Six Sigma

Brett Favre – Greatest Ever?

By Ron Pereira Updated on April 1st, 2013

“No data have meaning apart from their context.”
– Donald Wheeler

brett-favre.jpgUnless you live under a rock (or perhaps outside of the USA) you have likely heard that Brett Favre has decided to retire from the NFL.

Like him or not, no one can deny Favre’s greatness.  He played the game the way it is meant to be played.  He was tough, competitive, and left everything on the field.  Personally, while not a Packer fan, I always enjoyed watching him play.  To be sure, I will miss him.

Greatest Ever?

The sports radio shows are all debating where to place Favre on the list of all time best QB’s.  Most have him top 5 or 10.

Since I am into data, I thought I would do a little research myself.  While I was playing around with the data it dawned on me just how badly most people screw this type of analysis up.

MS Excel Fun

favre-passing-yards-1.JPGTypically, if someone wanted to see how consistent Favre was over his career, say for total passing yards, they would most likely find the data and dump it into MS Excel.  Then they would get busy with the infamous chart wizard finishing with a graph similar to the one to the left (click to enlarge).

From here the debate would really begin.  Favre haters would explain how inconsistent he was.  They would say, “Just look at the data man!  It’s all over the place.”  Meanwhile, Favre fans would explain how these haters need to get their eyes checked.  After five minutes of debating the two would eventually agree to disagree.

Adding Context to the Analysis

favre-passing-yards-2.JPGIt doesn’t have to be this way.  Instead of creating an old fashioned line chart as shown above, the two friends would be better served by adding some context to the analysis.

The easiest way to accomplish this is via a standard control chart.  The simplest choice, and my personal favorite, is to create an Individuals chart as shown to the left (click to enlarge).  The “context” is created by the addition of control limits and a measure of central tendency, namely the mean.

Once we have this graph in front of us it is pretty obvious that Brett Favre was one consistent passing machine!  All the data points fall in between the control limits demonstrating good old common cause variation.

In this example, the Favre hater would likely walk away mumbling something under their breath as the Favre fan would sit back, smile, and remember just how much they loved statistics… and Brett Favre!

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  1. Jason

    March 5, 2008 - 10:26 pm

    Ron –

    Good starting analysis. Football doesn’t lend itself to 6Sigma analysis quite like baseball, but I like it.

  2. Ron Pereira

    March 6, 2008 - 11:52 am

    Thanks Jason.

    Since I know you… and know you are both a six sigma guru and and baseball fanatic… I’d love to see some of your baseball analysis!

    Plus, I am sure others would be interested in this too!

    What say you?

  3. mark graban

    March 17, 2008 - 6:25 am

    The context question to ask is “greatest based on what?” Is any single metric a good gauge of anything? Do you rate Favre on wins, passing yards, TDs, or that stupid passer rating #? As Deming said, some important things cannot be measured. Hence the hours of debate. You’ll never be able to quantify an answer to that question of “who is the greatest?”

  4. Ron Pereira

    March 17, 2008 - 7:20 am

    But it sure makes for some water cooler conversation doesn’t it Mark?

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