MEANFootball™ - Our Story ⭐
Formidable. Certainly Not Average.

A Narrative about MEANFootball™.

My 4:30 am idea was not the birth of the analysis. It was the birth of communicating the analysis.

It actually began in 1988.

But, the 4:30 am experience in June 2025 solidified the concept.

The name captured everything the project had become. These four ideas supported and merged:

1) Mean is the statistical average—the foundation of the analytical system. It also reflects a commitment to saying what the data actually show, rather than what people hope or expect.

2) "Mean what I say and say what I mean." via objective analysis and repeatable data-driven evidence.

3) "Mean"/violent environment where girdiron matches are pitted.

4) Finally, the gentle giant, iconic Hall of Fame player, Mean Joe Green, of days past.

The objective is to understand performance better than opinion alone ever can.
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The Story Behind MEANFootball™


Why MEANFootball™ Exists

MEANFootball™ began with a simple question:
 
Can objective analysis help us better understand performance and improve decision‑making?

That question has guided my professional and analytical life. Also, the work of those who have joined me on this journey.
 
The Beginning: 1988
 
In 1988, long before sports analytics became mainstream, I conducted my first performance study after graduating from Duke University. That was Duke's basketball star, Danny Ferry’s free‑throw performance related to game outcomes.
 
I shared the results with Danny Ferry and Coach Mike Krzyzewski. More importantly, it became a valuable teaching tool.
That same year, I presented the study to management teams at a Fortune 500 manufacturing company. It served as a real‑world example of applying measurement, variation, and process improvement to organizational performance.
 
The lesson was simple:

    * Performance can be measured.
    * Variation can be understood.
    * Better decisions are made when you master both.

Learning How to Understand Performance
 
The analytical philosophy behind MEANFootball™ did not originate on the football field.

It was shaped through the study of economics, marketing, finance, quality management, and statistical decision‑making.
While earning my MBA at Duke University’s Fuqua School of Business, I learned from outstanding educators. After graduating, concepts and hands-on gained through following quality pioneers: Dr. W. Edwards Deming, Dr. Joseph Juran, and Philip Crosby.
 
Their teachings emphasized principles that remain central to MEANFootball™:
 
    * Separate meaningful signals from random noise.
    * Continuously improve processes and outcomes.
    * Measure performance objectively and understand variation.
    * Make decisions using evidence rather than assumptions.

The Coast Guard and the Big Peanut
 
During my service as an officer in the United States Coast Guard, another lesson reinforced these principles.
Our boss, a highly respected senior officer, often asked a deceptively simple question:
 
      “Did you move the big peanut forward today?”
 
Progress didn’t require perfection. It required moving important work forward, one deliberate step at a time!

That philosophy remains a cornerstone of MEANFootball™.
 
A Lifetime of Learning, Applied to Sports
 
Throughout my professional career—consulting, process improvement, management systems, and analytical problem-solving—one question persisted:
 
     Can objective analysis help us better understand performance and positively impact teams as well as communities?

Sports became an ideal laboratory
 
In 2013, I analyzed the Cincinnati Bengals using statistical process control. This work showed how variation, trends, correlation, and assignable causes can help explain as well as forecast team outcomes.
 
The conclusion extended beyond football:
 
     Performance should be measured, understood, and continuously improved.

From Newspaper Columns to MEANFootball™
 
In 2019 and 2020, the direct predecessor to MEANFootball™ appeared as a weekly column in The Nugget, a community newspaper in Central Oregon. These articles introduced readers to an objective, transparent, and systematic approach to analyzing football games. They also showed that fans were ready for a new kind of football analysis.
 
The Proving Ground: 2024–2025
 
Although the principles behind MEANFootball™ were developed over decades, the modern analytical framework was built and comprehensively tested beginning in 2024. This was following the conclusion of my full‑time professional career.

The 2024 NFL season became the proving ground for rolling averages, defined cause-and-effect, variation analysis, trend evaluation, and objective forecasting. Also, comparative analysis of other NFL game predictive models - the ones with billions of dollars in sales.
 
Building on those lessons, the 2025 season became a fully documented, proactive forecasting campaign.

2025 Results

    * NFL Regular Season: ~65% prediction accuracy. Higher than most NFL experts. #3 in 18 experts from big media outlets
    * NFL Playoffs: 12 of 13 games correctly forecasted (92%)
    * Last Two Super Bowls: Outcomes correctly predicted. Also, documented three out of four in recent years 
 

Importantly, process improvements in these models are showing even better results to these results!

These results reinforced a principle that has guided our work since 1987:

Disciplined analysis can produce remarkable insights.

What We Believe

We do not believe in tracking numbers just for the sake of empty data. Neither do we believe that raw numbers tell the entire story.

Interestingly, the very same year I was conducting that first statistical study at Duke in 1987, legendary football coach Steve Spurrier arrived in Durham to take over the Blue Devils football program. He famously shared his philosophy on statistics: 

"Statistics are for losers and assistant coaches. Head coaches worry about wins and losses."

True analysis should not care about bloated, meaningless volume stats. At MEANFootball™, we focus entirely on the vital metrics that actually drive performance and directly translate to wins. At the same time, we know data has limits.

We agree completely. Statistics provide the hard boundaries of insight, but context provides the true understanding. Together, they dramatically improve your decision-making.

Our Mission

MEANFootball™ exists to help football fans think differently about the game they love. Our approach is entirely:

    * Objective
    * Transparent
    * Repeatable
    * Continuously improving
    * Robust

We don't claim perfection. We claim a disciplined, relentless process. And every single week, we line up to ask the exact same question:

     "Did we move the big peanut forward today?"
 

MEANFootball™ is not the result of forty years spent building a football model or working in isolation.

It is the result of forty years spent learning, collaborating, and striving to understand performance.