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Super Bowl Preview: The Data Prediction

| January 29th, 2020

I’m very excited for this Super Bowl matchup between two of the best teams in the NFL. Here’s what I’ll be watching for on Sunday night.


When Kansas City Has the Ball

  • I can’t wait to see Patrick Mahomes vs. San Francisco’s defense. The NFL’s best QB against the NFL’s best front 7. How can you not love that?
  • San Francisco has played 4 games against the top 10 QBs in passer rating this year (Wilson 2x, Lamar Jackson, Drew Brees). 3 of the 4 averaged less than 7 yards per attempt, threw 2 or fewer TDs, and led their team to 27 or fewer points. San Francisco’s defense is really good.
  • The 4th was Drew Brees, who averaged 8.7 yards/attempt, threw 5 TD, and put up 46 points. What did Brees do differently? He got rid of the ball before he could get hit. His average time to throw was 2.45 seconds, which was faster than any QB in the NFL as a whole this year (the other 3 were all over 2.7 seconds). As a result, Brees didn’t get sacked. This meant that he had to throw the ball short, with his average completion traveling only 5.1 yards past the line of scrimmage. Instead, he relied on his pass catchers to pick up yards after the catch, and they responded with an average of 6.9 YAC.
  • Patrick Mahomes generally doesn’t get the ball out super fast; his average time to throw this year was 2.82 seconds, and it was 2.91 seconds in 2018. Yet he’s had 5 games in his career where the ball has come out in under 2.6 seconds, and his results there have been remarkable: 73% completion, 10.2 yards/attempt, 19 TD, 0 INT, and only 6 sacks on 198 dropbacks. His team has averaged 35 points per game in those contests too. If you want to get even pickier, he’s had 2 games getting the ball out in under 2.5 seconds: 79% completion, 11.5 yards/attempt, 9 TD, 0 INT, 1 sack. He’s capable of getting the ball out quickly and effectively, even if it’s not his preferred style.

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What Changed in the Passing Game: Volume III

| January 24th, 2020

Today I want to look back at two areas of concern I noted for Trubisky last off-season: deep passes and performance against good defenses.


Deep Passes

Last year, I noted that Trubisky was really good at short passes (15 yards or less past the line of scrimmage) and really bad throwing the ball deep. I also found that short passing performance tends to be less variable year over year than deep passing, which gave us a reason to be optimistic about Trubisky heading into 2019.

Let’s see how that theory played out in 2019.

A few thoughts:

  • So much for short stuff being consistent. Trubisky’s completion percentage, yards/attempt, yards/completion, and touchdown rate all plummeted from 2018 to 2019.
  • Some of the completion percentage can be accounted for by drops (as I have previously addressed), but not nearly all of it on the short stuff. Despite throwing shorter passes in the short stuff, Trubisky completed fewer of them. The end result was an extremely inefficient short passing game.

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What Changed in the Passing Game: Volume II

| January 23rd, 2020

Yesterday, it was discovered that the pass blocking and drops by pass catchers went from really good to about average.

The hypothesis, then, is that the quarterback was largely responsible for the Bears having one of the worst passing games – and thus worst offenses – in the NFL. So today I want to look at Mitchell Trubisky’s performance more closely to see what it can tell us.

On the surface, Trubisky certainly was awful in 2019. He completed 63.2% of his passes (18th in the NFL), averaged 6.1 yards/attempt (last), and posted a passer rating of 83.0 (28th). This was a big step back from 2019, when he was near average in all of those marks (66.6% completion, 14th; 7.4 yards/attempt, 18th; 95.4 rating, 16th).

Evaluating a quarterback’s play statistically can be tricky, because his stats depend both on his offensive line’s ability to block for him and his RBs/WRs/TEs’ ability to catch his passes, both of which are outside of his control. That’s why I started by looking at the offensive line and drops, both of which were worse in 2019 than 2018 but not nearly bad enough to explain bottom 5 production from the quarterback.

