This is the second part of a two-part series. In part one, we looked at consistency trends of quarterbacks throughout the NFL. Here we are going to examine in greater detail the consistency and production of the four NFC North quarterbacks.

The previous installment featured a study of all 24 NFL quarterbacks who have started at least twenty games for the same team between 2011 and 2012.  Conveniently, Jay Cutler, Christian Ponder, Aaron Rodgers, and Matthew Stafford—all four quarterbacks in the NFC North—fit that description.  So let’s look a little closer at those four in an effort to better understand just how they compare to each other in terms of consistency and overall production.

Consistency

The overall numbers showed that Aaron Rodgers was far and away the most consistent of the four quarterbacks; his passer rating standard deviation of 20.5 marked him as the third most consistent in the NFL. Matthew Stafford came in at 23.5, slightly more consistent than average, while Christian Ponder was on the other side of average with a standard deviation of 27.2. With a standard deviation of 30.0, Jay Cutler came in as the least consistent quarterback in the entire league.

Let’s dig in a little deeper to see more clearly the distribution of their games relative to their average passer rating that season. The chart below compares the percentage of games that are within 10.0 points of their average, between 10.1 and 20.0 points of their average, between 20.1 and 30.0 points of their average, and more than 30.0 points away from their average. The table also lists the percentage of games in which the quarterback is more than 50 points away from his average, but it should be noted that this is a subset of the 30 point group and those two are therefore not exclusive of each other.

There are a few interesting trends to note here. First, observe that Rodgers, the most consistent quarterback, has a significantly lower percentage of game right at his average than either Stafford or Ponder. What makes Rodgers so consistent is that he avoids the extremely varying games that are more than 30 points from his average passer rating. All of his games basically fall within a range of 60 points (i.e., ± 30 from his average).

That is not the case for the other quarterbacks, particularly Cutler and Ponder; nearly one-third of their games fall more than 30 points from their average passer rating. A large reason why Cutler has the largest standard deviation an insanely high proportion of his games — 16.0% — fall more than 50 points from his average. This is more than four times the NFL average and nearly doubles that of any other quarterback.

Overall production

It is important to note that all of the statistics discussed to this point have been about quarterback’s average and their production relative to that average. This ignores the difference between the average production of the quarterbacks, which can be fairly substantial when you consider that Aaron Rodger’s average passer rating of 114.9 is nearly 30 points better than that of Matthew Stafford, the second-best quarterback in the division with an 88.1 passer rating.

So let’s put some clarity in this discussion by looking at real numbers instead of simply averages. The table below shows the percentage of games that have fallen in various passer ratings by the average NFL quarterback (the 24 in the overall study) and each of the four NFC North quarterbacks. The graph below that shows the same numbers in a visual format.

These numbers show three clear groupings in the NFC North quarterbacks. Ponder produces an abnormally high number of bad games without really having many really good ones (only one game with a passer rating above 120), making him a below-average NFL quarterback. To be fair, Ponder has only finished his second year, so he still has significant room to grow. Stafford and Cutler both have roughly average numbers, at least in terms of their most typical passer ratings, although Cutler does have an atypically high number of really bad games.

The true standout here is Aaron Rodgers, as he incredibly has no games with a passer rating below 75 in the last two years (in fact he has none below 80); he is the only quarterback in this study who can claim that remarkable feat. The typical Rodgers game resides in the very good category, with relatively equal numbers of average and great games.

This clearly illustrates the difference between Rodgers and the rest of the NFC North quarterbacks. A bad game for Rodgers, when his passer rating is in the eighties, is an average game for Cutler, Ponder, or Stafford. An average game for Rodgers is a very good or great one for one of the other three.

This is not an earth-shattering revelation. Rodgers is clearly the best quarterback in the NFC North and by most statistical measurements is also the best quarterback in the NFL. It is truly remarkable, however, to look at just how large the gap is between Rodgers and the rest of the quarterbacks in the division.

Conclusion

This is the part for all you lazy bums who don’t feel like doing much reading (that’s all of you, including me). I’m going to put my findings in simple, easy-to-digest bullet points so you can skip all the long, confusing words above!

