Wrapping up our look at returning players and new veterans on defense, today we’re going to explore stopping the run.

This can be difficult to quantify, because much of what goes into run stopping doesn’t get measured. When Eddie Goldman holds his own against two blockers, he frees up a linebacker to make the tackle, but nothing Goldman did there shows up on a stat sheet. So I want to be clear from the start that this is not going to be a perfect science, and I make no claims that it is.

However, Pro Football Focus (PFF) does track some data that can give us an idea of how often a defender is directly involved in stopping a run play. We’ll look at basic metrics that are fairly self-explanatory, like how often a player makes a run tackle or misses a tackle, but also some more advanced data including how far downfield the average run tackle they make is.

One unconventional stat PFF uses that I want to briefly discuss is a “run stop.” PFF defines this as a solo tackle that counts as a “win” for the defense. I can’t find anything definitively saying what makes a play a “win,” but you can imagine this is probably similar to success rate, where it keeps the offense from picking up a certain % of the yards needed for a 1st down. In other words: a defender made a tackle to keep the run short and force the offense behind the chains.

I will examine every Bears defender who had at least 200 run defense snaps last year, whether in Chicago or somewhere else. This allows for a large enough individual sample size that the values have some meaning, but also a large enough sample size for comparing players from a position to their peers. The 200 snap threshold gave a sample of 74 interior defensive linemen (2.3/team), 52 edge defenders (1.6/team), 66 linebackers (2.1/team), 75 cornerbacks (2.3/team), and 70 safeties (2.2/team). That adds up to 10.5 defenders/team, or roughly those who played starter-level snaps.

Interior DL

Let’s start with a look at the defensive line, where the Bears return Angelo Blackson and added Justin Jones in free agency. The table below shows how they both fared in a variety of run-stopping metrics last year, as well as their rank compared to 74 interior defensive linemen who played at least 200 run snaps. To give a broader frame of reference, the best, average, median, and worst values among that 74-player sample are also provided for each statistics. Categories highlighted in green indicated the player was in the top 25% relative to their peers, while red indicates the player was in the bottom 25%.

A few thoughts:

• Angelo Blackson seems like a decent enough, if not great, run defender. He’s not overly good or bad in any of the areas. His missed tackle rate is a little higher than you would like to see, so hopefully that can improve a bit going forward.
• Justin Jones is very active in run defense, as evidenced by his high amount of run-defending tackles. However, he struggles with missed tackles, and very few of his tackles count as “wins” for the defense, which means they’re happening farther down the field than you would like.

Edge Rushers

Let’s switch gears and examine the edge rushers now, where the Bears have three notable players: returnees Robert Quinn and Trevis Gipson and newly signed Al-Quadin Muhammad. The table below shows their performance against the run in a variety of metrics, including their rank compared to 52 positional peers.

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Today we’ll switch to look at how linebackers and safeties have fared in coverage.

Like I did with cornerbacks, I’m using data from Pro Football Focus (PFF) that looks at how frequently and effectively individual players are targeted in coverage. I chose to set a threshold of 250 coverage snaps because it both gives a decent enough sample size to judge an individual player and gives a big enough grouping of players at each position to evaluate how somebody performed relative to their peers. This threshold gave a sample size of 68 linebackers (2.1/team) and 82 safeties (2.6/team).

Linebackers

Let’s start with a look at linebackers, where the Bears return Roquan Smith and bring in Nicholas Morrow. The table below shows how they fared in a variety of coverage metrics last year, as well as their rank compared to 68 linebackers who had at least 250 coverage snaps. To give a broader frame of reference, the best, average, median, and worst values among that 68-player sample are also provided for each statistic. Categories highlighted in green indicated the player was in the top 25% relative to their peers, while red indicates the player was in the bottom 25%.

Note: Since Morrow missed the 2021 season with an injury, his data is from 2020, but he is still ranked against his peers in 2021. I know this is not perfect, but these values shouldn’t change that much league-wide year over year, and it saved me a ton of work.

