Denver Broncos Run Defense Trends

This is a look at the Broncos run defense over the course of the season. I’ll be looking at eight key factors:

– Yards per carry in the game against the Broncos
– Yards per carry over the course of the season
– The difference between the two
– Difference between the two as a percentage (the difference divided by game yards per carry)
– Runs of 10 yards or longer
– Runs of 10 yards or longer as a percentage of the total runs
– Runs that went for negative yardage
– Runs that went for negative yardage as a percentage of the total runs

I didn’t include things like total yards because those are dependent on things like if a team is ahead or not. Teams that are behind by a large margin in a game tend to run less. So total yardage numbers are more an indicator of whether a team is in a close game moreso than ability to run.

Hopefully by doing this we’ll be able to see what trends arise, if any, over the course of the season.

Here is the link to the table and the included charts.

For just a few charts of the data, here you go.

Now to sum it up I’ve included a chart that shows the trend of defensive play by difference percentage but I included the injuries of key players as well as when they returned.

Defensive Trends

You are free to draw your own conclusions but the more I look at this the run defense was over hyped by two very strong games. While losing two starters along the defensive line (DE Derek Wolfe and DT Kevin Vickerson) obviously hurts, the run defensive breakdown clearly began before they got hurt.


How Do Teams Fare When Playing a Third Time in a Season?

So it looks like this season the Broncos and Chiefs may be the 122nd time two teams will meet for a 3rd time in a season.  Of those 122 times, 20 times one team went 2-0 in the regular season before facing the same team again in the playoffs. I wanted to look to see how these teams did when they match up again in the playoffs. Thanks to the miracle that is Pro Football Reference I was able to gather all of this data and take a look. This won’t be too indepth, just a look to see what history shows for these rare cases.

Here is a link to a table with those 20 teams.

In the 20 playoff games that were played the team that went 2-0 in the regular season won the playoff game 13 times. Dallas and Pittsburgh have beaten a team twice and met in the playoffs three times while Green Bay, New York Giants, Kansas City Chiefs, and the Tennessee/Houston Titans/Oilers did it twice. The Browns have been on the receiving end twice and lost both playoff games as well. Denver has never done it before but was on the receiving end in 1993 when the Raiders swept them in the regular season and then beat them in the playoffs.

Overall it’s a small sample size, but something fun to look at going forward if the Broncos and Chiefs get to meet in the playoffs. If they do meet, 13-7 isn’t a bad track record to go on, though it’s not perfect either.

The Broncos Numbers Updated With Week 15’s Data

While it was a tough loss to the San Diego Chargers, it doesn’t stop the march of the season or the collection of data so the pages have been updated:

Broncos defensive line pass rushing productivity
Broncos running back data including yards after contact, negative runs and long runs
Broncos wide receivers, tight ends and running backs receiving data which includes yards per target, touchdown percentage and the passer rating when targeting each player

Enjoy! I’ll be reviewing more of the run game this week than normal since it’s a longer week and the longest run of the week was 6 yards. I’ll give some foreshadowing, the offensive line doesn’t look good. I’m also hoping to review the safety play as well if time permits.

Does Playing Thursday Games Really Impact Play On the Field?

After the terrible performance from the Denver Broncos coaches and players on Thursday night, many cried out that this was a sign that Thursday night games caused below-par performance from both teams and leads to less enjoyable games to watch. I wanted to look at this by studying the Thursday night games of this season. To do this I looked at a few key areas:

– Points per game- Total yards per game
– Passing yards per attempt
– Rushing yards per attempt
– Penalties per game

I looked at these five because points and yards are a decent indicator of the offensive play of the game while the two efficiency metrics (the two yards per attempt numbers) show if the teams were efficient in getting their yards and points. Lastly I added penalties because those are one of the bigger indicators of preparations and sloppiness of a teams play. These five are hardly perfect but provide a good sampling of what the game was like both in magnitude and quality.

I’ll take these and compare each teams performance on Thursday against their season averages to see if they are above or below those averages. Finally I’ll include a percentage difference, that this means is that I take the difference between their Thursday game and their seasons averages and then divide it by the season average to get a percentage difference.

