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Building better ballplayers through data – ‘The MVP Machine’

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One of the longest-standing truisms in the athletic realm is that nothing is more important than inborn natural talent; while practice can make you better, there’s no amount of practice that can compensate for a lack of inherent ability.

But in baseball’s brave new world, with reams of data available at the press of a button, perhaps that truism isn’t quite so true after all.

“The MVP Machine: How Baseball’s New Nonconformists are Using Data to Build Better Ballplayers (Basic, $30), by Ben Lindbergh and Travis Sawchik, is an exploration of the rapidly-blossoming notion that there’s more to it than that. Teams are turning their vast data-collecting capabilities toward the field of player development, trying to find ways to maximize the talent of their players in new and sometimes unconventional ways.

It’s a new frontier, one awash in high-speed cameras and swing gurus. It’s all about spin rates and launch angles and elevating the velocity of the ball, be it thrown or batted. And the people who are the earliest adopters, from the front offices to the fields, are reaping the rewards.

Since baseball’s beginnings, there has been a way that things are done. The conventional wisdom (and there was no room for any Unconventional wisdom) was that talent would always win out; the cream would always rise, etc. For a century or more, that’s how it was. Certain skills and behaviors were considered important because they always had been important.

But after the seismic shift of Michael Lewis’s book “Moneyball,” the unconventional wisdom started appearing in the front offices of more and more teams. The value of analysis in the acquisition of players – drafts, signings, trades – became common knowledge, with each team building their own in-house analytics team … and when everyone has an advantage, no one has an advantage.

However, there will always be those who seek an edge. And it turns out that that edge is in the realm of player development. It’s no longer about finding undervalued assets and exploiting them, but rather about maximizing the talents of the players already in your system.

Linbdbergh and Sawchik go deep, talking to figures up and down the game. They dug into data-driven development philosophies on levels ranging from broad to granular, looking at how things are handled on an organizational level (they spent a lot of time on the Astros, which makes a ton of sense, considering the forward-thinking nature of that team) while also talking to individual coaches (the stuff with Brian Bannister is fascinating) and players (ditto Trevor Bauer) about what they have discovered buried in the numbers.

Bauer is one of the stars of the book. He has long been a proponent of the power of data, unabashedly sharing his thoughts with pretty much anyone who will listen. Of particular interest is his work with the Washington-based Driveline, a baseball performance training facility led by Kyle Boddy, a data scientist who built his development model on a foundation provided by former MLB pitcher Mike Marshall’s ideas and expanded upon through rigorous research.

Bauer’s usage of unconventional training methods – particularly throwing weighted balls – was initially viewed with skepticism at best and outright ridicule at worst. But as technological advances have made their way into the game – high-speed cameras and biometric monitoring devices from companies like TrackMan and Rapsodo and the like – someone like Bauer, already analytically inclined, can start using that information to their benefit. We watch him use the information provided him by Edgertronic cameras – cameras that capture thousands of frames per second – to gradually craft a pitch that breaks the way he wants it to. There may be no one currently in baseball who has so single-mindedly devoted themselves to full maximization of his abilities.

And then there’s Bannister, who’s a fascinating case himself. A former pitcher who put up middling numbers over a four-year big-league career, Bannister was someone who recognized the possibilities of data early on. Even during his playing days, he espoused the importance of statistical analysis and sabermetrics; he wound up in the Red Sox front office starting in 2015.

He became something of an organizational shooting star, rapidly rising in the ranks. Bannister is one of the still-rare people who can bridge the gap between the numbers side and the on-field side; with his experience as a player, he brings a credibility that those who haven’t played the game simply can’t match. One can argue whether playing experience should matter, but it undeniably does, so having someone like Bannister – Lindbergh and Sawchik call them “conduits” – is vitally important in ensuring that the lines of communication are open and flowing in both directions.

(There’s a moment where Bannister – a gifted photographer – basically ascribes his development philosophy to an understanding of the work of the famed photographer Ansel Adams and it is unexpected and fascinating and one of the coolest bits of what is a very cool book.)

Honestly, I could go on and on. Want to learn something about how little guys like Jose Altuve and Mookie Betts turned into MVP-level hitters? Or more about the revolutionary data-driven approaches that led to World Series titles for teams like the Astros and Red Sox? The fascinating details just keep coming – we’re watching a developmental revolution take place in real time and this book serves as an effective chronicle of that sea change.

“The MVP Machine” is an incredibly well-reported look at one of baseball’s bleeding edge frontiers. And for a book addressing a dense and fairly wonky subject, it proves remarkably readable as well – Lindbergh and Sawchik are both talented writers who have a particular knack for finding engaging, understandable ways to present complex ideas.

(Note: This is where I stick my plug for the “Effectively Wild” podcast that Lindbergh co-hosts for the website FanGraphs; it is a repository of delightful dorkiness surrounding baseball, exploring subjects that are silly or sublime or sometimes both. They dig into the numbers but also embrace absurd hypotheticals and the simple on-field beauty of the game. It’s good, is what I’m saying.)

Anyone with a desire to learn more about how baseball’s future is being built in the here and now should really check out this book. The ways players learn and the ways we learn about them are changing. “The MVP Machine” is a magnificent exploration of what those changes mean for the game we love.


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