Moneyball 1.0

If you have been following baseball since the turn of the new millennium then you know the story of how the Oakland A's used new-age statistical data to better assess and evaluate players that had otherwise been overlooked by the market.  The A's were able to expose an outdated system that had overvalued players winning hundreds of games against bigger market, bigger budget teams.  Since then teams have used the same model to win multiple World Series titles and now every team has its own data and evaluation model.

The Advent of Statcast

In 2015 Trackman radar technology was installed in every Major League park.  What you get is mountains of data for pitchers and hitters to assess outcomes such as spin rates, exit velocity, and launch angles.  Combining all of this data with the new age technology such as Hit Trax, Diamond Kinetics and high-resolution slow motion camera technology we can get a real understanding of training the outcomes that make elite players elite.  Players like Washington Nationals second baseman Daniel Murphy are talking more and more about practicing within the parameters of certain launch angles in the cage “You want to hit the ball optimally about 25 degrees at 98 mph,” Murphy said, “those are home runs, but Ryan’s exit velocity last year, I read articles on it, was borderline elite, so I think that he’s just looking at it like, if I can take the already elite skill of bat-to-ball and exit velocity off the barrel and get it at the right angle, now we’re starting to do some damage” - (accessed April 10, 2017).


Applying the Data to an Intent Based Movement Pattern Model


Every coach/organization's ultimate goal should be to create an environment that gives both hitters and pitchers a high rate of transfer from practice to the games. So what transfers?  Do external mechanics transfer, or does internal intent matter more?  In the heat of battle will you be thinking more about the specific cues you have been given by a coach or will you be more focused on producing specific outcomes?  With the statistical feedback produced through Statcast we can better apply Bernstein’s principle of learning a specific motor skill that suggests that the body will adapt to accomplish the desired outcome when we now know and are measuring those outcomes.  If your goal is to outrun the fastest tiger to survive, and you now how fast that tiger runs wouldn't it make more sense to survive if you trained to run that fast all the time?  The aesthetic of the movement is only established after the intent of the movement is understood and mastered.  With this in mind, coaches can start to understand and measure the movement patterns that are creating these high-level outcomes to train and plan their programs around them.  No more guessing.   

To quote my Twitter friend Ryan Parker "Moneyball 1.0 was all about buying better groceries, 2.0 is now about how to cook and prepare them better."

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