A few thoughts:

• Overall, both Roquan and Morrow appear to be very good in coverage. This should be a real strength of Chicago’s defense.
• The two main stats I would use to evaluate effectiveness are yards/target and yards/coverage snap. These encapsulate a bunch of the other metrics to show how many yards the defender gave up overall.
  • In those areas, Roquan is solidly above average, but not great, which honestly surprised me.
  • Morrow, on the other hand, ranks near the top in both. The Bears haven’t had a good coverage linebacker to put next to Roquan since he was a rookie in 2018, so the thought of pairing him with somebody who excels in coverage is enticing.
• Some of the other stats can give us a glimpse into playing style. For instance, Roquan gives up plenty of catches (high catch %), but they are mostly very short (low target depth and air yards/catch). This is a common trade off in coverage, since shorter passes are easier to complete. Unfortunately, Roquan struggles a bit with giving up yards after the catch – though it’s not due to missed tackles – which is what brings him down overall. In general, Roquan is good at limiting the yards/catch allowed, but the high catch rate brings his yards/target and yards/snap ranks down a bit.
  • Morrow, on the other hand, keeps the catch rate low despite giving up short passes, which gives him stellar coverage marks pretty much across the board.

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Today we’re going to shift from examining players who rush the passer to those who defend passes that are thrown. We’ll start by looking at the CBs, with an upcoming article to look at linebackers and safeties.

In order to do this, I’m using data from Pro Football Focus (PFF) that looks at how frequently and effectively individual players are targeted in coverage. I chose to set a threshold of 250 coverage snaps because it both gives a decent enough sample size to judge an individual player and gives a big enough grouping of players at each position to evaluate how somebody performed relative to their peers. This threshold gave a sample size of 106 cornerbacks, or 3.3 per NFL team.

First Look

The Bears have four notable veteran cornerbacks: returners Jaylon Johnson, Kindle Vildor, Duke Shelley, and newcomer Tavon Young. The table below shows how they fared in a variety of coverage metrics last year, as well as their rank compared to 106 cornerbacks who had at least 250 coverage snaps. To give a broader frame of reference, the best, average, median, and worst values among that 106-player sample are also provided for each statistic. Categories highlighted in green indicated the player was in the top 25% relative to their peers, while red indicates the player was in the bottom 25%.

A few thoughts:

• Let’s start with Jaylon Johnson, who is probably not as good as many Bears fans have made him out to be. To be fair to Johnson, he often shadowed the other team’s best WR in 2021, so quite a bit was asked of him, but his overall profile here shows a CB who is more average starter than great. Still, he is at least an average starter, and that’s something.
  • You can also see Johnson’s stylistic approach to CB show up through a few of the stats. Passes thrown at him are generally pretty deep because he plays tight man coverage and doesn’t give up easy stuff underneath. That leads to a low catch percentage, but also a high yards/catch value.
  • Overall, Johnson ends up around average in both yards/target and yards/coverage snap, which are probably the best 2 overall metrics to go to when evaluating CB play.
• It’s a very different story for Kindle Vildor, who was the worst CB in the NFL in yards/target. Like Johnson, he likes to play tight coverage, which gives him a high average target and catch depth. Unlike Johnson, Vildor gave up a really high catch percentage, which is really bad when passes are deep. One good thing is that teams didn’t throw at him very often, but they were hugely successful when they did.
• Finally, let’s take a look at Duke Shelley and Tavon Young, who have similar profiles because they both primarily play nickel. That means they see more short passes (low target depth and air yards/catch) but give up more catches (high catch %). Young was appreciably better at limiting yards after the catch, which meant his overall metrics (yards/target and yards/coverage snap) were around average, while Shelley’s were terrible.
  • It seems weird that Shelley was the worst CB in the NFL giving up yards after the catch despite being very good at avoiding missed tackles. That must mean many players who caught the ball had so much space between them and Shelley that they could keep moving without him having an attempted tackle to miss.

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Almost everything I’ve looked at so far this offseason has been about the offense, so now I want to shift gears and give some attention to returning players and new veterans on defense. That starts today with a closer examination of the pass rush.

