2009 NFL Season - Passer Ratings

We now have data for the entire 2009 season, and I can calculate the best and worst performers for the season, using my standard measure, CMI - or more appropriately, Standard Deviations from mean CMI.  CMI is easily calculated, as it is simply [pass completion percentage] - 3 * [interception percentage].  I can calculate that at any point during the season.  In order to calculate the standard deviations from the mean CMI, I like to wait until the season is over (actually, even this can be calculated at any point during the season, but it's a lot simpler for me to just do it at the end of the season - perhaps next year, I can do this after every week during the regular NFL season).   For those of you familiar with statistics, the measure of standard deviation from the mean is also called a z-score (or z-value).  And, furthermore, z-score can be very easily converted to a percentile rank (assuming that the population is normally distributed.  In a later post, I will show that z scores for CMTI or NFL passer rating over the years is distributed normally).  The beautiful thing about a percentile rank is that it is always a number between 0 and 100.  What's not to like about that!

A quick couple of notes here regarding CMI, and many of the calculations that I will be using from here on out. While I will go through the exercise of creating arduous, complex and sometimes arbitrary (and even unnecessary) calculations, I will strive for simplicity whenever possible when I present my ideas, as I believe they are more likely to be accepted.   The use of percentile ranks is an example of this.

Last year, when I first developed CMI, and especially as I looked back in time, I had to figure out how many players to use each year to determine the number of qualifiers.  I went through some elaborate mechanisms to calculate the number of passes attempted during the season (per team per game), and some qualifying standard.  As you are aware, the NFL uses 14 passes per game as the standard.  And yes, while it is simple to use, I am not a big fan of that standard since the average # of passes attempted per game has changed (increased) over time, as you can see from the table below.

The standard today should be closer to 16.

Last year, I arbitrarily assigned a factor close to 50% (with adjustments for the earlier years) to the total # of passes attempted by each team per game to determine the # of qualifiers.  I realized this year, that if I simply used the # of teams in the league as the cutoff for determining the # of qualifiers, I get fairly close to my original method.  And because it is simple, easy to explain, does a better job (in my opinion, anyway) than the current NFL standard, I will use that as the cutoff.  The table below shows the # of qualifiers by season using the NFL standard, my original standard, and my current standard.

As you can see, the # of qualifiers, regardless of which method you select is fairly close in each year, with the exceptions being the earliest years, where the NFL method simply excludes too many passers (in my opinion anyway).  Also note that the the AAFC is excluded by the NFL altogether, while the AFL and NFL have been combined in the years 1960-1969 by the NFL.  This doesn't make sense to me, since each league played a different # of games (and had a different # of teams).  Regardless, if you combine the AFL and NFL results from my method, you get close to the #s used by the NFL.  While I think that my method works, I also recognize that this standard may not be the most appropriate for future NFL seasons.

OK, back to the passer ratings.

Because I will discuss other passer rating systems/calculations that are related to CMI in later posts, I will take this moment to re-classify CMI as CMTI (acronym stands for Completions Minus Three times Interceptions).  The definition itself hasn't changed - just the acronym.

The table below shows each of the qualifying quarterbacks with their 2009 season's statistics, their NFL passer rating, the percentile rank of their 2009 NFL passer rating (in other words, the converted z-scores), their 2009 rank in terms of NFL passer rating, their 2008 NFL passer rating, the percentile rank of their 2008 NFL passer rating, their 2008 NFL passer rating rank, their 2009 CMTI, 2009 CMTI percentile rank, their 2008 CMTI and 2008 CMTI percentile rank, and their 2008 CMTI ranking, and finally, their average 2-year CMTI percentile rank (again a # between 0 and 100), together with that ranking.

I don't think there's any question as to who the elite quarterbacks are.  Also notice the struggles of first-year quarterbacks in each year.

Was Steve McNair A Good Passer?

Earlier this month, Steve McNair was shot and killed. It was a story that caught everyone by surprise, and there was much said about his contributions to the game, and how he played the game. I thought it might be worthwhile to digress briefly from my current topic - the economics of the NFL Draft to take a look back at McNair's career.

Steve McNair was drafted in 1995 out of little-known Alcorn State. The 3rd overall pick in the draft, he was the 1st quarterback taken that year. The then Houston Oilers (now Tennessee Titans) drafted him ahead of current Titans quarterback Kerry Collins.

He started out his career backing up Chris Chandler in both 1995 and 1996 while the team was still the Houston Oilers. The first year in Tennessee, he took over the starting job. He had a sub-par first year (as most quarterbacks tend to do), and then went on to have a fine career. He is of course, most notably remembered for coming one yard short of leading the Titans to a victory against the St Louis Rams in Superbowl XXXIV. The table and chart below illustrate his career in terms of the standard deviations from the mean CMI.

As you can see, from 1998 until his retirement after the 2007 season, he finished each year at above the mean CMI, with the exceptions of the 2004 and 2007 seasons which were cut short due to injury. His best year was 2003, where he finished 1.40 standard deviations above the mean CMI. His statistics that year: 62.5% completion rate, and a 1.75% interception rate. For his performance on the field that year, he was named Co-NFL MVP along with Peyton Manning. He was traded to the Baltimore Ravens following the 2005 season.

All told, Steve McNair had 9 qualifying years in his 13-year career. Of the 51 quarterbacks since 1940 to throw enough passes to qualify in 9 or more seasons, he ranks 17th. His career average standard deviation from the mean CMI during his 9 years was 0.46, putting him in the company of quarterbacks such as Norm Van Brocklin, John Brodie and Sid Luckman. The chart below illustrates the 51 quarterbacks, and Steve McNair's standing among them.

Better Than Jay Cutler

A lot of noise this past month about Jay Cutler. First, the Denver Broncos' new head coach, former New England Patriots offensive coordinator Josh McDaniels, apparently tried to work a trade to get Matt Cassel from the New England Patriots. This apparently didn't it well with the Pro-Bowl quarterback. After a lot of posturing from both sides, Cutler was eventually traded to the Chicago Bears for Kyle Orton and draft picks. This post isn't about who was right or wrong in the fracas, or which team got the better end of the deal in the trade. This post is about answering the following two questions:

1) How good is Jay Cutler?