• Aaron Rodgers is one of the most consistent quarterbacks in the NFL because he is exceptional at avoiding games with extreme passer ratings (relative to his average).
• Jay Cutler is the least consistent quarterback in the NFL because he has an incredibly high rate of games that are either really good or really bad.
• A bad game for Aaron Rodgers is an average game for any other NFC North quarterbacks.

Introduction

Football announcers are fond of saying that an outstanding quarterback is “consistently excellent” — or conversely bashing an underachieving quarterback by saying he “needs to improve his consistency.”

Based on comments like this, there seems to be a prevailing theory out there that the elite quarterbacks in the NFL are separated from the pack by their consistency.  Do the statistics back this assertion up?  Let’s dive in and take a look.

Because I am a giant stats nerd, I just had to dig into this and see if there was any truth to the conventional wisdom. This is the first installment of a two-part series in which I will examine the consistency of NFL quarterbacks. This installment will explore league-wide trends, while the second part will focus on the four NFC North quarterbacks.

To the statsmobile!

Numbers and tables

To find the simplest method possible of measuring quarterback consistency, I looked at the standard deviation of game-by-game passer ratings for quarterbacks in the last two years. Ignoring playoff games, I included only quarterbacks who made at least 20 regular-season starts for the same team between 2011 and 2012. A total of 24 players qualified for this study. These numbers were chosen to find the best middle ground between getting a large enough pool to do a meaningful study and having a large enough sample size for each individual to get meaningful results.

The table below shows the 24 quarterbacks examined, along with their passer rating over the last two years and the standard deviation of their single-game passer ratings. A lower standard deviation means there is less variability — or in other words, that a quarterback is more consistent.

Looking at the spread of this data, we can see that it shows what statisticians call a “normal distribution,” which is a fancy way of saying that the frequency of the numbers peaks around the mean (average) and tapers off toward either end of the range. In this case, the range is roughly 20 to 30.

Lessons

A quick glance also tells us that more consistent does not necessarily equal to better: five of the six least consistent quarterbacks rank in the top ten for passer rating over the last two years. Indeed, there is almost no correlation between a quarterback’s average passer rating and his standard deviation(r²=0.002). In other words, there is no indication that consistency is necessarily a marker of excellence, for a quarterback can just as easily be consistently bad as consistently good.

This makes intuitive sense. St. Louis Rams quarterback Sam Bradford has put up the most consistent passer rating in the NFL the last two years — but no one would accuse him of being an excellent quarterback. There is no value found in being consistently mediocre.

The next two most consistent quarterbacks, however, have been two of the best in recent years. Ask the average NFL fan to name the best two quarterbacks of 2011 and 2012, and the most common answers would likely be Aaron Rodgers and Tom Brady (Drew Brees would be in the mix as well), and indeed, they rank as two of the top three in passer rating. Interestingly, though, seven of the top ten highest-rated quarterbacks rank in the bottom half for consistency.

This suggests that, among the top quarterbacks, what separates the truly elite players from the rest is their ability to avoid bad games and be consistently excellent. The numbers suggest that may be possible, as the correlation between passer rating and standard deviation rises to 0.38 if the sample size is limited to the top ten highest passer ratings It should be noted, however, that 0.38 still represents a relatively low correlation.

Now I want to look briefly at one interesting case for a quarterback who did not qualify for this study because he missed the 2011 season: Peyton Manning. I am looking at quarterbacks playing for the same team, so rather than combine his 2010 and 2012 numbers (which featured him plying his trade in two different cities), I decided to look at his numbers from 2009 and 2010. In those years, Manning posted a passer rating of 95.6 with a standard deviation of 22.2. His passer rating would rank only sixth in this study — likely because he missed out on the passing bonanza that was 2011, when defenses suffered tremendously from the lockout and shortened training camp — while his standard deviation would score him as the fifth most consistent quarterback.

These numbers actually muddy the waters a little bit: Manning falls short of the elite benchmark in passer rating but is still relatively consistent (similar to Ben Roethlisberger).