In order to do this, I’m using data from Pro Football Focus (PFF) that examine pressures, wins, sacks, and pass rush productivity. Here’s a quick explainer of what PFF means by some of those that are less obvious:

• Pressure: This is a measure of how often a player bothers the QB – makes him move off his spot, hits him, or sacks him.  It will be defined through the % of pass-rushing snaps that count as a pressure, QB hit, or sack.
• Win: this is a measure of how often a player beats their block to impact a play within 2.5 seconds. It will be defined through the % of pass-rushing snaps that count as a win.
• Pass Rush Productivity: this accounts for all sacks, pressures, and QB hits on a per-snap basis, with an added weight given to sacks. PFF doesn’t give an exact formula for how much extra sacks are weighted, but generally a higher number is better.

I’ll examine both all pass rushing snaps and only what PFF defines as true pass sets. These are basically set up to only look at 4-man rushes on standard passing plays, so all screens, play action, designed rollouts, blitzes, 3-man rushes, and exceptionally fast (ball thrown in <2 seconds) or slow (ball thrown in >4 seconds) plays are removed. PFF says that these values tend to be more stable year-to-year, since they are more indicative of actual pass rushing ability.

Edge Rushers

Let’s start by examining edge rushers, where the Bears have three notable NFL veterans: returners Robert Quinn and Trevis Gipson and newly signed Al-Quadin Muhammad.

The table below shows how all three fared in a variety of pass rushing stats in 2021, as well as their rank compared to 93 NFL edge rushers with at least 200 pass rush opportunities. To give a broader frame of reference, the best, average, median, and worst values among that 93-player sample are also provided for each statistic.

Categories highlighted in green indicated the player was in the top 25% of edge rushers (top 23), while red indicates the player was in the bottom 25% (bottom 23).

A few thoughts:

• If you ignore sacks and look more at the pressure and win rates – which are more stable season to season – Quinn was more good than great as a pass rusher in 2021. That feels weird to say for somebody who finished 2nd in the NFL in sacks, but the extremely low pressure/sack ratio tells us that he produced more sacks than expected based on the pressure he generated, and pressures are generally more consistent than sacks.
  • This tracks with other data showing that Quinn generally took longer to get to the QB than the NFL’s elite pass rushers.
  • Quinn also has a fairly established track record of season-to-season inconsistency. He’s never produced an above-average pass rush productivity ranking in two consecutive years during his career, and he hasn’t had back-to-back seasons with 8+ sacks since 2014.
  • Add it all up, and I think a regression from Quinn is highly likely in 2022. The Bears would be wise to sell high on him now rather than waiting for the trade deadline if they are hoping to get value in return.
• Trevis Gipson honestly was fairly comparable to Robert Quinn in most of these statistics, which is pretty impressive. He had a very solid year in 2021. His sample size was much smaller (229 pass rush snaps vs. 402 for Quinn), so I’m eager to see if he can repeat that performance. It’s worth noting, however, that his pressure/sack ratio was about as low as Quinn’s, so he could play better this year and still see a dip in sacks.
• Al-Quadin Muhammad is a bad pass rusher. I really hope the Bears aren’t planning on him doing much to bother the QB, because 2021 was actually the best season rushing the passer of his career, and it was still bad.

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Despite only starting 10 of 17 games last year, Justin Fields fumbled the ball 12 times, which was the 4th highest mark in the NFL. That’s a real problem. Since fumble recovery is random, meaning you will lose roughly half of your fumbles, that’s an additional turnover around once every two games. Given the strong relationship between turnovers and game outcome, this is a recipe for losing a whole lot of games.

But is this a problem that is likely to continue for Fields? Let’s see what history might be able to tell us.

Fumbling Rookies.

It is surprisingly common for rookie QBs to fumble the ball. A lot. Since 2001, there have been 24 instances of a rookie QB fumbling the ball ten or more times. Looking at the rookies who have played the most, there are 61 rookie QBs in that time span with at least 250 pass attempts, and 22 of them (more than 1/3) had at least ten fumbles.

So, in that regard, Fields is in good company. While many of the QBs on that list went on to bust status, there were plenty of successful QBs as well, including Lamar Jackson, Andrew Luck, Derek Carr, Alex Smith, and Carson Wentz as long-time starters.

