The Most Overrated NFL Quarterbacks of All-Time… A Statistical Analysis and Introduction of the Janus Method

I do not usually venture into the realm of human indulgence… At least not in print anyhow… But due to recent events, I felt the need to address a certain situation that came to my attention…

There are three kinds of lies: lies, damn lies, and statistics. This holds most true whenever the method or interpretation of such statistics remains ambiguous, or when an interpreter fails to sufficiently justify their conclusion based upon the numbers. If one cannot recognize and accept the method of interpretation, such statistical analysis is worthless.

In addition, there are several facets of human existence that statistics cannot totally described. For example, a general’s win/loss record does not fully portray their prowess or strategic proficiency on the field of battle. A poor commander may achieve victory through blind luck while a great commander may suffer the same in defeat, yet neither fully illustrates her/his capability. However, one can sufficiently compensate for these disadvantages through cross-referencing various statistics, or finding the one category that best defines and effects the actions of another. We will not get the entire truth, but we will arrive closer to actual context than we would through basic comparisons.

This is no better illustrated than through a statistical analysis of NFL quarterbacks. Cowboys quarterback Troy Aikman gets off a first quarter pass. Tom Lynn photoRecently, a friend and I became embroiled in a heated argument regarding whether or not NFL pundits could sufficiently compare Dallas Cowboy Legend Troy Aikman to Arizona’s Carson Palmer and vice versa with any credibility. I argued that Aikman was the most overrated quarterback in NFL history, while my friend held that the chasm separating Palmer and Aikman was limitless in favor of the Cowboy.

Most football fans are loath to accept statistics as the decisive characteristic in any football related hierarchy. The objections are similar and of analogous merit: Statistics cannot compensate for human elements. There is no doubt to the legitimacy of this claim; yet, some statistics not only illuminate a better path to the truth, but also they have more positive repercussions spanning various categories as we will soon discover.

Method
We compiled data from the eight most instructive categories attributable to a quarterback’s ability. As a sample, we utilized bleacherreport.com’s list of the 50 Most Overrated Quarterbacks of All-Time and a list compiled by the author using Facebook, where friends randomly posted their Top 10 Greatest Quarterbacks. The categories chosen were: total seasons with 4000 passing yards or more, total career touchdowns, total career interceptions, touchdown to interception ratio, total seasons with 20 or more touchdowns, career yards per game average, passer rating, and completion percentage. We gathered all statistics from the NFL archives related to player performance. A player must have at least 10 years playing experience to be considered.

Once entered into Microsoft Office Exel, we sorted each category in ascending order and measured the impact this had on the remaining seven categories. For example, if we sorted the completion percentage category, we weighed the consecutive order of the other sections taking note of how such impacted the chronological order. If the sort placed 3 or more items out-of-order in each of the remaining categories, we classified this as an illegitimate source of determining a quarterback’s effectiveness.

Result
After analysis of each category, one section in particular withstood scrutiny and caused the least impact with the chronological order of the remaining seven categories. Whenever we sorted the touchdown to interception ratio (TD/INT), fewer than 3 items in each of the other sections became displaced, or out of chronological order. We interpret this to mean the TD/INT ratio better explains the chronological reality of each individual category.

For example, if we sort touchdowns in ascending chronological order, the order of total seasons with 4000 passing yards or more became extremely affected, but the TD/INT ratio category remained virtually unblemished. In other words, the TD/INT ratio has the greatest impact across every other statistical category. Therefore, we believe the touchdown to interception ratio to be the most accurate statistical method (the Janus Method) of analyzing a quarterback’s ability.