2) Are there quarterbacks with similar experience that are better than Jay Cutler, and, if so, who are they?

The table below ranks each of the 30 quarterbacks that threw enough passes last year to qualify to be ranked. The ranking is based on CMI, and not the NFL's quarterback rating system. In numerous posts prior to this, I have discussed why CMI is a better measure of a quarterback's passing performance than the NFL passer rating system.

Just looking at last year, the year that Jay Cutler got named to his first Pro-Bowl, he was, by this measure, a below-average quarterback. His CMI of 0.536 was (0.14) standard deviations below the mean. It should be noted that even though he was below average relative to all quarterbacks in 2008, it wasn't unexpected. Previously, I discussed the notion of performance improving with experience. So, if you were to look only at quarterbacks and their second year performance, their average is (0.21) standard deviations relative to the mean. Relative to that measure, he actually did better than the typical second year quarterback.

Let's take a closer look at the table above. The last 2 columns indicate the # of years the quarterback has played since he first qualified, and the total # of years he has qualified. So, Cutler has played 2 seasons where he threw enough passes to qualify, and this is second consecutive year of being qualified. There are six other quarterbacks in this table who have similar experience.

They are (rank in parenthesis):

Jason Campbell - WAS (5)

Matt Schaub - HOU (7)

Trent Edwards - BUF (8)

David Garrard - JAX (12)

Jay Cutler - DEN (16)

Derek Anderson - CLE (30)

Of the six quarterbacks who were in their second year (Garrard has the most experience of all the quarterbacks, even though he has only qualified in two years), Cutler only outperformed Derek Anderson of Cleveland in 2008. Ok, so 1 year does not make a quarterback. Let's take a look at these six quarterbacks and see how they've done in each of their first two (qualifying) years.

According to this table, both Garrard and Schaub have outperformed Cutler in each of 2007 and 2008. And, arguably, over the two-year period, so did Campbell. The only quarterback in this class that has clearly underperformed the rest of the group is Derek Anderson. He will not last long in the NFL.

Admittedly, it's difficult to judge a quarterback after his first two years. But, so far at least, there appear to be several quarterbacks that have outperformed Cutler. It will be interesting to watch this group over the next several years, and especially Cutler, as he will be with a new team.

Does Experience Improve Performance?

In my earlier post, "First Year Performance - An Evaluation Method", I discussed how, over the history of the NFL, from 1940-2008, a quarterback's passing performance, as measured using CMI, and more specifically, the standard deviation from the mean of CMI, changes over time (in that post, see in particular the third graphical illustration labeled "CMI - SDs from Mean - By Qualifying Year").  That illustration pointed out that it takes about 5 years for a quarterback to become "average" (or, better than average).  That's obviously only true for quarterbacks who qualify in at least that many years.  Meaning that since the graphical illustration includes all quarterbacks (who have thrown enough passes to qualify in at least 1 year), that the earlier years could be biased by quarterbacks who only qualify in  those earlier years, and not the later ones.  

This is the issue pointed out by a commenter regarding that post.  He (she) was suggesting that I have a biased sample, in that the later years are only populated by quarterbacks who throw for that many years, and hence, performance should be expected to improve, as the NFL weeds out the under-performers of the earlier years.

Here's the comment:

"This effect could be due to sampling bias.  It may be that there are a large pool of first year QBs.  Some are good and some are bad.  The good ones make it to year four, and the bad ones are cut, released, or benched before they can play four years...."

He (she) then went on to ask the following question:

"...if you restrict the analysis to only QBs that have played >= 4 years, do you get the same result?"

Before I answer the question, let's address the comment.  

First, the commenter does make a very valid (and what would seem to be an obvious) point, in that those QBs that make it to year 5 and beyond, must necessarily be the better ones, as the under-performers drop-off.  This point has several implications though.  The first is that the NFL does not look at quarterbacks (or, more accurately, their passing performance) the way I do.  So we can't simply assume that the point is in fact that obvious.  Second, perhaps the way I look at quarterbacks passing performance, CMI, is in fact, a decent (good?) measure of a their true passing ability, and, the graph validates that fact (this would be rather presumptuous of course, but that is what I am trying to prove after all - that I have, in fact, developed a method that appropriately evaluates a QBs passing performance, and, perhaps even more importantly, that I have developed a method by which one can identify a good passer versus a poor passer early on).

Second, the commenter suggests that my sample is biased because of this fact (i.e. it is biased towards the better players in the later years).  There are two ways we can look at that.  The first is that the sample isn't biased because it uses the entire population.  In other words it is what it is (and perhaps this again validates my measurement technique).  The second point is that the sample is biased (remember, however, the context in which the graphical illustration was shown - in that it was trying to look at all quarterbacks, and how their performances changed over time), and that we can, if we choose to do so, look at it differently.  This is, in fact, what the commenter was suggesting with their question.

So let's take a look.  As a matter of fact, let's take the question a bit further and look at it in four different groupings:  

QBs qualifying in at least 1 year (the original graph) - 345 Quarterbacks

QBs qualifying in at least 3 or more years - 180 Quarterbacks

QBs qualifying in at least 5 or more years - 121 Quarterbacks

QBs qualifying in at least 7 or more years - 84 Quarterbacks

The graphical illustration is followed by a tabular display of the same data.

There's no question about it.  Performance improves as a quarterback gains experience.  All groupings follow the same basic pattern:  Sub-par performance in year 1, followed by several years of gradually improving performance.  When the improvement takes place, and by how much, does vary by group.  For example, after three years, teams still haven't been able to markedly separate the good quarterbacks from the bad ones.  By the fifth year, it's now quite apparent who has "cut it", and who hasn't.  For all quarterbacks qualifying in at least 7 or more years, they appear to show their skill, or differentiate themselves, as early as year two.  So, to prove the obvious point that the commenter in the previous post making, those that don't turn in positive performances early do tend to get weeded out.  The process, however, happens to take a few years.