This led to a logical follow-up question: do QBs who fumble a bunch as rookies improve after that? In order to explore this, I tracked fumble rate through two methods:

• Plays per fumble, which includes all pass attempts, sacks, and rushes. This is a measure of how often a QB fumbles compared to how often the ball is in his hands.
• Hits per fumble, which includes all sacks and rushes as plays in which the QB got hit. This is a measure of how often a QB fumbles when exposed to contact with the ball in his hands.

I should note that this list only includes QBs who had 1000+ career pass attempts total, such that there was a large enough post-rookie sample size to gather meaningful data. This gave a sample size of 17, which includes over 8,000 rookie plays and 40,000 non-rookie plays.

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In his opening press conference as the general manager of the Chicago Bears, Ryan Poles boldly proclaimed his goal to “sustain success over a long period of time.” This is a fairly standard thing to say for a new general manager, because it’s what everybody in the NFL is trying to accomplish. But today I want to evaluate Poles’ approach to his first offseason in charge of a team with that goal in mind.

How to Achieve Sustained Success

Fact 1: Offense is far more stable than defense year over year. To put it another way, defensive success is not sustainable – a fact Bears fans should be intimately familiar with after the last five years. Thus, the main factor to drive sustained team success is going to be sustained offensive success.

Fact 2: Good offensive play is driven by good QB play. This makes perfect sense, and I think we all knew it, but it’s good to have proof to back it up.

Conclusion: The best path to sustained success is a good QB. A brief look at recent NFL history supports that notion:

If you consider making the playoffs to mean success, there have been 18 instances in the last ten years where teams made the playoffs at least three times in a four-year span. Ten of those involved a solid or better QB on a rookie deal as the primary starter, while six more featured future HOF QBs on veteran contracts.

Only two of 18, then, involved solid-but-unspectacular QBs who weren’t on rookie deals. Those were Tennessee with Ryan Tannehill and Kansas City with Alex Smith. So, it is possible to sustain success without a really good QB or cheap solid QB, but it’s a much less likely path.

It’s also worth noting that both of those two found very little success in the playoffs. Only three of nine playoff seasons featured a playoff win, and only one reached a conference championship game. So, if your definition of sustained success involves more than bouncing out of the playoffs early on, those don’t really meet it.

If you want to get more selective and look at playoff success as an indicator of success, this list gets even more QB-dependent.

• 28 of 40 teams in the conference championship game featured a starting QB with at least one All Pro or MVP in their career, and that doesn’t include Andrew Luck (retired early before achieving either of those) or Joe Burrow (only two NFL seasons so far, seems headed in that direction).
• Only eight NFL QBs have started at least two conference championship games in the last decade, and six of them have made an All Pro or won MVP.

Again, this doesn’t mean getting a really good QB is the only path to sustained success (see SF with Alex Smith/Colin Kaepernick about a decade ago, or SF with Jimmy Garoppolo the last several years). It’s just the most likely path to sustained success.

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Let’s look at historical trends to see where the Bears can expect to find positional value at various points in the draft. This builds very closely off work I’ve done each of the last two years, and here’s a quick recap of the approach:

• I looked at the last 15 drafts (2007-21) to see how many players at each position were drafted in the top 50 (their 2nd round picks are #39 and 48), top 70 (their 3rd round pick is #71), and top 150 (their next picks are #148 and #150). I didn’t look at the 1st round because the Bears don’t have a 1st round pick this year.
  • My source for this data did not differentiate between CB and S, so I combined those into DB.
  • They did differentiate between interior offensive line and offensive tackle, so I kept those separate.
• I then used The Athletic’s composite big board, which averages rankings from a number of different draft sources, to compare to historical trends. I focused especially on positions which I believe are the primary needs for the Bears. The idea here is that positions with more players than usual ranked in a given range are more likely to have somebody highly rated slip through the cracks, while positions with fewer players than usual ranked in a given range are more likely to have somebody reach for them to fill a need.

