Just How Much Performance Data Is Enough?

Golf Digest has put up a fairly lengthy article called Big Data: Info Seekers that I thought some of you might be interested in. It takes a detailed look at how three players -- Zach Johnson, Bryson DeChambeau and Kevin Streelman -- collect and use "big data" to improve their games.



If you Google "what is big data" you'll get this definition: "extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions." But I think this additional bit from the Wikipedia article on big data adds an important fact:

Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy.

Lately, the term "big data" tends to refer to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set...

That second paragraph better sums up what golfers are looking for when they turn to big data. They're looking for trends and patterns that may not be readily apparent just from looking at the data itself, simply because there's too much for one person to grasp easily.

Some golfers -- and not just golfers, but other athletes as well -- are looking for something, anything, that will give them a competitive edge against the field. For example, according to the article, Zach is analyzing 600+ performance stats from ShotLink. Bryson is measuring how many millimeters his shaft flexes during his downswing. And Kevin is using a special launch monitor when he putts.

That's right... when he putts.

I'm linking you guys to this article because I know many of you want to copy the techniques of the pros. But you also need to ask yourself... just how much is too much? We can organize tens of thousands of data points if we desire, but does that mean we need to use them all? Is there some point at which all this analysis becomes counterproductive and actually hurts our games?

Those are questions you'll have to answer for yourselves. But this article is a good overview of the kinds of things that the pros are teasing from the multitude of stats that are now available to them. You need to know what's being done before you can decide if you want to pursue the same approach...

Or whether such analysis will simply paralyze you with info that's beyond your ability to use.