Conclusion

Those of you who don’t like wading through a whole long article full of numbers — in other words, all of you — can skip straight to this point and read what I learned in easy-to-digest bullet points!

• There is no statistical relationship between consistency and effectiveness for NFL quarterbacks.
• It looks possible, but is not proven, that the truly elite quarterbacks are separated from the merely good ones by being consistently good.
• Second-tier quarterbacks are some of the most inconsistent in the NFL, probably because they fluctuate so often between good and mediocre.

Stay tuned for an upcoming look at the NFC North quarterbacks!

“If only our guys had stayed healthy.”

This common lament from NFL fans at the end of a disappointing season reflects the harsh reality that injuries are an unavoidable part of football.  I don’t particularly like using injuries as an excuse, but there is no denying that the health (or lack thereof) of certain key players can have a dramatic impact on a team’s fortunes in a season.

With that in mind, I thought I’d take a look at the four teams in the NFC North to see how they were affected by injuries in 2013.  I had some difficulty here in trying to find one perfect metric for looking at injuries, and ended up settling on four different ways.  No one of them is perfect , but together they should give you a pretty good idea of how badly teams were impacted by injuries.  Before we get to the numbers, let’s take a minute to briefly explain each method.

Procedure

WARNING: if you don’t care about how I did what I did and just want to see the results, you should save yourself a lot of time and skip to the results section.

The first metric I examined was games missed due to injury.  This simply counts any time a player on the roster is ruled inactive for a week due to an injury.  This is useful for seeing how much injuries impacted the roster as a whole, but completely ignores the value of a player.  A superstar quarterback missing a game means a lot more to the team than a fringe roster player who only plays on special teams, but they both count the same here.

The second metric, therefore, is starts missed.  This looks only at games missed due to injury by players expected to be starters with a fully healthy team (so the standard eleven on offense and defense, plus a third wide receiver and cornerback).  This helps distinguish in player value a little bit, but still treats all starters equally when in fact that is not close to being accurate.

The third metric looks at starts missed by Pro Bowl performers, that is, players who have made a Pro Bowl since 2012 playing for their current team.  The idea here is to look at players who are high-impact starters expected to be the best players on the field.  The flaws are that the Pro Bowl voting system is far from perfect, and again, there is still a difference in value between a star quarterback like Aaron Rodgers and a nice fullback like John Kuhn, both of whom qualified as Pro Bowl players here.

Finally, I looked at money lost due to injuries, assuming each players gets 1/16^th of his cap for the season.  So if a player has a cap hit of $16 million for the year and missed one game due to injury, the team just “lost” $1 million.  The general idea is that teams pay their better players more money, but there will always be guys who are overpaid or underpaid, sometimes dramatically (Chicago defensive end Julius Peppers, for example, had the second highest cap hit in the NFC North this year but did not play anywhere close to that level).  Players who particularly get overlooked here are young players playing well on relatively small rookie contracts (think of guys like safety Harrison Smith and tight end Kyle Rudolph in Minnesota).

So again, let me emphasize that no one approach is perfect here.  Different teams will appear to have larger injury issues than they actually did (or vice-versa) if you look only at one of the four metrics, but looking at all four should generally give us a solid idea of how teams fared relative to each other.

I should also mention that all salary cap numbers come from Spotrac and all injury information is from Pro Football Reference.

Results

Here are the totals for each team in the NFC North in the four injury areas.  For those who are curious, the raw data can be seen here.  I had bold and italicized fonts to indicate starters and Pro Bowl players, but it didn’t copy and paste from Excel to Google Docs, and I didn’t care enough to go back and add it in manually.  Sorry.

Discussion

In three of the four areas, the Green Bay Packers comes out as the NFC North team that suffered from injuries the most in 2013.  This is probably not very surprising to anybody who followed the division closely this year-their injury woes were well documented-and makes their division title all the more impressive.

What is interesting to me is that, despite having almost twice as many games lost due to injury as any other NFC North team, the Packers were not that far off from some of the others in starts, Pro Bowl Starts, and money lost.  This suggests that a good number of their injuries were to backups and special teams players, although they still certainly lost their fair share of top-shelf talent as well.