This is my third year applying this approach to the draft, and I was a bit hesitant about it at first, because it seems risky to rely on draft rankings from people who don’t work in the NFL. It’s quite possible that people in the NFL view these players entirely differently. However, I think the track record has been pretty solid over the last two years. For instance:

• In 2020, I found the Bears should look to grab a defensive back early, because the depth on day three was not very good, and they landed Jaylon Johnson in round two. I also found the value at WR should be good throughout the draft, so the Bears could add there at any point, and they found Darnell Mooney in round five.
• In 2021, I found the QB class was loaded at the top but not deep, so the Bears should look to take a QB early. At the same time, I found the OT class was historically deep, so they should look to draft one early and another late. They ended up with Justin Fields, Teven Jenkins, and Larry Borom all contributing as rookies.
• Of course, it hasn’t all been great. In 2020 I said the Bears would not find value at TE in round 2, and they landed Cole Kmet, who has at least been a capable player (even if I don’t think he’s particularly great).

This is definitely an inexact science, and we don’t want to put too much stock in it, but I think it’s a useful exercise to see what positions might have more good players than usual, and thus possibly value for the Bears.

Round 2 (Top 50)

Here is the data for players drafted in the top 50.

• Because every draft is different, I provided a range from the least to most players at that position drafted in the top 50 picks since 2007, as well as an average.
• The last column shows how many players from that position are ranked in the top 50 right now according to the composite big board linked above.
• Positions that are particularly good or bad are highlighted in colors (red for historically low, orange for near the low end of the range, light green for near the top end of the range, and green for historically good).

A few thoughts:

• It’s a good year for the Bears to need a WR, especially at the top of their draft. There are nine WRs ranked in the top 50 on the composite big board, there have been eight or fewer WRs taken in the top 50 13 times in the last 15 drafts. If history holds here, the Bears should have some solid value options at WR with either of their second round picks.
• There also seems to be pretty solid value at defensive back, where 12 players are ranked in the top 50 and 13 of the last 15 drafts have seen 11 or fewer DBs selected in that range. The Bears could use starters at outside CB, nickel CB, and safety, so they may look to fill one of those spots in the second round.
• The rest of the Bears’ biggest need positions are right around their historical averages, meaning there may or may not be value present for the Bears, depending on how the draft falls.

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It’s no secret that the Bears need a WR, but I would take it even further; they should enter the weekend with the goal of drafting two wideouts they think can contribute right away.

One of those has to be a bigger-bodied WR, which they are sorely missing right now, but my draft crush does not fit that bill.

In fact, Memphis WR Calvin Austin III comes in at the other end of the spectrum for WRs. He stands only 5’7″ and weighed in at the Combine at only 170 pounds. If you’re going to be that small, you need to be an athletic freak to make it at the NFL level, and Austin certainly fits the bill.

This is Austin’s Relative Athletic Score, or RAS, based on his Combine performance. RAS scales everything against historical players at your position from 0 (worst) to 10 (best). As I’ve already said, Austin is tiny, but he scores in the top 8% amongst WRs in literally every athletic testing metric (credit to Kent Lee Platte for RAS data), placing him in the top 6% overall in total athletic ability.

That athleticism certainly shows up when you watch Austin play. He’s both fast and quick, and his change of direction abilities are noticeable in tight spaces. This speed and acceleration lets Austin excel after the catch, as he had the 5th highest yards after the catch/catch mark of all WRs in the 2022 draft.

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Chicago Bears TE Cole Kmet saw his production jump across the board in his 2021 sophomore campaign, as his targets, receptions, and receiving yards all more than doubled from his rookie year. This left him ranking among the top 20 NFL TEs in the main three receiving categories, as you can see in the table below.

Of course, those are all volume stats, and high volume does not necessarily mean that you are a top player. Chicago’s receiving options were extremely limited in 2021, and the former coaching staff had a vested interest in getting Kmet the ball to justify their second-round investment in him, so of course he saw a lot of balls thrown his way. But how effective was he with those targets?

In order to dig into that question, I’m going to take a closer look at Kmet’s underlying metrics to see how well he performed. This will be very similar to what I recently did with Darnell Mooney, the only other returning pass catcher on the Bears.