It’s also worth noting that Chase Daniel’s production barely changed between seasons. In 2018, he completed 70% of his passes, averaged 6.8 yards/attempt, threw 3 TD and 2 INT, and posted a 90.6 passer rating. In 2019, he completed 70% of his passes, averaged 6.8 yards/attempt, threw 3 TD and 2 INT, and posted a 91.6 passer rating. To be fair, it’s a small sample size – he played 2 games and threw around 70 passes each year – but still, this is at least anecdotal evidence to support the notion that the offense as a whole didn’t change all that drastically.


Advanced Stats

With that said, let’s look more closely at Trubisky’s performance to see if we can hone in on what changed, besides worse pocket presence and less running impact, which were touched on in previous articles. This is going to focus on passing. We’ll start by looking at a smattering of advanced statistics, which come from a combination of Next Gen Stats and Pro Football Reference.

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What Changed in the Passing Game: Volume I

| January 22nd, 2020

It stands to reason that if the offense was mainly responsible for the Bears’ 2019 regression, and the running game didn’t change all that much, most of the regression came from the passing game. And a quick look at the stats backs that up. In 2018, the Bears were 9th in completion percentage, 18th in yards/attempt, 14th in passer rating, and 10th in sack percentage. In 2019, those ranks fell to 14th, 32nd, 24th, and 23rd.

So what went wrong in the passing game? Generally, there are 3 components to examine: the pass protection, the pass catchers, and the quarterback. Let’s look at each one by one.


Pass Protection

Evaluating pass protection statistically is difficult, but thankfully advanced statistics to help with this are getting better. A number of them are shown below, with their ranks out of 32 NFL teams in parentheses. Average time to throw is from Next Gen Stats, Average time to pressure and pressure rate is from Pro Football Reference, and Pass Block Win Rate – a measure of how often a QB has a clean pocket for at least 2.5 seconds, is from ESPN Metrics (source for 2018 and 2019).

 

As I tried to make sense of these numbers, it seemed to me that the change in NFL ranks was often greater than the change in the actual value. Sure enough, it seems that pass blocking was slightly better across the league in 2019 than 2018. The median average time to pressure increased from 2.4 to 2.5 seconds, the median pressure rate dropped from 24.1% to 22.6%, and the median pass block win rate increased from 50% to 59%.

Looking just at the Bears’ numbers, they generally got a little worse in pass protection, but their drop in the rankings looks worse than it is because the rest of the NFL got better. The average time to throw didn’t change all that much and the pressure got there a little faster, but the Bears still ranked right around average both in pressure rate and pass block win rate.

If the pass protection didn’t get much worse, how do we account for the massive uptick in sacks? The Bears went from giving up 33 sacks in 2018 (6.1% of dropbacks) to 45 in 2018 (7.2% of dropbacks).

Well, sacks aren’t only due to the pass blocking, they’re a result of the quarterback as well. Lester Wiltfong of Windy City Gridiron breaks down film on every sack and assigns blame to the person or people he deems responsible (he also splits blame if multiple people mess up).

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What Changed in the Rush Game: Volume II

| January 16th, 2020

Yesterday I dove into Chicago’s 2019 ground game to figure out where it all went wrong. There I found that the Bears missed Mitchell Trubisky’s legs, didn’t change how they used their 2 main running backs much, and saw the largest regression on runs outside of the tackles.

Today, I want to look a little more closely at directional running.

Let’s start by looking at yards per carry, which can be seen in the figure below. Bar height is proportional to yards per carry (ypc), numbers in parentheses are NFL rank out of 32 teams, and bars are color coded according to that. Green = top 10, red = bottom 10, yellow = middle 12.



A few thoughts:

  • I don’t think it’s a coincidence that the red all comes on the right side and the Bears had injury issues at right guard and right tackle this year. The yards/carry actually improved behind left tackle and left guard compared to 2018.
  • The numbers look even better up the middle and behind left guard when you look at runs after the Bears swapped Cody Whitehair and James Daniels back to their 2018 spots. After that, the Bears averaged a combined 4.7 yards/carry on runs to those areas.
  • Runs outside the tackles were fairly poor on both sides, which is new since 2018. I think this speaks more to the blocking of WRs and TEs than the offensive line. The Bears got fewer fewer snaps from Trey Burton, Josh Bellamy, Kevin White, and Taylor Gabriel in 2019, and it appears the young players who took those snaps may have struggled in run blocking.