The question this prompts however, is, why does it take so long to weed out the poor performers?  

Well, there are at least two different answers.  

The first, something I alluded to earlier, is that the NFL doesn't evaluate passers the way I do.  I am a statistical analyst, and what I have created is a an objective methodology to evaluate a player's performance.  Teams in the NFL, aren't inclined to do the type of statistical analysis that I do.  In addition, it's just simply not clear, even using my statistical methods, that you can be sure that you can identify the good and bad future quarterbacks after year 1.  By year 2, however, year 3 the latest, my method does show who the keepers should be.

The second is, that teams pay a lot of supposedly smart people (scouts, GMs, etc) a lot of money to evaluate, and draft good talent.  Subsequently, these teams draft these "talented" players early in the draft, and pay them lofty sums of money, a lot of which is guaranteed.  Now what do you do?  You've got a poor-performing team (generally, a team's draft order is determined by their won-loss record, with the teams with poorer records drafting earlier, and vice-versa) that just drafted the next "Peyton Manning", and have paid them a lot of money, and they have a lousy first year.  You're not likely to blame the young quarterback for that year's performance.  The team still has a lot of weaknesses elsewhere, so you pick early again the next year (perhaps shoring up the defense).  Second year passing performance is better than the first, but still not better than average.  You even ignore the statistical evidence (he can't be that bad).  You're still paying him lots of money, you've seen improvement, team has won perhaps a couple of more games, and this gives you hope that, the third year is THE YEAR.  Then, much to your dismay, the quarterback that you paid millions of dollars for, doesn't pan out as you have another miserable year (the teams is "close" to 0.500).  You get impatient,  fire the head coach, try an aging veteran as your quarterback, he has a decent year, a quarterback controversy brews, ya da ya da ya da....and, you continue to ignore the statistical evidence....

Just off the top of my head, I can think of several recent obvious examples - Alex Smith of the Forty Niners (and, proving the corollary, the approach taken by the Green Bay Packers with Aaron Rodgers), and JaMarcus Russell of the Oakland Raiders.

Here are three quarterbacks that the NFL, teams, and fans, have fallen in love with, but, statistically have yet to prove themselves.

Eli Manning (I can hear the argument - but they won the Superbowl)

Tony Romo

Michael Vick

So there you have it.  My method is the Moneyball approach.  What actually happens in the NFL is quite different.  NFL teams could save themselves a lot of money (and perhaps even win a few more games) if they were to adopt a statistical approach to their business (I think a lot of NFL teams actually believe they take a statistical approach, but I don't think that most actually go through rigorous analyses the way I do).  

My next post will be my preseason rankings for 2009.

The Best and Worst of 2008

This is a simple post.  Really simple.  The list should pretty much speak for itself.  The best and worst of 2008.  I use the same criteria I've been using the past few posts.  CMI, and, more specifically, standard deviation of a player's CMI relative to the mean.  30 players attempted enough passes in 2008 to make the list.  

The Best 3:

3.  Jeff Garcia, Tampa Bay Buccaneers - Why no team has picked him up is a complete mystery to me - the man can still play, even though his durability is certainly a question.  Completed nearly 65% of his passes, and less than 1.6% of his passes were intercepted.

2.  Peyton Manning, Indianapolis Colts - Do we even need to say anything? Coming off off-season knee surgery, Mr. Consistency now holds the highest current active streak of games started consecutively - 176 games. He completed almost 67% of his passes.

1.  Chad Pennington, Miami Dolphins - Let go by the Jets so that they could welcome Brett Favre (that worked out well for the Jets, didn't it?) and subsequently picked up by the Dolphins. Had a terrific season, completing more than 67% of his passes, and less than 1.5% of his passes were intercepted.

In previous posts on my blog, I have spent time discussing each of the above 3 players.

The Worst 3:

28.  Tyler Thigpen, Kansas City Chiefs - Won't show up at the bottom of the list in 2009.  Why?  Matt Cassel (#10 in 2008).  The Chiefs made a deal with the New England Patriots to get Cassel (and Mike Vrabel) for a 2nd round pick in the upcoming draft.  In 2008, Thigpen, replacing Damon Huard, completed fewer than 55% of his passes.

29.  Gus Frerotte, Minnesota Vikings - Replaced an ineffective Tarvaris Jackson in the 3rd game of the season, started 11 games, and then was himself replaced by Jackson against the Lions.  Completed less than 60% of his passes, and at almost 5.0%, was one of only three quarterbacks whose interception percentage exceeded 3.0% - the other two being Ben Roethlisberger of the Steelers (3.2%), and Brett Favre of the Jets (4.2%).

30.  Derek Anderson, Cleveland Browns - Barely completed 50% of his passes, then got hurt.  Was replaced by Brady Quinn.  Is it Quinn's time in 2009?

Here's the entire list.

My next post - a pre-season ranking for 2009

First Year Quarterback Performance - An Evaluation Method

This past weekend, the New England Patriots traded Matt Cassel to the Kansas City Chiefs.  In fact, they traded linebacker Mike Vrabel and Cassel for a 2nd round pick (pick #34) in the upcoming April draft (see here for the details).  Depending on what your news source is, this was labeled as either a good deal for Kansas City, or a bad deal for New England.  The experts discussing this issue don't seem to support their arguments by any objective measures - they just opine.  I am not going to jump into the debate here.  I will offer this however - we will probably not know who will end up on the better end of this deal until many years from now, and even then, we may not know.  

What about the objective evidence?

Matt Cassel is not the only quarterback in 2008 that had a good year as a first-year quarterback.  There was Aaron Rodgers of the Packers, Shaun Hill of the 49'ers, and Matt Ryan of the Falcons.  There were four other quarterbacks who threw enough passes this year to make the list of first-year quarterbacks - Ryan Fitzpatrick of the Bengals, Joe Flacco of the Ravens, JaMarcus Russell of the Raiders and Tyler Thigpen of the Chiefs.  