Man vs. Zone

Let’s start by looking at how Kmet did against man and zone coverages compared to his peers. I split the overall TE group based on how many targets players earned, and the sample broke down like this:

• 50+ targets: 25 TEs fell in this group. With 32 NFL teams, this is more or less the starting TEs.
• 20-49 targets: 33 TEs fell in this range, meaning these are generally the second TEs on a team.
• Less than 20 targets: 64 players fit in here, so these are the depth TE on a team.

The table below shows how TEs in those groupings performed in a variety of metrics against both man (orange) and zone (blue) coverage. All stats are from Pro Football Focus (PFF).

A few thoughts:

• Like we did with Darnell Mooney, it’s important to take the offense into consideration when evaluating Kmet’s stats against his peers. The Bears as a team ranked in the bottom five in the majority of passing categories, so it’s not really a surprise to see some of his efficiency stats looking low. For example, the Bears were about 4% lower than the NFL average in completion % (catch % here) and 0.4 yards below the NFL average in yards/attempt (yards/target here).
• Given that context, Kmet served as a capable weapon against zone coverage. His catch percentage and yards/target mark are fairly solid, if unspectacular, though it’s worth noting his poor YAC (yards after catch) performance. Time will tell if that’s a scheme issue from last year (Andy Dalton and Justin Fields ranked 21st and 31st, respectively, in YAC/completion of the 33 QBs with 200+ passing attempts in 2021) or a Kmet issue, but it’s worth noting Mooney did not have the same YAC issues. Kmet’s average catch against zone is also a bit shorter down the field than most starting TEs, which is notable considering how Justin Fields had one of the deepest average passes in the NFL last year.
• Kmet’s man metrics, on the other hand, are unquestionably poor. His catch rate was just fine, but his average catch against man was very short, indicating he was only able to produce against man coverage on dump-offs underneath. This is in line with the TE2 and depth TE group, not the starters. Kmet’s YAC here was also laughably bad, indicating he was unable to consistently break tackles and turn those dump-offs into more meaningful gains.

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After a promising rookie campaign, Chicago Bears WR Darnell Mooney had a breakthrough sophomore season in 2021. He posted the first 1000-yard season of his career and, as you can see in the table below, was among the top 20 WRs in the NFL in the three main receiving categories.

Of course, these are all volume stats, and high volume does not necessarily mean you are a top player. Mooney was the only not-terrible WR in Chicago last year, so he naturally saw a lot of balls thrown his way. As the only returning WR in 2022, I think it’s worth digging a bit into the advanced statistics to see how well Mooney did with those passes.

Man vs. Zone

Let’s start by looking at how Mooney did against man and zone coverages compared to his peers. I split the overall WR group based on how many targets players earned, and the samples broke down like this:

• 100+ targets: 33 WRs fell in this group, and with 32 NFL teams, this was basically the WR1s.
• 50-99 targets: 56 WRs are in this group, making it the WR 2 + 3 for each team. These are generally starters, but not the top targets.
• 30-49 targets: 28 WRs are in this group, making it roughly a teams’ WR4. These are the top backups.
• Less than 30 targets: 117 WRs (about 3.6/team) fell in this group, and these can be viewed as depth pieces.

The table below shows how WRs in those groupings performed in a variety of metrics against both man (orange) and zone (blue) coverage. All stats are from Pro Football Focus (PFF).

A few thoughts:

• It’s important to take the offense into consideration when evaluating Mooney’s stats against his peers. The Bears as a team ranked in the bottom 5 in the majority of passing categories, so it’s not really a surprise to see some of his efficiency stats looking low. For example, the Bears were about 4% lower than the NFL average in completion % (catch % here) and 0.4 yards below the NFL average in yards/attempt (yards/target here).
• Even given that context, Mooney’s catch percentage is still quite low against both man and zone coverage. In man, this can be explained by his deeper targets (higher air yards/target), but that’s not true in zone. Mooney’s drop rate was not an issue (4.7%, 12th best of 33 WRs with 100+ targets), so I’m inclined to chalk this up to a high rate of uncatchable passes (Justin Fields was one of the least accurate passers in the NFL last year).

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