Now I want to look at this from another perspective using success rate, which can generally be thought of as a measure of staying ahead of the chains. A run is considered successful if it:

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What Changed in the Rush Game: Volume I

| January 15th, 2020

Chicago’s rushing attack was woeful in 2019, finishing 27th in the NFL in rushing yards (91 yards/game), 29th in yards per attempt (3.7 yards/carry), and 26th in success rate on rushing attempts (44%). All three marks showed a decrease from 2018, when they were 11th (121 yards/game), 27th (4.1 yards/carry), and 10th (48%) in those three metrics.

This happened despite having fairly decent consistency in personnel. The starting offensive line was the same (when healthy), and the Bears saw only three primary rushers in both seasons. Tarik Cohen and Mitchell Trubisky were 2 of the 3, with the main rusher changing from Jordan Howard in 2018 to David Montgomery in 2019.

Today I want to look at the running game from a variety of angles to try and figure out what changed to account for the dip in production.


Player vs. Player Comparison

Let’s start out by comparing each player from season-to-season. First, I’ll look at the players who accounted for the majority of rushing attempts each year: Jordan Howard and David Montgomery. Their usage and production was remarkably similar in the two seasons, as you can see in the table below.

Similar playing time, similar carries, similar efficiency. The two were basically indistinguishable from each other, at least on the surface. That really makes you question whether it was worth getting rid of Howard and trading up for Montgomery in the 3rd round last year. At least for 2019, the answer is a resounding no.

This post is focused on rushing, but look at those bottom two rows. One of the reasons to swap Howard out for Montgomery was supposed to be that Montgomery can feature more heavily in the passing game, and thus make the offense less predictable and harder to defend. That didn’t happen in 2019. One of Chicago’s big problems in 2018 was that they were too predictable based on personnel (Tarik Cohen = pass, Jordan Howard = run, Anthony Miller = pass, etc.). In 2019, the offense ran the ball 50% of the time when Montgomery was on the field and only 24% of the time when he wasn’t. For Cohen, those numbers were 25% and 52%. That’s too big of a swing in tendencies based on personnel.

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Don’t Blame Defense for Offensive Regression

| January 13th, 2020

Chicago scored only 17.5 points per game in 2018, the 4th worst mark in the NFL. This was a significant drop from 2018, when they were 9th best in the NFL at 26.3 points per game. I’ve seen some people argue that this is mainly due to Chicago’s defense, which scored 5 fewer touchdowns and forced 17 fewer turnovers in 2019. The logic then was that the offense in 2018 was just as bad, but it was overshadowed by a dominant defense that handed them points on a regular basis.

This argument made me curious, so I dug into the numbers to see if it held up.


Non-Offensive Points

The 2018 Bears had 44 points that were scored by their defense and special teams, while the 2019 version had 16*. If you remove those from the season totals, the 2018 offense scored 277 points (23.6 per game) while the 2019 version scored 264 (16.5 per game).

That means Chicago’s offense scored 7.1 points per game more in 2018 than 2019. The total points scored dropped by 8.8 per game, so clearly the bulk of that was from offensive points, not defense/special teams.

*Quick disclaimer: I tallied touchdowns, field goals and safeties, and applied values of 7, 3, and 2, respectively, for each. These numbers might be a little off because not all touchdowns result in exactly 7 points due to missed extra points or going for 2.


Points Off Turnovers

Of course, points directly scored by the defense is only half of the original argument. The 2018 defense also forced far more turnovers, in theory setting the offense up in better field position for more easy points. In order to see what effect this had, I looked at points scored off turnovers for each team using Pro Football Reference’s Drive Finder. The table below shows the data.

Despite forcing far more turnovers, the Bears didn’t actually get many more points from them. Part of this may because of where the turnovers happened; the average starting field position for these drives was the Chicago 42 in 2018 and the opponent 47 in 2019. Accordingly, the Bears got 2.4 points per drive off turnovers in 2018 and 3.3 in 2019. Because of this, offensive scoring following a defensive turnover changed by only 0.7 points per game from 2018 to 2019.