Notice here that I didn't use the term rookie quarterback, but instead used the term first year.  The way I look at a quarterback, is that I only consider a quarterback who has thrown "enough" passes to qualify in a given year.  The # of passes has varied by year (as opposed to the fixed standard used by NFL.com).  For the 69-year period from 1940-2008, my database contains 1,451 passing seasons, 336 of which were by a quarterback qualifying for the first time.

How did the aforementioned 8 quarterbacks do?  

I use a statistical measure I have previously developed and discussed, called CMI (Completions Minus Interceptions, calculated as Completions/Attempts - 3*Interceptions/Attempts) instead of the NFL Passer Rating system (using the NFL passer rating system gets you essentially the same answers), and then use the standard deviation from the mean as the measuring stick (for the pool of qualifying passers, I calculate the the mean and standard deviations for each year, and relate a particular performance in that year to the mean using that year's standard deviation).  Using the mean and standard deviation this way not only allows me to compare these 8 quarterbacks relative to each other, but also relative to all quarterbacks this year, or any other year.

In a post not too long ago, I showed how, over the past 69 years from 1940-2008, when the standard deviation is used as the measuring stick, the accumulated data form a near-perfect theoretical standard normal distribution.  And I also showed how, this is true regardless of whether one used the NFL passer rating system or CMI as the statistical base.

I can now show you how these first year quarterbacks did compare to the rest of the QBs in 2008, using this measure.  But this picture may not tell us much, if anything.  Here's the graphical illustration:

Perhaps the only thing that may be apparent from this is that first year quarterbacks don't do nearly as well as quarterbacks with more experience.  Even drawing that conclusion from this is a little iffy.  However, it is clear (at least by this measure) that Cassel had the best year of the 8 first year QBs.  Rodgers was a close second.  JaMarcus Russell and Tyler Thigpen had disastrous first years.  In an earlier post regarding Jeff Garcia, I had suggested that Kansas City might be a good place for Garcia.  Scott Pioli, the new Chiefs' GM apparently was thinking the same thing - upgrade at quarterback, and he did - with Cassel.

Going back to the standard normal curve, let's look at just the first year performances.  Recall that, when all 1,451 seasons are aggregated in a histogram, it looks very much like a standard normal curve.

This doesn't quite look "normal", does it?  The first year performances appear skewed to the left, or, compared to all quarterback performances, appear to under-perform.  Since the total database is normally distributed, then performances in years 2 and beyond must obviously be skewed to the right.  This prompts the question: does experience improve performance, and, in particular, how and when?

One way to look at this is to take the entire database, and look at the average standard deviation from the mean for each additional year a player qualified.  Here's what that graph looks like.

Wow!  I didn't realize that it takes about 5 qualifying years to turn into an average quarterback.  And that's just for those playing that long!  Even though this graph goes out to 18 years, there is hardly any data beyond the 15th year (there are only 8 quarterbacks who have had qualifying seasons 16 different years).  According to this illustration, basically, first year quarterbacks, as a group, struggle mightily.  They then gradually improve each year until about year nine.  Quarterbacks, on average, must still endure sub-par years in years 2-4, and for those that survive, their reward is about four more years of improving performance, assuming they stay healthy for that long.

Note: This analysis - the method of breaking down a quarterback's expected career in terms of passing performance as it relates to experience and how it is expected to change over time, is the first I've seen published publicly.  But I digress.

Ok, so we've taken a look at these 8 QBs relative to all quarterbacks in 2008, and we've taken a look at first year quarterbacks in general.  So the next step is to take a look at the best first year seasons.  In my database, there are 336 first year seasons in all (in other words, in the 69-year period from 1940-2008, 336 different quarterbacks threw enough passes in a season to qualify at least once).  The table below shows the 75 best.

Cassel (#48) and Rodgers (#60) are the only 2 of the 8 in 2008 that crack the top 75 all-time.  On the other end of the scale, we get JaMarcus Russell (#264) and Tyler Thigpen (#290).

When Matt Ryan (#128) got off to a solid start, and the Falcons surprised many by getting into the playoffs, there were many debates as to whether his season was one of the best ever by a first year player.  Not according to this measure.  Often, during those discussions, Kurt Warner's first year was brought up.  In looking at the table above, well, he did have an outstanding first year in 1999.  It ranks #6 all-time in terms of first year seasons.  The best ever - Roger Staubach's 1971 season (Staubach was a rookie in 1966, and played in both 1969 and 1970.  However, he didn't attempt enough passes in either year to qualify).  

Notable quarterbacks high on this list: Joe Montana in 1980 (#4), Tom Brady in 2001 (#14) - (see my post earlier comparing Brady's season to Cassel's here), Brett Favre in 1992 (#15), Dan Marino in 1983 (#21), and Johnny Unitas in 1956 (#22).  

Notable absentees:  Steve Young in 1986 (#154), Peyton Manning in 1998 (#208), Joe Namath in 1970 (#202)*, and Troy Aikman in 1989 (#311).  The all-time worst first year performance - Terry Bradshaw in 1970 (#337)*.

* Keep in mind that 1970 was the first year of the NFL following the merger, and 15 quarterbacks showed up in the database as having that year as their first year, although Bradshaw's 1970 season was his actual rookie season.

Are we done?  Hardly.  So after I went through this list, and still trying to objectively value Matt Cassel, I was interested in answering the following question(s):  what does the first-year tell us about a quarterback's future potential?  Do quarterbacks who have good first years, have good careers?  What about quarterbacks who have sub-par first years?  In other words, is there a correlation between year 1 performance and subsequent years?  When in doubt, it's always a good idea to take a look at the data.

Whoa!  The correlation between year 1 performance, and career performance, as measured by CMI standard deviations relative to the mean, is 0.75.  What that really means is that 57% of the variation in a quarterback's career performance can be explained by his year 1 performance.  I find that incredible.  So I looked a little deeper.  It turns out that 112 of the 336 quarterbacks only have 1 qualifying year.  And, for that group, the correlation coefficient is, well, 100%!  If I only looked at those quarterbacks whose career included at least 2 different years in which they threw enough passes to qualify, then the correlation coefficient drops to 64%.  Still quite remarkable.  