Conclusion
Using the Janus Method, we complied two lists regarding quarterback talent: the Top 9 Greatest NFL Quarterbacks (we stopped at 9 because we could not find a tenth out of the sample), and the 10 Most Overrated NFL Quarterbacks of All-Time. The TD/INT ratio was the decisive factor in each list’s construction. To make the “Greatest,” the ratio had to be 1.50:1 or greater. Anything less than 1.50:1 assigned a quarterback to the “Overrated” list. The resulting classifications are as follows:

10 Most Overrated NFL Quarterbacks of All-Time

Name- TD/INT Ratio
1. Archie Manning- 0.73:1
2. Joe Namath- 0.78:1
3. Otto Graham- 0.93:1
4. Terry Bradshaw- 1:1
5. Dan Fouts- 1.04:1
6. Johnny Unitas- 1.14:1
7. Troy Aikman- 1.17:1
8. Phil Simms- 1.27:1
9. John Elway- 1.32:1
10. Carson Palmer- 1.45:1

Top 9 Greatest NFL Quarterbacks of All-Time

Name- TD/INT Ratio
1. Tom Brady- 2.71:1
2. Steve Young- 2.17:1
3. Peyton Manning- 2.08:1
4. Joe Montana- 1.96:1
5. Drew Brees- 1.96:1
6. Dan Marino- 1.66:1
7. Kurt Warner- 1.63:1
8. Randell Cunningham- 1.54:1
9. Brett Favre- 1.51:1

Some may argue that the Janus Method still does not account for outlying factors such as era of play, Super Bowl and other championships, systems, or other human elements. However, as the above study indicated, the TD/INT ratio is the one category that transcends other statistical classifications or generations. In more absolute terms, if a quarterback’s primary duty is to get the ball into the hands of his own receiver, the TD/INT ratio determines how well he accomplished this task.

All other categories distort reality on a grander scale. For example, if one uses seasons with 4000 or more passing yards as their decisive category, such fails to consider the context of the passing game’s infancy, or the accomplishments of those quarterbacks proficient at the short passing game, i.e. Troy Aikman or Joe Montana. Likewise, if one chooses to utilize Super Bowl victories as their decisive category, such severely distorts the reality in other areas, in addition to the overall picture. Using this method of classification, Terry Bradshaw’s 4 Super Bowl wins would be far superior to Dan Marino’s 0, suggesting Bradshaw as the better quarterback. However, in every other statistical category recognized by football fans the world over, Dan Marino not only posted better numbers, they are infinitely better numbers in every area except championships.

This is not to imply the invalidity if other methods of classification. In the era of the Ring, and decades long Super Bowl dynasties the Ring will out. However, to measure the effectiveness of a quarterback’s true ability, keeping the ball in the hands of his own team to create opportunities to score, devoid of context or other outlying factors, the Janus Method of Statistical Analysis, weighing the TD/INT ratio, is a most efficient strategy.

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Comments
2 Responses to “The Most Overrated NFL Quarterbacks of All-Time… A Statistical Analysis and Introduction of the Janus Method”
  1. My reaction generalizes to any post or piece that compares athletes, albeit who played the same position, whom were not in the same peer-group: you can’t take it that seriously. There are WAY too many variables that many who post this type of stuff don’t even begin to consider.

    In this you attempt to legitimize one category over a specific, and highly limited subset, over the others you happened to include. Unfortunately, by doing so, your entire argument falls into the cardinal fallacy of logic, which is CORRELATION DOES NOT EQUAL CAUSATION. That is basically rule number 1 in Logic.

    But even if I wasn’t to unravel your entire post beforehand, I would still say that there are too many variables overlooked, especially in pro football; where for a decade, there were 2 leagues with different rules – where the rules and roles of different positions constantly morph – where a general inequity is built into each season’s schedule for each team, as commonly there are many more teams in the league than there are games and opponents – where each team’s home field has different characteristics and weather conditions – where each team has a different scheme and personnel and thusly each team’s subset of opponents has specific, unique schemes and personnel – where games have on a semi-regular basis been corrupted by both internal and external forces…..need I go on?

    Unless you can somehow statistically even BEGIN to deal with the above, you ain’t proving shit.

    • You are very correct… Correlation does nor equal causation, and there are various other factors that come into play, which you mentioned and the article acounted for as well… However, I think you missed one important aspect of the arguement. If you are the type of fan that prefers statistical justifications for the caliber of your QB of choice, then the TD-INT ratio would be the most telling category… Sure, it is not absolute, but it does spark a good conversation… Thanks for the post…

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