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Using Minitab Statistical Software to Analyze the Woeful Bengals

Bengalsby Jeff Parks, guest blogger

Being a Cincinnati Bengals fan is tough. It's true that Bengals fans don't have it as bad as, say, long-suffering Chicago Cubs fans...nevertheless, the Bengals haven’t won a playoff game since January 1991. That's currently the longest streak in the NFL. In the 1990s they were voted the worst sports franchise by ESPN. Not the worst football team, mind you, but the worst franchise in all of sports.

Not the L.A. Clippers. Not the Cleveland Browns. Not the Pittsburgh Pirates.

The Cincinnati Bengals.

Why? Why must it be so? What separates the Bengals from the good teams in the NFL? 

During the 1980s they went to the Super Bowl twice. Once they were within about 39 seconds of winning the whole thing. In the 1970s they were competitive with the great Pittsburgh Steelers dynasty, year-in and year-out, for AFC North supremacy.

So what happened?

It was a question like this that sent me on the cathartic journey of writing a book, Applying Six Sigma Tools to the Woeful Bengals: A Fan Laments

As a Six Sigma Master Black Belt for the past 12 years, I've  worked on more than 350 projects in over 15 industries...surely I could bring some of what I know about process improvement to find some way—any way—to improve them “Who Dey” Bengals.

I started this venture by postulating (the “Define” Phase of DMAIC, if you will), what would the Bengals need to do to be  more like today's AFC Champions—the people who play in the Super Bowl like the Bengals once did?

Let’s start with the win-loss record over the past 20-odd years. From 1991 till 2012, the Bengals have average a record of

6 wins
10 losses

For a winning percentage of 37%.  That’s right—37%.

Now look at the percentages for the AFC Champs over that same time period:

YEAR

AFC CHAMP

WINS

LOSSES

TIES

WINNING PCT

1991

Buffalo Bills

13

3

0

81.25%

1992

Buffalo Bills

11

5

0

68.75%

1993

Buffalo Bills

12

4

0

75.00%

1994

San Diego Chargers

11

5

0

68.75%

1995

Pittsburgh Steelers

11

5

0

68.75%

1996

New England Patriots

11

5

0

68.75%

1997

Denver Broncos†

12

4

0

75.00%

1998

Denver Broncos†

14

2

0

87.50%

1999

Tennessee Titans

13

3

0

81.25%

2000

Baltimore Ravens†

12

4

0

75.00%

2001

New England Patriots†

11

5

0

68.75%

2002

Oakland Raiders

11

5

0

68.75%

2003

New England Patriots†

14

2

0

87.50%

2004

New England Patriots†

14

2

0

87.50%

2005

Pittsburgh Steelers†

11

5

0

68.75%

2006

Indianapolis Colts†

12

4

0

75.00%

2007

New England Patriots

16

0

0

100.00%

2008

Pittsburgh Steelers†

12

4

0

75.00%

2009

Indianapolis Colts

14

2

0

87.50%

2010

Pittsburgh Steelers

12

4

0

75.00%

2011

New England Patriots

13

3

0

81.25%

2012

Baltimore Ravens†

10

6

0

62.50%

 

AVERAGE

12

4

0

76.70%

So, on average, the AFC champs won twice as many games (12) as the Bengals did (6) over those 20-odd years from 1991.

We can use Minitab to superimpose those two win-lose curves on the same graph. 

Bengals vs AFC Champs

The Bengals in essence need to:

  • Move the above curve to the right (i.e., increase their average wins per season more in line with the AFC champs).
  • Decrease the width of the curve (i.e., be more consistent in the wins each season).
  • In other words, “shift and narrow” the curve.

A good question to ask right about now would be: “What does it take to produce a good winning percentage—12 or more games in a 16 game schedule—in the NFL?”  It has been said that defense wins championships, but is that really true? To find out, I pulled data from the past 10 years for all NFL teams from the nfldata.com web site.

Then I used Minitab to do a regression analysis on “defensive points/game” (how many points does a team’s defense allow each game) as well as “offensive points/game” (how many points does a team’s offense score each game) as “X” or “independent variables.” I wanted to see if any correlation exists for my “Y” or “dependent variable” of “Winning percentage” (number of wins each year divided by 16 total games in a season). My analysis in Minitab produced the following output:

Bengals Regression Analysis

Points per game (Pts/G) for both offense and defense are statistically significant, and the adjusted R-squared value shows the model explains 83.8% of the variation in winning percentage (not too bad of a model).

But which is more important: offense or defense?  Notice the coefficients or the numbers in front of each of “DEFENSE Pts/G” and “OFFENSIVE pts/game” above respectively. These values tell us how much each of the variables impact winning percentage (our “Y”).

Since the defense .0279 is larger than the offense .0273, we know that defense DOES matter more, but not by much.

(Note: that the defensive coefficient is negative, -0.0279, only means that as the defense allows more pts/game then the winning pct goes down. Likewise, if the offense pts/game goes up, so does the winning pct. This should be intuitive, as when any defense stops any opponent from scoring the defense pts/game will go down—and that’s a good thing.)

By comparing the two numbers (their absolute values) we can say that, the defense pts/game has a 2.2% greater impact on winning pct than does the offense.

Maybe Defense does win championships, but not by much.

Now that we know defense matters so much, to really help the Bengals we would need to do a deeper dive into what aspects of the Bengals defense is so lacking when compared to the defense of the AFC Champions. And since the two variables of offense/defense pts/game are so close, we would want to do the same thing for the Bengals’ offense.

For instance I was able to determine that there is a statistically significant difference between the number of sacks the Bengals get each game compared to the AFC Champions over the past 10 years:

Bengals Paired T Test

As I explain in my book, by using Minitab for hypothesis testing, capability analysis, regression, and graphing, I was able to come up with some specific, precise items that the Bengals need to address. (For instance, the sack difference above is totally attributed to the linebackers. The sacks from the defensive line, corner backs and safeties are on par with the AFC Champion teams.)

Will they do it?

I don’t know but I emailed a copy of my book to Paul Brown, the Bengals' general manager—so one can only hope, right?

 

About the Guest Blogger:

Jeff Parks has been a Lean Six Sigma Master Black Belt since 2002 and involved in process improvement work since 1997. He is a former Navy Nuclear Submarine Officer and lives in Louisville, KY with his wife and 7 children. He can be reached at Jwparks407@hotmail.com and via Twitter, @JeffParks3. 

 

Would you like to publish a guest post on the Minitab Blog? Contact publicrelations@minitab.com.

 

Photograph of Bengals quarterback Andy Dalton by Melissa Batson, used under Creative Commons 3.0 license.

 

Comments

Name: juan • Wednesday, August 21, 2013

very good


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