The table below breaks down the 336 first year seasons in terms of CMI standard deviations to see if we can glean any additional insight into whether a good first year translates into a good career and vice versa.


Well, the evidence is pretty clear.  Taken as two groups, players that have better than average (remember, the mean and standard deviation is relative to all quarterbacks, not just first year quarterbacks) first years tend to have longer careers and more productive careers than those that have sub-par first years.  And, breaking it down even further (in other words, just looking at the group whose first year was better than average, or the group whose first year was worse than average), you can clearly see that even within those sub-groups, the better the first year, the longer the career (although this correlation isn't nearly as strong), and the more productive the career. 

I haven't spent too much time on my blog discussing individual careers, except in the posts discussing Brett Favre and Jeff Garcia.  If I do this en masse, it would be such a powerful post - I'll basically be giving you my list of greatest passers to ever play the game, that I need to put a lot more thought into it than I have to-date.  In any case, some of the obvious names will show up on that list.  However, you'll find some exceptions as well (and I'm sure many of you will take exceptions to the list).  The point I really want to make here is that, when combining the table above, and the discussion following the list of the top 75 first years, it is quite remarkable how Troy Aikman "escaped" the trend, and turned into a great quarterback (or, more accurately, a great passer) - he truly turned out to be an exception (as for Young and Manning, even though they didn't rank well on the first year list, their first years weren't "that bad" compared to other first year seasons - as a matter of fact, Young's was "above average" compared to a typical first year).  Notice how I don't mention Bradshaw and Namath - it is because, statistically, their careers were sub-par.  When I publish my list of all-time greatest (and worst) passers, we'll get into it in more detail.

So, in trying to look at Matt Cassel's first year performance objectively, we've looked at how quarterbacks perform as their careers progress, how quarterbacks perform in their first year, who had great first years, where Cassel's season ranks on that list, and, how a first year translates into (or, is predictive of) a career.  Now perhaps, we can view Matt Cassel's 2008 year in an objective manner, and, if so inclined, you can at least evaluate the trade armed with some data.

Naturally, while I was putting this post together a question popped into my mind, and that is:  is a quarterback's second year a good indicator of their career?  What about looking at their first and second years?  Check back in a week or two to find out.

A Brief History of the NFL Passer Rating System

Philip Rivers of the San Diego Chargers had a phenomenal season in 2008.  Or did he?  According to the NFL's passer rating system, Rivers' season, where he completed 312 passes out of 478 attempted, threw for 4,009 yards, and 34 touchdowns against 11 interceptions resulted in a passer rating of 105.5.  That's great, right?  Before we answer that question, we'll need to answer a few more questions.

How do the statistics 312 for 478, with 4,009 yards, 34 touchdowns and 11 interceptions translate to a rating of 105.5?

What does having a rating of 105.5 mean?

Where does Rivers' season rank all-time?

How has the average NFL passer rating changed over time, and how does that affect how we look at Rivers' season?

The NFL began keeping statistics in 1932.  The NFL has used various methods to determine the "best" passer in the years since.  According to the Pro Football Hall of Fame, the following is a chronology and description of the different methods used:

1932-1937: Total yards passing

1938-1940: Percentage of completions

1941-1948: Inverse ranking system of the following categories: completions, percentage of completions, total yards, total TD passes, number of interceptions, and percentage of interceptions

1949: The same formula used from 1941-1948 except the number of interceptions were dropped from the equation

1950-1959: Average yards gained per pass with a minimum of 100 attempts needed to qualify

1960-1961: Inverse ranking system based on six categories: total completions, total yards, total TD passes, percentage of completions, percentage of interceptions, average gain per attempt with the principle established of at least 10 attempts per game to qualify

1962-1971: Inverse ranking system based on four categories: percentage of completions, total touchdown passes, percentage of interceptions, average gain per attempt

1972: Same system used from 1962-1971 except that the percentage of touchdown passes was substituted for total touchdown passes

1973 to present:  See below.

Current NFL Passer Rating System:

The passer rating system used by the NFL has been in place since 1973.  In 1971, after the merger, then-commissioner Pete Rozelle wanted to implement a standardized set of statistics, including a standard measure of passing performance.  As the description on the Hall of Fame site suggests, this is a measure of a quarterback's passing effectiveness, not a measure of how good a quarterback is.  Rozelle called upon Don Smith, then an executive with the Hall of Fame, to work with the league's official statistician, the Elias Sports Bureau, to develop a new standard.  

One of the problems with the standard that existed at the time, was that you didn't know where you stood until all the teams' quarterbacks had finished playing, as it was a relative ranking system.  In addition, there wasn't a convenient way to compare a performance in a given year to that of another.

Don liked the use of the combination of statistics - in other words, the completion percentage, the yardage per attempt, the touchdown percentage and interception percentage.  He had to figure out how to use all four in some manner that would make sense.

Working with the Elias Sports Bureau, he studied passing statistics for each of the four categories from the decade before - the sixties.  After much study and thought, he devised a system whereby, for each of the four statistical measures, he would convert that particular measure to a "score" between 0 and 2.  A score of 0 would indicate poor performance, a score of 1.00 would indicate "average" performance, and a score of 2.00 would indicate "superior" performance.  With truly exceptional performance, it was possible to exceed a score of 2.00.  He arbitrarily chose the maximum score to be 2.375.  

He decided that an "average" performance across all four categories, that is, a score of 1.00 for each of the four measures, should be a rating of 66.7.  Under this new rating system, it would be possible for a rating to exceed 100.0, but, he theorized that those instances would be rare.

(Note:  I took a lot of this history from an article written by Don Steinberg, published in Slate magazine in 2001 - see here for the full article)

In summary then, this is how we end up with the current NFL passer rating system:  we take four components of passing, convert each component, using league averages from the 1960's, to a score with a minimum of 0.000 and a maximum of 2.375, combine these scores by adding them, and convert to a rating system that has 66.7 as the "average".

