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Which Wide Receivers in the 2019 Draft Fit the Testing Profile for Matt Nagy’s Offense?

| March 25th, 2019

Last year, Data Entry looked at wide receivers who found success in coach Matt Nagy’s offense in Kansas City and identified physical traits they all shared. When examining their Combine performance, all typically excelled at three drills:

  • 40 yard dash: 4.51 seconds or better
  • Vertical jump: 35.5 inches or higher
  • Broad jump: 10 feet or longer

Receivers who were targeted for that offense usually hit at least 2 of those 3 thresholds, with many of them hitting all 3. And this seemed to hold true in Chicago, as Allen Robinson, Anthony Miller, and Taylor Gabriel all hit at least 2 of 3 (it’s worth noting that Javon Wims hit 0 of 3, though a 7th round pick is far less of an investment than was put into the players listed above).

Though the Bears have far less of a need at the position this year than they did in 2018, it’s still not out of the realm of possibility they invest a later pick in somebody to improve positional depth, so let’s look to see who from this year’s crop matches the physical profile. As always, these test results are not a way to say how good or bad a wide receiver will be, but simply if they match the physical characteristics of previous players who have excelled in this offense.


Hit All Three

There were 42 wide receivers who did tests at the Combine, and 17 of them hit all three thresholds. They are shown in the table below.

A few thoughts on this group:

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Understanding the Role of Newly-Acquired Free Agents in 2019: Defense

| March 21st, 2019

The Bears have made a number of moves in free agency, and I want to use some advanced statistics to weigh in on their likely role on the roster and value to the team. We looked at the offense yesterday, and now will move to the defense, where the Bears will be replacing two starters.

Buster Skrine

Nickelback Bryce Callahan followed Vic Fangio to the Broncos, and the Bears replaced him with Buster Skrine, who was a bit cheaper ($5.5 million/year vs. $7 million/year) and has been a bit healthier (5 games missed vs. 12 games missed in last 3 years). According to The Quant Edge, both players have spent the majority of their time over the last three years at nickel, though Skrine has spent a bit more (roughly 30%, compared to 15%) playing outside.

The table below uses data from The Quant Edge to show how effective each player has been in coverage. In order to increase sample sizes, I looked at Skrine and Callahan cumulatively from 2016-18 (I’ll note this actually helped Callahan and hurt Skrine, lest I be accused of trying to skew the numbers in the Bears’ favor), and for context compared them to averaged 2018 stats from five other nickelbacks who are widely viewed as being quality players: Chris Harris, Aaron Colvin, Tavon Young, Nickell Robey-Coleman, and Justin Coleman.

Based on this data, it is pretty clear to see that Skrine is a downgrade from Callahan, but that is not to say he’s a bad player. Skrine gets targeted more frequently than other nickel CBs, but holds up to the targeting quite well. The only thing that really jumps out poorly there is the TD:INT ratio. Like Callahan, Skrine doesn’t really get many interceptions, and he has given up more scores than you would like to see.

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Understanding the Role of Newly-Acquired Free Agents in 2019: Offense

| March 20th, 2019

The Bears have made a number of moves in free agency, and I want to use some statistics to weigh in on their likely role on the roster / value to the team. Let’s start with a look at the offense.


Mike Davis

Davis has just 238 carries in 4 seasons so it was a little surprising to see the Bears move so quickly to sign him at the start of free agency. But a closer look reveals why they did so.

A few weeks ago I identified the typical physical profile of a running back in this offense, and Davis fits the bill, as you can see in the table below. Thresholds that he failed to hit are highlighted in red.

Davis matches the profile of backs who are usually targeted for this offense. He’s short but well built and has solid acceleration (as evidenced by the first 10 yards of the 40-yard dash) and explosion (as evidenced by the jumps). This doesn’t mean he’ll magically be a stud here after being a role player in San Francisco and Seattle, but it explains a little bit about why he was on the Bears’ radar.

Another way Davis fits is in terms of his skill set. Running backs in this offense are asked to do two things: run between the tackles and catch the ball out of the backfield. The table below shows how effective Davis was doing those compared to Jordan Howard in 2018, with both compared to Kareem Hunt as an ideal (on-field) back for this system. I highlighted cells in red when one running back stood out from the other two in a bad way, and green when one running back stood out in a good way.