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Big Picture Stats: What Changed from 2018 to 2019?

| January 8th, 2020

The 2018 Chicago Bears went 12-4 and outscored their opponents by 138 points, the 4th best mark in the NFL. Expectations for the team were sky high heading into 2019, but Chicago responded by falling flat. They finished 8-8 and were actually outscored by 18 points over the course of the season.

So what changed from 2018 to cause such significant regression? That’s exactly what I’ll be looking at over the first part of the off-season to see what areas the Bears need to prioritize improving for 2020. Let’s start today with a general overview of all three phases.


Offense

Chicago’s offense was not great in 2018, but it took a decided turn for the worse pretty much across the board in 2019, as you can see in the table below. DVOA is a metric from Football Outsiders intended to be an all-encompassing measure of how well a unit performs. Values in parentheses are NFL rank out of 32 teams.

A few thoughts:

  • The 2018 offense could generally be described as average to slightly below average. The 2019 version was one of the 4-5 worst in the NFL.
  • The run game actually didn’t change all that much, remaining fairly consistently bad in both years. This is probably why the Bears shook up their offensive coaching staff this off-season. I’ll have a more detailed look at what did and did not change in the run game in the next few weeks.
  • The passing offense went from average to possibly the worst in the NFL. Some – but certainly not all – of this can be attributed to a decrease in pass protection, though notice the pressure rate allowed was still average, making pass blocking one of the strongest areas of the offense. I’ll take a much closer look at the passing game in the near future.
  • Pretty much the only area where the Bears actually improved was that they turned the ball over less. This is why their DVOA – which heavily weights turnovers – didn’t fall as far as most of the other statistics suggest it should have.

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Heading into the 2020 Off-Season, a Primer.

| January 6th, 2020

A disappointing 2019 season is over, and it’s time to start thinking about what the Bears can do over the next several months to set up a 2020 rebound. To start the offseason, let’s take a look at where things currently stand for the roster.


Salary Cap Situation

The 2020 salary cap has been projected between $196.8M and $201.2M. We’ll play it safe and use the low end of that estimate. As you can see in the table below, the Bears don’t currently have a lot of money to work with (bottom row). All cap information courtesy of Spotrac.

So the Bears currently have around $13.5M in cap room for 2020, though that could be around $18.5M if the cap hits more optimistic projections. Now let’s look at who they lose from 2019.

NOTE: these numbers are before the Eddie Jackson extension. I’ll update once the exact figures for that come out, and then remove this note. I’m guessing they’ll only drop the 2020 space by 1/5 of his signing bonus, which will probably come out to $2-3M.


Key Free Agents

The Bears actually don’t have a huge number of free agents this year, at least in terms of players who were significant contributors. I’ll briefly list and discuss the main ones here, sorted by position.

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A Closer Look at New OL Coach Juan Castillo

| January 2nd, 2020

The Bears didn’t wait long to start attacking the offseason following a disappointing 2019. Just three days after their last game and one day after firing offensive line coach Harry Hiestand, they hired his replacement in Juan Castillo. He brings a wealth of experience to the role, having filled the same position in Philadelphia under Andy Reid from 1998-2010, in Baltimore from 2013-16, and in Buffalo from 2017-18.

Castillo is expected to be heavily involved in designing and coordinating the run game in Chicago, which will be revamped this offseason after 2 unproductive years under Hiestand and former offensive coordinator Mark Helfrich. Accordingly, I dug into how well run games have fared under Castillo in the 19 years he’s served as an offensive line coach and/or run game coordinator. I did this using DVOA rankings, from Football Outsiders, which are a generally solid all-encompassing metric to evaluate both the rushing and passing production from an offense. The ranks for rushing and passing DVOA can be seen in the table below.

There’s a lot of data to parse through here, and I think you can look at it fairly from both an optimistic and pessimistic viewpoint. Let’s take a brief look at each perspective:

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