Here's the math that does this:

Q = [ ( J + K + L + M ) * 100 ] / 6

where,

Q = Passer Rating

J = max [ min ( C, 2.375 ), 0 ]

K = max [ min ( Y, 2.375 ), 0 ]

L = max [ min ( T, 2.375 ), 0 ]

M = max [ min ( I, 2.375 ), 0 ]

and where,

C = [ ( Completions / Attempts ) * 100 - k1 ] / 20

Y = [ ( Yards / Attempts ) - k2 ] / 4

T = [ ( Touchdowns / Attempts ) * k3 ] * 20

I = 2.375 - [ ( Interceptions / Attempts ) * k4 ] * 25

and where,

k1 = 30

k2 = 3

k3 = 1

k4 = 1

In the first formula, you can easily see where if J = K = L = M = 1.000, the passer rating formula would yield Q = 66.7.  In order to get J = K = L = M = 1.000, certain "transformations" were needed to each of the passing statistics to convert the averages to a score of 1.000.  The transformations for each are shown as C, Y, T, and I, and, more specifically, k1, k2, k3 and k4.  The figures for k1-k4 were derived using league statistics from the 1960's, and to make it somewhat easier, rounded.  If you looked at data from 1960-1969, you get the following actual values for k1-k4:

k1 = 31.70

k2 = 3.24

k3 = 0.96

k4 = 0.99

The table below shows, for each NFL season from 1940-2008, how the averages, or, more precisely, the "scores" for those averages have changed from year to year (for a graphical illustration see my previous post on the subject here).  For example, you can see that the average score for "J", in 2008 was 1.550, reflecting the fact that the "C" component, or, completions per attempt, for the average NFL quarterback was 61.0%.  Compare this to the average score for "J" in 1968 of 1.079, reflecting the "C" component, or completions per attempt of that time of 51.6%.  This is what happens when the transformations do not change over time, even when the actual game itself has undergone many transformations.  If one wanted to keep everything in balance from year to year in the passer rating formula, in other words, to keep J = K = L = M = 1.000 for every year, then one would have to change the values of k1 - k4 every year.  I have done that in the table below.

You can use these different k values every year to "adjust" the passer rating formula, so that you can make meaningful comparisons from year to year.  If you didn't do that, and simply compared a quarterback rating from one year to the next, you wouldn't get an appropriate comparison, for the simple reason that the four components would be "out of balance".  

While it was never Don Smith's intention to have a relative measure of performance - he wanted performance as measured relative to a fixed standard, that "fixed" standard has changed, and will continue to change over time.  One way to minimize the effect of these changes is to look at a given performance in a given year to that season's average, using the standard deviation as a measuring stick.  The other way, is to simply "adjust" the standard to reflect the averages for that year.  In a previous post, I discussed the former method.  In this, I am obviously discussing the latter.

This discussion is only to put Rivers' 2008 season in perspective.  It is not intended as passing judgment on the NFL passer rating system.  I have, in previous posts (see here and here) discussed why I do not like the system.  In a post in the future, I'll elaborate further on why I think the NFL's passer rating system should be revised.

The table below shows the 75 greatest seasons in the NFL, both in terms of the current NFL passer rating system, and using an "adjusted" passer rating system, going through the transformations as I have described above.  You can see that, using the current system, that Rivers' 2008 ranks as 13th best all-time.  Using an "adjusted" passer rating system, however, results in a ranking of 60th best all-time.  If we used the previously mentioned standard deviations from mean measurement, it would rank as the 16th best all-time.

We still have some unfinished business:

How does Rivers' stats translate to a rating of 105.5?

He completed 312 of 478 passes, or, a completion percentage of 65.3% - using k1 = 30, and Comp/Att = 0.653 in the formulas above, yields a J value of 1.764

He threw for 4,009 yards, or, yards per attempt of 8.4 - using k2 = 2, and Yards/Att of 8.4, we get a value for K of 1.347

He threw 34 TDs, or, TD/Att of 7.1% - using k3 = 1, and TD/Att = 0.071, we get a value for L of 1.423

He threw 11 INTs, or, INT/Att of 2.3% - using k4 = 1, and INT/Att - 0.023, we get a value for M of 1.800

Combining all, we get

Q = ( J + K + L + M ) * 100 / 6, or

Q = ( 1.764 + 1.347 + 1.423 + 1.800 ) * 100 / 6 = 105.5

There is no doubt that, whether we use the current NFL passer rating system, an "adjusted" passer rating system with different transformations for different years, or, the current system, but adjusted by looking at standard deviations from the mean, that Rivers' 2008 season was quite remarkable.  

Whether the passer rating system is an accurate reflection of a passer's ability is a completely different question altogether.  We shall, over time, address this question.

Anybody Looking for a Good QB?

Available:  Experienced quarterback with an accurate arm with ability to make immediate contributions to team; Ideally, would like to start, but not a requirement; may be perfect as back-up; durability maybe an issue.

I am referring of course to Jeff Garcia, released today by the Tampa Bay Buccaneers.  I am personally a big fan of Garcia, because I believe he is underrated, and his achievements on the field have gone relatively unnoticed.

Let's take a look.

He began his NFL career in San Francisco in 1999, replacing not one, but two back-to-back Hall of Famers, and arguably the two greatest passers of all-time, Joe Montana and Steve Young.  There was no way Jeff could live up to those lofty expectations.  However, he did perform very well, as the table and chart below shows.  While he may not have performed at Joe Montana and Steve Young levels, his years in San Francisco were very productive.  After a sub-par year in 2003, he bounced around for three years, first as a starter in Cleveland (2004), then as a back-up in Detroit (2005) and Philly (2006).  He finished the 2006 season as the starter in Philadelphia for the last 6 games after Donovan McNabb got injured.  He showed that he could still play, and Tampa Bay, in need of a quarterback following an injury to Chris Simms, picked him up.  He did well above average each of 2007 and 2008, as you can see from the table and charts (he doesn't show up in the charts in the years 2004-2006 since he didn't attempt enough passes to qualify).  

