January 18, 2016

    Data Maturity in Sports: The Pursuit of Depth

    My favorite story of coaching revolves around a young John Madden, a Hall of Fame football coach, attending a coaching clinic where the speaker was Vince Lombardi, another Hall of Fame football coach. As Madden tells it, he was quite confident in his football knowledge. Showing up at the clinic, he sat in the back row and settled in for the eight-hour lesson. What he discovered was that the subject of the all-day session was a single play—the power sweep, which Lombardi made famous in Green Bay.

    At the end of the day, Madden was astonished by what had transpired and what he had learned. As he tells it, “I went in there cocky thinking I knew everything there was to know about football, and he spent eight hours talking about this one play. He talked for four hours, took a break, and came back and talked four more. I realized then that I actually knew nothing about football.”

    The reason this story resonates with me is that it reveals the depth available to us, even just with a little information. With the age of Big Data and lower job security in professional sports, this lesson has been abandoned to pursue width. Width is more data sources, more variables of that data, and an ever changing landscape of which variables are the most important for this particular week.

    The Problem is Width: Do not be Reactive

    Our experiences have matched this negative trend as the most common questions asked about our technology revolves around MORE width…

    “Can we do this test as well?”

    “Can we add this column to the dashboard?”

    “Can we collect/automate this data?”

    After the 3rd or 4th question regarding MORE, the line needs to be drawn in the sand so I have had to stop the excitement and endless possibilities with a simple statement, “The answer to all of your questions will be Yes, but you have to decide what information will actually change your decision.” The key part of this statement is that a width of variables and tests cannot help you make decisions proactively. The likely explanation for the desire of more data is to retroactively explain why things happen. If someone hurts their hamstring and you have dozens of variables, you can always point to one as the explanation (reactive). This approach isn’t scientific (sample size of one!), but it will likely provide a deterrent for the interested party (sport coach, general manager, etc.).

    The Solution is Depth: becoming Proactive

    The Age of Big Data can be helpful, collecting and storing massive amounts of information. However, the focus should be on depth of information rather than the smokescreen of width that calls for more tests and variables to examine. So rather than choosing 5+ technologies and 30+ variables, instead associating a few strong pieces of good data with each other is a novel, yet simple solution.

    Having a depth of frequent, reliable, longitudinal data allows you to begin the  pursuit of predictability.  If x happens, there is an increased/decreased odds of y that z will happen.

    The largest challenge for any organization is good data; specifically information that is…

    a. reliable/valid: The data has to be 3rd party validated for consistency and relevance.

    b. longitudinal:  Individual changes and trends require months/years to be more accurate

    c. frequent: You can never break the reactive habits and become proactive unless you have recent, current information to work from

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    Have a Mindset of Data Maturity

    Our technical staff always uses this term “data maturity” to refer to our longitudinal data that has depths of information to be proactive. Yet to me, the term refers to the largest challenge we face which is cultural or emotional. We must have the maturity to be disciplined, focusing only a few pieces of data that are frequent, longitudinal, reliable, and valid.

    Vince Lombardi saw this need for simple depth to achieve success even 60 years ago. He saw this simplicity of depth as the best route for communication to staff and players, when such understanding was ubiquitous within an organization, then execution was possible. One of his more memorable quotes was “You cannot coach them what they have not been taught.

    We might think things have changed, every generation does, but the reality is we can just better quantify good coaching instincts.

    Tag(s): Data , Education

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