The Tenth Inning
 The Tenth Inning Blog
Periodically, I will post new entries about current baseball topics.  The posts will typically be a mixture of commentary, history, facts, and stats.  Hopefully, they will provoke some  of your thoughts or emotions. Clicking on the word "Comments" associated with each post below will open a new dialog box to enter or retrieve any feedback.
I Don't Like the Way Baseball Has Evolved

Call me old-school.  Say that I can’t handle change.  Tell me I’m a product of the Deadball Era.  I don’t care.  Some others might be hesitant to admit it, for fear of being shamed by the new-age baseball analysts and commentators and other baseball enthusiasts.  But, I’m not afraid to say it--I just don’ like the way the game of baseball has evolved over the past five to seven years.

Data collection technologies and baseball analytics are at the root of the changes occurring.  I understand the value of data analytics.  I worked a long time in information technology for a couple of Fortune 500 companies, where I learned to fully appreciate how comprehending your company’s essential data can offer new insights in how to increase revenues, reduce expenses, improve productivity, and enhance customer satisfaction.  Gaining those insights can fundamentally change your business.

A few years ago, some Ivy League MBA-types figured, “why not apply data analytics methodologies and technologies from the business world to the game of baseball?”  It was as though the basic stats used in baseball for over 100 years weren’t sufficient enough anymore.  Baseball analytics gave life to metrics that only the real baseball geeks (many of them sabrmetricians) previously talked and wrote about.  It started a trend that has consumed the sport now.  You can’t watch a game on TV nowadays that doesn’t reference many of the new metrics.

Analytics are currently used by every pro baseball organization in practically every facet of the sport including roster creation, player selection and development, player health, opposing team and player assessments, and contract negotiations.  By and large, I think it has been good for baseball organizations who, like all other industries, are trying to optimize their business operations.

But it didn’t stop with just the back-office operations of the sport.  Game strategies and decisions are also being heavily influenced by the use of data analytics and are being determined before the games are played, not as the games are happening.  (Remember the Los Angeles Dodgers’ pitching situations in the World Series last year?)  I saw a recent article saying the two most important skills of major-league coaches have evolved to being able to throw batting practice and using the SQL database programming language to navigate the massive amounts of data available to teams.

If you watch any MLB game now, you’re likely to see most pitchers, particularly relievers, throwing in the upper 90s and frequently breaking 100 mph.  Hitters are all about extra-base hits--singles are only marginally valuable.  Strikeout rates for many hitters are in the 20-30% range.  A third of all plate appearances don’t result in a ball put in play—they’re either a strikeout, walk, or a home run.  Fielders, especially infielders, play all over the field using shifting strategies.  It’s not uncommon for a team to use six or more relief pitchers in a game.  Stolen bases and bunting are no longer a strategic part of an offensive strategy.  Pitch framing by catchers is viewed as a skill equally important to digging pitches out of the dirt.

If baseball people had mentioned these as predominant scenarios just ten years ago, most of us probably would have laughed them off.

Yet they are real and are not going away, but I’m not sure they’re all that good for the game.  The game has given way to a simple “throw hard, swing hard” mentality.  A lot of the other intricacies that defined the game for so long don’t seem to be as relevant anymore.  I think the game is losing some of its allure because of this shift.

Baseball has become dominated by new-fangled terminology (much of which is facilitated by data analytics) such as spin rate, launch angle, exit velocity, route efficiency, defensive shifts, defensive runs saved, and runs created.  Basic familiar stats such as saves, wins, RBI, and fielding average are now being debunked as relevant measures of player performance.  Even the most casual fan could count or calculate these basic stats, but nowadays you need a PhD in mathematics and Amazon’s cloud computing services to figure out some of the newer metrics.

Part of the folklore of baseball has involved such things as the tracking of career leaders in various statistical categories.  For example, we all know Mariano Rivera as the all-time saves leader with over 600 saves, and Rickey Henderson’s Hall of Fame career was largely based on his ability to draw walks as a leadoff batter and steal bases.

In the future, will we know Aaron Judge’s career launch angle or Clayton Kershaw’s career spin rate?  I hope it doesn’t come to that.

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