Now, Tampa Bay, deciding to turn to the youth movement, have invested in Luke McCown, and, have deemed Garcia expendable.  

Garcia has been a very accurate as a passer throughout his career.  In a previous post, I discussed interceptions at length.  His 2007 season ranks 18th all-time (see Exhibit 3 in this post) in interceptions per attempt, in terms of standard deviations from the mean (his 2008 season ranks 118th, out of the 1,451 seasons in the database since 1940).  As a career passer, he ranks 12th all-time (see Exhibit 6 in this post).  By not throwing interceptions, he will help your team win.

I believe that Garcia has a couple of good years still left in him, if not as a starter, as a back-up.  His durability has been an issue the past two seasons, and hence, might be a liability as the starter.  

So who might be worthwhile candidates?

The following charts show, for each of 2007 and 2008, how a team's passing game stacked up in terms of standard deviations from the mean.  It's no coincidence that teams that were above average won more games than they lost, and teams that were below average lost more games than they won.  The charts show how the teams did both in terms of NFL passer rating and CMI.  Note that Garcia averaged 0.53 standard deviations above average in terms of NFL passer rating for the past two seasons, and averaged 1.23 standard deviations above average in terms of CMI.

To see which teams should be looking to get Garcia, let's start at the bottom, and move our way up.

Cleveland Browns - They have two young quarterbacks, Derek Anderson and Brady Quinn, both coming off season-ending injuries, that will compete for the starting job.  Not a candidate.  Look for another miserable year in Cleveland.

St Louis Rams - Marc Bulger is the starter, and for now at least, another soon-to-be 39 year-old - Trent Green, is the back-up.  Not a candidate.  By the way, what's happened to Bulger?  Will 2009 be more like his first few years, or his last two?  I suspect the latter.  Another long year in St Louis.

Oakland Raiders - Paying a lot of money for JaMarcus Russell.  They've also got Andrew Walter, Marques Tuiasosopo, and they just picked up Bruce Gradkowski off waivers.  I haven't a clue what the Raiders are doing, and I don't think the Raiders do either.  Not a candidate.  Perhaps we'll start paying attention when Al Davis passes away.

San Francisco Forty Niners - They're not sure who their starting quarterback is.  Shaun Hill?  J.T. O'Sullivan?  Alex Smith?  The niners maybe a candidate.  Garcia played here, and is originally from close-by Gilroy.

Detroit Lions - Daunte Culpepper is the starter.  Or is it Dan Orlovsky?  Didn't seem to matter in 2008, as they went 0-16.  If I was GM, I'd replace Culpepper with Garcia, and draft a quarterback.  But that's just me.  Garcia may not want to go here, but that's a different matter altogeher.

Chicago Bears - Kyle Orton is the starter, and Rex Grossman is the back-up.  Neither of whom are very good.  I would think that Garcia would be an excellent choice to be a back-up here.

Kansas City Chiefs - Tyler Thigpen is the starter.  Previous starter Damon Huard is the back-up.  Garcia could be a potential back-up here.

Cincinnati Bengals - Ryan Fitzpatrick finished the year as the starter, having replaced the injured Carson Palmer.  Not a candidate.

Of the remaining teams, perhaps the Minnesota Vikings might be interested.  Gus Frerotte is simply not a good option.  Maybe they'll lure Brett Favre out of retirement!  The NY Jets might be an option for Garcia as well.  Most likely, Kellen Clemens will be the starter, but Garcia could be a viable back-up here.  

So these are teams that should be interested in Garcia.  We'll wait and see where he actually ends up.  

Brett Favre - Best Ever?

Brett Favre retired earlier this week.

He played in the NFL for 18 years. He set numerous NFL records during the course of his career. The most impressive has to be the fact that, as a quarterback, he started a record 269 consecutive regular season games. Peyton Manning is second on the list, his streak currently standing at 176 games. Third on the list is Ron Jaworski, his streak having ended at 116 games. Tom Brady is next on the list, but his streak ended in the first game of last season at 110 games. Peyton Manning needs another 94 games - he would have to start every single game through the 14th game of the 2014 season to break Favre's record. In addition to the four mentioned above, only two other quarterbacks in history - Joe Ferguson (107 games), and Dan Marino (95 games) have started that many games consecutively. I suspect Favre's record will never be broken.



People are fascinated with Favre. Many consider him to be among the all-time greatest to ever play the game. Some consider him the greatest ever. I do not belong to either group.


The media loved Favre. And vice versa. He never met a camera he didn't like, always seeking an opportunity to get into the limelight (of course, the media loved that). He also seemed intensely competitive, and the combination is what I believe led him to his unfortunate decision to come back for one more season in 2008.


Let's start from the beginning.


In 1991, the Atlanta Falcons took Favre in the second round of the draft. With Chris Miller as their starting QB, in 1992, the Falcons traded Favre to Green Bay. Favre started the season as the back-up to the 'Magic Man', Don Majkowski. In the third game of the season, against the Cincinnati Bengals, he replaced the injured Majkowski in the first quarter. With 13 seconds left, he threw a 35-yard touchdown that helped the Packers come-from-behind to win 24-23. He started the next game against the Steelers, a game the Packers won. The rest, as they say, is history, as he started every game for the Packers until his trade to the Jets following the 2007 season (for a detailed history of, or, more aptly, a tribute to Favre, see here).


The table below shows how Favre did each year.



Before we go on, some explanations.


