as does the college passing game that prepares them for the NFL. Comparing rookie QBs now to rookie QBs from 20 years ago just isn’t reasonable. Heck, even comparing now to 10 years ago isn’t great, but cutting it much shorter than that really limits the sample size, which is already pretty small.
• Who Played Twelve Games as Rookies. I’m tracking growth in four-game samples, and two sets of data isn’t really enough, so twelve games gives some sort of growth trend through at least 3 sets.

These stipulations gave me a sample size of 16 quarterbacks: Matt Ryan, Joe Flacco, Mark Sanchez, Sam Bradford, Cam Newton, Blaine Gabbert, Robert Griffin III, Ryan Tannehill, Brandon Weeden, Andrew Luck, Teddy Bridgewater, Blake Bortles, Jameis Winston, Marcus Mariota, Carson Wentz, and Mitch Trubisky.

Before doing this study, it seemed fairly logical to me that most rookie QBs would naturally improve as the season wore on. After all, they’re brand new at this and facing a steep growth curve. And you usually get better at your job within the first few months, right?

Also, take into consideration that most of these quarterbacks were starters from day one of training camp, let alone the regular season. Trubisky faced the unique scenario of not seeing first-team reps until after the first quarter, as the Bears prepared to face what was then the league’s best defense.

Nevertheless, we look at the numbers.

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In his rookie season, Mitch Trubisky got to play 12 games and throw the ball 330 times. In those 330 attempts, he threw 7 interceptions, which is actually pretty good. That rate – an interception on 2.1% of his throws – was 12th best in the NFL among qualified passers, ahead of established veterans like Matt Ryan, Ben Roethlisberger, and Aaron Rodgers.

As that list above shows, there’s more to being a good quarterback than simply not throwing interceptions. But avoiding interceptions is an important part of a quarterback’s job; in no small part because they can be game-changing plays that make it a lot harder to win.

But not all interceptions are created equal. Sometimes it’s the quarterback’s fault, sometimes it’s on the wide receiver, and sometimes it’s hard to tell. In general, I think you can group them all into one of four categories:

1. Bad decision. These are throws that should never be made because the receiver isn’t open and a defender has a good chance at an interception. Bears fans have seen plenty of these in the last 8 years from balls being chucked up into double or triple coverage.
2. Bad throw. The target is open, but the pass is off target. The problem here comes not in the choice to throw but in the throw itself.
3. Miscommunication. The quarterback thinks the wide receiver is running one route, the wide receiver runs another route, and the defensive back is the beneficiary.
4. Receiver error. The receiver is open, the pass is good, but the ball bounces off of the target’s hands and gets intercepted.

The first two are both the fault of the quarterback, though in very different ways. The third one makes it pretty much impossible for us to assign fault. The last one is the fault of the target.

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