For example if a team normally averages 25 points a game but had 20 points on Thursday, that’s a difference of -5. Now take that -5 and divide it by the season average of 25 and this team underperformed by 20%. Another example is a team that normally has 5 penalties but only has 3 on Thursday has a difference 2 penalties and did better by 40%.

Here is a link to the table.

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Broncos Run Game Breakdown – Week 14

So each week I’ve decide to break down about three to six rushing plays for the game that week so we can see how the offensive line, tight ends and running backs did that week. To do this I’ll take all the plays and randomly select three plays and add more depending on the time. I’ll take these plays and break them down using clippings from the game. For each play we will start with the down and distance, the personnel formation and grouping as well as the result of the play. We will also break the play into parts, the pre-play, mid-play, and the end. To get a better view of the image just click on it, it will open in a new tab. This will be the first running breakdown I do this season. Another feature is after going through each clip you can view it as a slideshow to see how the play progresses with the notes.

How to Understand the Images:– Red lines are defenders actions
– Green lines are blockers
– Blue lines is the running back
– I include small caption boxes that help explain what is going on, pointing with black arrows to appropriate spots on the field.

I won’t be doing as many this week due to other obligations, also since the run game was so much more effective each play required more time to study and clip anyways.

Play 1

– Down and Distance: 2nd and 10
– Personnel: 3 WR, 1 TE, 1 RB
– Result: 20 Yard Gain


KM 1 Pre Play Edit

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Fun Facts – Pre Week 14

Not So Happy Fun Facts:

– The Broncos two running backs in week 13, Knowshon Moreno and Montee Ball, got hit behind the line of scrimmage on 64% of their runs, the most this season for the Broncos since week 1.

– During his limited time this season Champ Bailey has just plain struggled. He has been targeted 20 times and allowed 15 receptions for 161 yards and 1 touchdown. When quarterbacks target him they have a passer rating of 114.8.

Happy Fun Facts:

– Despite being without DE Derek Wolfe against the Chiefs, the Broncos actually managed to be a better pass rushing team with DE Robert Ayers and DT Malik Jackson taking his snaps. With Wolfe on the field the Broncos average pressure on 8.61% of the time but when Wolfe isn’t on the field the Broncos get pressure 9.17% of the time. The Broncos also have three defensive lineman who rank in the top 5 of their positions for pass rushing productivity, which is total pressures divided by total pass rushing snaps. These three are Robert Ayers (5th among DE’s), Malik Jackson (1st among DT’s) and Terrance Knighton (4th among DT’s).

– RB Knowshon Moreno leads the NFL’s running backs in Win Probability Added and Expected Points Added. What this means is Moreno adds more per play in terms of production towards winning and scoring than any back in the NFL. For more info on WPA and EPA click the link.

– Safety Rahim Moore may be out by his two replacements, Mike Adams and David Bruton, haven’t given up a touchdown since they took over for him. Adams also made the game saving pass deflection at the end of the game.

NFL Hall of Fame Class of 2014

The list of potential Hall of Fame members for the NFL class of 2014 has been narrowed down to 25 with the list being released just a few weeks ago. The NFL Hall of Fame selection process is a tricky thing since you have players across positions and eras, and that doesn’t even take into account non-players who are up for nomination. As a fan and student of the NFL it’s a hard thing to compare these players to narrow down the best players but for fun I wanted to try. I’ll be grading on seven categories:

– Games Played
– Career AV
– AV per Year
– Pro Bowls
– Pro Bowls per Year
– All-Pro Awards
– All-Pro Awards per Year

I’ll explain the metrics below. To do this comparison I wanted to solve the two big issues that arise from these conversations:

1. Comparing Across Positions

This is solved with Approximate Value. Now for those who don’t know Approximate Value (AV) is a metric created by Pro Football Reference to help compare players from different positions and eras. The math is more than a little tricky but let me quote it’s creators:

“AV is not meant to be a be-all end-all metric. Football stat lines just do not come close to capturing all the contributions of a player the way they do in baseball and basketball. If one player is a 16 and another is a 14, we can’t be very confident that the 16AV player actually had a better season than the 14AV player. But I am pretty confident that the collection of all players with 16AV played better, as an entire group, than the collection of all players with 14AV.”