In order to be able to truly compare Brett Favre to other quarterbacks so that we can properly gauge his place in history, we can't simply look at the NFL's passer rating system. First, we know that the average NFL passer rating in the NFL has been increasing over time. So, by simply using the NFL's passer rating system, the more recent quarterbacks would appear to have done better than quarterbacks from earlier years (see here and here for evidence). Second, we have to agree that the NFL's passer rating system is an accurate, if not adequate measure of a quarterback's performance. I have previously introduced a metric, CMI, which I believe is a better, if not more understandable measure of performance. CMI, however, also has the same bias as the passer rating system. One way to adjust for, and remove the bias favoring more recent quarterbacks is to look at each year's performance for each quarterback, and relate that to the average performance that year. The measure that we use is the standard deviation. I have discussed previously how using this measure tends to "normalize" performances across years. In other words, when a given year's performance by a particular quarterback is "normalized" to the average for that year, and we do that for every year, we can very easily see how that particular performance compares to other performances across years. Since CMI is very similar to the passer rating system, when using standard deviations, it shouldn't really matter whether we use CMI or the NFL passer rating system (there will be differences, and, I often include both so that you can see the differences). The two graphs below show how using either the "normalized" NFL's passer rating system or "normalized" CMI as measures compare to a standard normal curve with 1,451 observations (that's how many qualified quarterback seasons there have been over the past 69 years).



Ok, so back to the table.


Favre had a "pretty good", or, "above average" first year in 1992. Using the NFL passer rating, he finished 0.57 standard deviations above the average that year. Using a standard normal curve, that would mean between the 71st and 72nd percentiles. If we used CMI as the standard, then his performance that year, 1.24 standard deviations above the mean, would place him between the 89th and 90th percentiles.


He followed that with a sub-par year in 1993, finishing between the 30th and 31st percentiles according to the NFL passer rating system, or between the 35th and 36th percentiles using CMI. Then followed several "above average" to "very good" years (1994-1998), depending on your perspective, followed by a couple of mediocre years (1999-2000), followed by four above average years (2001-2004), followed by his two worst years (2005-2006). He finished his Green Bay tenure with an "above average" year in 2007.


He should have taken the opportunity to retire then.


His last year, his first full season not with Green Bay, was "below average". So he finished his career with 3 "below average" years out of 4. Perhaps the Packers brain trust was on to something when they decided that Aaron Rodgers was their future at the end of the 2007 season.


The two graphical illustrations below show each of Favre's seasons in terms of standard deviations from the mean. In case you haven't noticed, as much as I love statistics, I find that graphs are better way to illustrate a point than a table of statistical measures. I show the CMI graph first and the graph based on NFL passer rating next, for reasons that will become plainly apparent when you read on.





Ok, so until now, we've been looking at Brett Favre's career in a bit of a vacuum. Yes, we have compared his performances to an average, and yes, we have tried to put it into historical perspective, but I haven't given you any 'perspective'.


First, let's compare Brett Favre's career to some individual careers. The biggest problem we face in comparing Favre's career to any other individual career, is obviously the length of his career. There have been only 5 individuals who have thrown enough passes to qualify in at least 15 different seasons. Those are Fran Tarkenton (18 years), Brett Favre (17 years), Dan Marino (16 years), John Elway (16 years), and Johnny Unitas (15 years). So how does Favre's "picture" compare to these quarterbacks, all of whom are in the Hall of Fame?


Fran Tarkenton - a picture of "excellence". With a couple of exceptions, Tarkenton exceeded his peers consistently for a very long time. Quite remarkable. Without question, Favre's picture does not resemble that of Tarkenton.


Dan Marino - Marino was "above average" for many of his years, tailing off towards the end of his career. He was "very good" very early in his career. He really didn't have a "bad" year until his last, and wisely decided to hang it up after that. Although closer in resemblance, Marino's picture still looks better Favre's overall.


John Elway - Elway underperformed his peers much of his early career, exceeding the average in only two of his first ten years. He then was "above average", or even "very good" his last six years. He went out on top, having retired following the Broncos having won back-to-back Super Bowls (Super Bowl XXXII and Super Bowl XXXIII). I think it's safe to suggest that Favre's picture looks better than Elway's.


Johnny Unitas - In my opinion, Favre's picture most closely resembles that of Johnny Unitas. They both started out well, had a couple of mediocre years, then had several years where they outperformed their peers, and ended their careers with a few sub-par years.



What if we compared Favre's average performance (in other words, average each of his year's performance in terms of standard deviations), to other players? Well, over his career, in terms of NFL passer rating, Favre averaged 0.42 standard deviations above the mean (0.26 when looking at CMI). Tarkenton averaged 0.65, Marino averaged 0.63, Elway averaged 0.06, and Unitas averaged 0.51 standard deviations above the mean.


Let's expand the comparison list to players who qualified in at least 10 different seasons. 41 different quarterbacks make that list. The two graphs below illustrate where Favre ranks on those lists.



The same graph as above, except looking at it Using CMI as the measure of performance.




Looking at his career statistically, it is hard to make the argument that he belongs in the truly elite group of all-time quarterbacks - those that would be ranked in the top 3 or top 5 all time. I think it is fair to suggest that Favre has had a very good career. It was certainly a lengthy one, and, in that regard, it was exceptional. But as far as his actual performance on the field, there isn't a measure, or set of measures, that suggest that it was exceptional.


People will suggest that he holds the all-time record for yards, or touchdowns, for example. But that is merely a function of his longevity, just as much as he holds the record for interceptions thrown, all-time.


I also don't discuss measures frequently used as evidence of greatness. MVP awards, for example - these are popularity contests more than a reflection of outstanding statistics or an individual's value to a team (the NFL MVP award is given by the Associated Press). Pro-bowl selections for example are another popularity contest - just look at who got selected this past year in the AFC. Another measure frequently used is Super Bowls. Dan Marino didn't win any Super Bowls. Trent Dilfer won a Super Bowl. Winning percentage is also frequently used - last time I looked, a quarterback doesn't play defense, return kicks or punts, or kick field goals. These pieces of evidence would never enter any serious discussion in terms of statistical evaluation.


My eventual goal is to identify the greatest passer of all time. I will use several statistical measures, many of which are mentioned in this post, to identify the most worthy candidates for consideration. As far as my research is concerned so far, Favre would not make that list. There are several other quarterbacks, not mentioned in this post, nor even displayed in either of the last two graphs that would make more worthy candidates, but that is for a different article.