A few thoughts:

  • The first thing that stands out is that Davis is better than Howard at running between the tackles, where both were asked to have a majority of their carries in 2018. This can be evidenced by his significantly higher yards/carry average between the tackles last year, when he was comparable to Kareem Hunt in that regard. It’s worth noting that this trend was only really true in 2018; Davis was generally inefficient at pretty much everything prior to that in his career, and Howard had -by far – the worst year of his career in 2018. Still, the Bears are banking on getting the 2018 form of Davis, which would be a running upgrade over 2018 Howard.
  • Sticking with running, let’s take a look at success rates in the bottom two rows. This was one area where I pointed out Howard actually did quite well, and Davis did as well (again in 2018, not so much before that). Since success rate is a measure of staying with or ahead of the chains, this indicates Davis should hopefully be able to continue Howard’s success converting in short-yardage situations.

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How Well has Ryan Pace drafted? (Spoiler Alert: Very.)

| March 18th, 2019

The Bears were really good in 2018, and are poised to be good for the next few years. The man responsible for that turnaround is Ryan Pace. He has used a combination of draft picks and free agents to assemble nearly the entirety of one of the most talented rosters in football.

But somehow Pace doesn’t get his due as one of the best general managers in the NFL, largely because he got a lot of bad press early on as he oversaw three necessary losing seasons to overhaul one of the oldest and worst rosters in the league. But I’m here to fix that today by highlighting just how good he’s been at the most important part of a GM’s job: drafting.

The premise of this study is simple enough: try to find a way to quantify how well teams have drafted since 2015. Of course, that’s easier said than done, because how do you quantify a draft? There is no one perfect metric to measure the success of a draft pick, so instead I used a bunch, hoping that they would combine overall to give us a clearer picture of draft success.

Here are the metrics I used, with a quick explainer for each:

  • 1st team All-Pro nods: This is meant to be a measure of how well a team acquires top-end talent, the guys who can lead your roster to a championship.
  • Pro Bowl berths: Similar to All-Pros, but less demanding. Really good players can be Pro Bowlers without becoming All-Pros. Think of this as a measure of really good but not great starters.
  • Seasons as a starter: This is then intended to measure how many solid players teams acquire in a draft.
  • Career Added Value (AV): Pro Football Reference assigns a value to every season for every player, so I added this up for every draft pick from 2015-18. Higher AV = more total value from your draft picks (at least in theory).
  • Games played: This is more a measure of total depth measure than anything, because it counts everybody on the active roster the same. Basically a measure of how many picks stick around to contribute in some way, even if that’s mainly special teams.

Total data for every team (from Pro Football Reference) can be viewed below, with the teams placed in alphabetical order and average values for each metric on the bottom row.


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Thinking About Compensatory Picks for the First Time in a Generation

| March 12th, 2019

Bears fans are in unfamiliar territory.

For the first time in a long time, they are in position to lose more than they gain in free agency. And it’ll be that way the next few years. This is a good thing, as it means the Bears have finally been drafting well and now have enough talent that they can’t afford to keep everybody.

With that in mind, it’s time to pay attention to compensatory draft picks, a confusing program the NFL runs to reward teams like the Bears that lose talented players in free agency. The general idea here is teams who lose more valuable free agents than they bring in get additional draft picks in the following draft. So the Bears could be looking at compensatory picks in 2020 based on what happens this month with Adrian Amos, Bryce Callahan, and Aaron Lynch.

The Bears haven’t had a compensatory pick since 2009 so it’s understandable if many Bears fans aren’t super familiar with how they work. The exact NFL formula for them is a secret, but some people have done really good work tracking them over the years and figuring the general process out. If you’re really interested, here’s the best detailed breakdown I could find, but for now I’m going to give a primer and go over the basics.


Where The Picks Are

For the very basics, let’s start with where compensatory picks fall in the draft. Nobody is getting an extra 1st round pick based on losing a valuable free agent, so don’t hold your breath there.