“Essentially, AV is a substitute for — and a significant improvement upon, in my opinion — metrics like ‘number of seasons as a starter’ or ‘number of times making the pro bowl’ or the like. You should think of it as being essentially like those two metrics, but with interpolation in between. That is, ‘number of seasons as a starter’ is a reasonable starting point if you’re trying to measure, say, how good a particular draft class is, or what kind of player you can expect to get with the #13 pick in the draft. But obviously some starters are better than others. Starters on good teams are, as a group, better than starters on bad teams. Starting WRs who had lots of receiving yards are, as a group, better than starting WRs who did not have many receiving yards. Starters who made the pro bowl are, as a group, better than starters who didn’t, and so on. And non-starters aren’t worthless, so they get some points too.”

What AV does is create a nice broad stroke to view a player. Like Doug said, it’s usefulness increases as times passes. If you want to get into the math you are free to do so. While it is not a perfect metric, it is by far the most complete and balanced way to view players who played in different eras and at different positions. That is why this is listed as the 1st big problem with comparing potential Hall of Fame candidates.

There is a post-script, AV is an evolving metric, it recently improved it’s special teams methodology, and will likely be tweaked into the future, but large sweeping changes are not the norm, only small changes.

2. Consistent, Long Career versus Short, Exceptional Career

To look at this one I included in my table both totals for games played, Approximate Value, Pro Bowls and Pro Bowls. To off-set those which shorter careers I’ve also included a rate metric total over years played. So I take AV divided by years. This way we get to see how each player does on a per year basis. I do need to state to assist this method I didn’t just use purely “years in the league” which is susceptible to over-valuing injuries, I took total games and divided by 16 (or 14 depending on the era) that way we get relative seasons instead of just vague “years in the league.”

Again this is a flawed way to study these players, but it 100% vilifies those who say length of career shouldn’t matter, only quality of those years but it also rewards those who play at a consistently good level for years and year. Now I included an average rankings number as well, this is how each player ranked on average for each category. So there are 7 categories and there are 25 players so if a player ranked 1, 2, 3, 4, 5, 6, 7 then their average ranking would be 4.00 or if a player was ranked 25, 1, 17, 12, 11, 19, 10 their average ranking would be 13.57. For my own benefit I created a weighted ranking system where 1 equals a full “vote.” What this means if a category has a value, or “vote,” of .50 that means it’s relatively half as valuable while 1.50 is twice as valuable. To put it simply getting 1st place in a category valued at 1.00 is going to matter more than getting 1st in a category valued at .75.

– Games Played: .75
– Career AV: 1.00
– AV per Year: 1.25
– Pro Bowls: .75
– Pro Bowls per Year: 1.00
– All-Pro Awards: 1.00
– All-Pro Awards per Year: 1.25

I don’t give each metric matching value due to me viewing them as not equal. I think an All-Pro award is more valuable than a Pro Bowl. This weighted rankings is purely my opinion.

So How Does The Table Look?

Here is a link to the table since Word Press doesn’t feel like supporting tables for it’s in browser creation tools. You are free to copy and paste into Excel and fiddle with the table as much as you want to create your own list.

Now if I had to make my pick these are the five men I’d pick:

– WR Marvin Harrison
– OT Walter Jones
– LB Derrick Brooks
– OG Will Shields
– Owner Eddie DeBartolo Jr.

My final cuts were DE Michael Strahan, DB Aeneas Williams, and RB Terrell Davis. My finalists are highlighted in bold on the spreadsheet. While it may seem I just took the top 4 players in the rankings, I’m actually pretty happy with that list. You are getting two of the best offensive lineman of a decade, one of the best linebackers ever, and a wide receiver who helped shape a decade and dynasty with the Colts. As for DeBartolo, I choose him out of bias, I grew up in southern Oregon and the San Fransisco 49ers were the team to be a fan of for my youth in the 1980’s and 1990’s and DeBartolo was a huge reason for that. I do think a non-player will get in again this year and while I think George Young deserves to get in as well, I broke the tie with a bit of bias, but I’d be happy with either.

To wrap up this is just one way I wanted to study this potential Hall of Fame class, it’s not perfect and it’s not meant to be set in stone, each person will have their own criteria for the Hall, I just wanted to present a tool to use and give my opinion on the topic. I’ll likely discuss this topic again as the list gets narrowed down the the eventual finalists who get to enter that coveted Hall.