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A long time ago, in a galaxy far, far away, sabermetrics was all the rage for different reasons. 

The analytics-based method for constructing a baseball roster was revolutionary and controversial. It was met with hostility from the purists – the scouts, coaches, and managers who made baseball decisions based on their “eye test.” 

Analytics brought in the dimension of numbers and hard statistical analysis that bucked the traditional notions of the “five-tooled” player that had all of the desired physical attributes. Instead, factors such as high on-base percentage (which often meant having patient hitters that could take a walk) became more important. All of a sudden, Napoleon Dynamite could compete with the Incredible Hulk.   

A man named Bill James can be credited with its creation. A man named Billy Beane can be credited with pioneering its practice. If you’ve seen the movie "Moneyball", you know how the rest of this story unfolds. If you haven’t seen the movie, you really should, but here is an excerpt from the book it was based on. 


Today, sabermetrics is enjoying a wide acceptance rate in the often conservative-to-a-fault baseball community—thanks in large part to Beane’s success. Beane’s forward-thinking has led to other general managers and executives applying sabermetrics to their decision-making processes, including lineup changes, player acquisitions, and other roster maneuvers. 

One of those GMs is Theo Epstein, who just saw his Chicago Cubs team get ousted by the New York Mets in the National League Championship Series. 

According to The Great Analytics Rankings that ESPN put together of the four major sports teams, the Cubs were among the teams classified as being “all-in” on analytics. 

Epstein, of course, used sabermetrics to help the Red Sox win the World Series in 2004 and 2007. Since joining the Cubs, he’s supplemented the sabermetrics formula by developing a custom baseball info system. He also hired Chris Moore—a Ph.D. in cognitive neuroscience at Princeton—to infuse predictive modeling and machine learning into their processes. 

The Mets—the other lovable loser that everyone roots for—are moving on to the World Series. And, with that, "Back to the Future Part II" was wrong about the Cubs making the Series in 2015. 

The Mets used analytics to fuel their run to the World Series.  

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Although it might not be through a sophisticated software platform, they have their own system in place dubbed "The Matrix". The Matrix is a chart that helps the Mets coaches forecast their hitters’ performance against opposing pitchers. 

The Mets ranked as “believers” under the ESPN ranking system, one spot behind the “all-in” distinction.  

Of all the baseball organizations that have adapted analytics, the Houston Astros have been the biggest proponents. 

They ranked first among their MLB peers and second overall among all of the major sports franchises. The Astros’ analytics-inspired cultural revival made waves this season, especially when it came to using sabermetrics and mathematical models to call more defensive shifts on balls that were in play. 

As ESPN described, “Houston has made metrics the foundation of its revival.” The Astros enjoyed a remarkable turnaround this season, going 86-76 after a disastrous 70-92 output last year. 

With the Mets preparing to square off against the Kansas City Royals in the World Series, it’ll be interesting to see how often analytics gets the call to help decide a critical substitution or pitching change. 

The pervasive use of analytics in baseball is proof that it can also be a competitive difference-maker for the haves and have-nots in the corporate arena. 

How are decision-makers outside of the baseball world taking advantage of analytics?

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Written by IBM BP Network