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Links with Data: Stop Worrying and Love the Bomb

| March 7th, 2019

By Andrew Link

In part 2 of this crossover series (that nobody asked for), Johnathan Wood and I will take you on a journey of expectations for the third-year Bears quarterback. As discussed in part 1, Mitch Trubisky has struggled with the deep ball. There were a myriad of reasons why but the gist of it is this: Trubisky was below league average, threw almost as many deep passes as anyone in the NFL, and for this offense to take a leap in 2019, that particular portion of the game needs to improve.

Esteemed data man Johnathan Wood has come up with some theories of his own and you can read about those here. And I urge everyone to go and read the full article at Da Bears Blog. But for the sake of simplicity, I will take a few excerpts from said article and share those with you all.

To approach this from a statistics perspective, I used the Pro Football Reference Game Play Finder to break up raw passing statistics into deep (15+ yards down the field) and short (<15 yards past the line of scrimmage). I looked at 19 quarterbacks who were starters in 2018 and had been playing consistently for at least 4 years (full data here). I’ll note that data for deep passes only goes back through 2008, so that’s as far back as I was able to go for QBs who have played longer than that.

Here’s what I found: while some quarterbacks are certainly better deep passers than others, the amount of year-to-year variability for each quarterback is greater for deep passes than short passes. That can be measured through the standard deviation for each quarterback, which expresses how much they vary from year to year in a given statistic (bigger number = more fluctuation). I found this for each quarterback for the main passing statistics, both short and deep, and then averaged them together for all 19 quarterbacks in each category. The results can be seen in the table below.

Pay particular attention to the ratio. That’s a rough measure of how much more variable deep passing statistics are to short ones for a given quarterback from year to year. Yards per attempt and interception percentage are both more than 4 times as variable for deep passes as short ones. That is excellent news for Bears fans, given Mitchell Trubisky’s high interception rate on deep passes in 2018.

I found this to be interesting. This makes sense to a point. Surely throwing the ball deep is going to have some level of pure luck, and as you will see in the videos, there is certainly an element of luck to it. It also makes sense that the deeper the throw, the farther off-target misthrown balls will be. Imagine being able to hit your driver 320 yards and being off by a few degrees. A much larger margin of error than say, someone who hits their 3 wood 230 yards.


Worthy Adversaries

But luck can’t be everything, can it? There has to be more to it than that. I decided to look at some of the other quarterbacks in the league to see what I can key on as areas of improvement for Trubisky as he heads into his 2nd year under head coach and playcaller Matt Nagy. I scoured the tape of some of the best deep ball artists in the NFL: Aaron Rodgers, Drew Brees, Tom Brady, Ben Roethlisberger, and Russell Wilson.

Disclaimer: This second part took so long to produce because I became violently ill after watching so many plays of Aaron Rodgers wearing those horrible yellow uniforms. I am feeling better now, thanks for asking.

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The Trubisky Deep Ball Should Improve

| March 7th, 2019

This is part of a series of collaborations between film guru Andrew Link of Windy City Gridiron and stats guy Johnathan Wood of DaBearsBlog. We’re excited to be working together to bring fans of both sites great content by combining our approaches.


Last time, we identified deep passes as the main thing Mitchell Trubisky struggled with in 2018, and broke down film to see why that happened. Despite making up less than 25% of his pass attempts, 75% of Trubisky’s interceptions came on deep balls, and his completion percentage on those throws was well below the league average as he missed a lot of open targets.

This week, we want to again use stats and film to see why that may or may not improve going forward.

Highly Variable

To approach this from a statistics perspective, I used the Pro Football Reference Game Play Finder to break up raw passing statistics into:

  • Deep (15+ yards down the field)
  • Short (<15 yards past the line of scrimmage)

I looked at 19 quarterbacks who were starters in 2018 and had been playing consistently for at least 4 years (full data here). I’ll note that data for deep passes only goes back through 2008, so that’s as far back as I was able to go for QBs who have played longer than that.

Here’s what I found: while some quarterbacks are certainly better deep passers than others, the amount of year-to-year variability for each quarterback is greater for deep passes than short passes. That can be measured through the standard deviation for each quarterback, which expresses how much they vary from year to year in a given statistic (bigger number = more fluctuation). I found this for each quarterback for the main passing statistics, both short and deep, and then averaged them for all 19 quarterbacks in each category. The results can be seen in the table below.

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As Free Agency and the Draft Approach, a Full Breakdown of the Current Roster

| March 6th, 2019

As NFL teams leave the Combine in Indianapolis, the NFL offseason is about to ramp up. A brief timeline of what’s happening in the next two months:

  • Now: teams manage their current roster, finishing up cutting and re-signing their own players to make sure they’re under the salary cap before…
  • March 13: free agency begins. Teams must stay under the cap at this point, and they can officially sign players from other teams who are not under contract.
  • April 25-27: NFL draft.

Since we are just a few weeks away from the six-week period that features the main roster improvement time of the offseason, it’s a good time to take stock of where the Bears are at.

Current Roster

Let’s start by looking at players they already have under contract. A rough depth chart for that is shown below; players who have not played meaningfully in the NFL are not included. I should also note that I included the Bears’ 4 exclusive rights free agents, because those players are all but under contract unless the Bears decide not to sign them (equivalent to cutting a player currently under contract).


 


Areas to Improve

Now let’s take a closer look at that roster to see what areas need to be cleaned up, ranked roughly from most-to-least pressing.

  • Nickel cornerback. Sherrick McManis filled in admirably after Bryce Callahan got hurt last year, but he’s a 31 year old career special teamer for a reason. I’d feel much better about this position group, both in terms of starters and depth, if a new starter at nickel was signed and McManis slots in to a backup role next to Kevin Toliver.

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Mathematical Proof the Bears Need More Explosive Plays on Offense

| March 4th, 2019

I recently ran across this Tweet from NFL Matchup on ESPN – a terrific account you should definitely follow on Twitter if you want to be a better educated football fan. It got me thinking about Chicago’s offense and explosive plays.

Seeing as I’ve already written about Mitchell Trubisky’s struggles throwing the ball deep and Jordan Howard’s lack of explosive runs, I figured the Bears probably ranked towards the low end in this area. Using Pro Football Reference’s fantastic Game Play Finder, I was able to track these stats for every team in 2018 (full data here, slight discrepancies for the 17 teams shown in Tweet above, but all were within 1 or 2 plays).

As you can see in the table below, the Bears did indeed not do very well when it came to explosive plays.

We can see here that the Bears were slightly below average in every category, meaning there is need for improvement in explosive plays across the board. I’ll also note that percentages are calculated simply: (explosive plays/total plays)100; I figured this might be a useful metric since there is a some difference in how many plays teams run, especially when you split it up into run and pass plays.


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Jordan Howard’s 2018 Struggles Get “The Data Treatment”

| March 1st, 2019

It’s no secret that Jordan Howard struggled in 2018. DBB’s Andrew Dannehy detailed those struggles in a column a few weeks ago. Despite getting 250 carries – 6th most in the NFL – he didn’t reach 1,000 yards thanks to a dismal 3.7 yards/attempt, the 4th worst average of the 23 running backs who averaged at least 10 carries per game.

And lest we be tempted to blame this on Chicago’s offensive line, it’s worth pointing out that the Bears were 5th in total yards gained before contact and 9th in yards/carry before contact, per ESPN’s NFL Matchup. Tarik Cohen, who ran behind the same offensive line, averaged close to a full yard per carry more than Howard (4.5 vs. 3.7).

So I don’t think it’s fair to blame Chicago’s offensive line for Howard’s struggles. It is worth noting that Howard averaged only 1 yard before contact this year, one of the lowest marks in the league (PFF). Tarik Cohen averaged 2.3 yards before contact, one of the better marks in the NFL. So I think that stat says more about Howard (and how he was used) than the offensive line.

To figure out where it all went wrong for Howard, I took a closer look at a few different advanced metrics used for running backs. The first is success rate, which can be thought of as a measure of staying ahead of the chains. A run is successful if it:

  • picks up 40% of the yardage needed on 1st down
  • picks up 60% of the yardage needed on 2nd down
  • picks up 100% of the yardage needed on 3rd or 4th down

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