MLBAM – Batting 1.000 Against Big Data

In 2014, the MLB’s Advanced Media department introduced a new method of measuring every single play that occurs over the course of a game in the form of an advanced tracking system. The tracking system observes plays and sends coordinate data to computer systems at MLBAM (Major League Baseball Advanced Media), which uses algorithms developed by New York University computer science professors Claudio Silva and Carlos Dietrich to compute game metrics. The system had its debut last year at three MLB parks (Miller Park- Milwaukee Brewers, Target Field- Minnesota Twins, and Citi Field- New York Mets), and takes into account statistical factors like error mapping and confidence scoring.

The video below showcases some of the analytical data points made available by MLBAM tracking system. Watch as former Atlanta Braves outfielder Jason Heyward makes a game-ending, diving catch in the 9th:

The goal of this project is to revolutionize the way baseball is evaluated; by presenting tools that connect all actions that happen on the field and determining how they work together. This new datastream will enable the industry to understand the whole spectrum of a baseball game (batting, pitching, fielding and baserunning) and enable new metrics for evaluation by clubs, scouts, players and fans. It can be confidently said that this is the largest league-wide embrace of advanced analytics, regarding big data, to date.

Metrics Utilized

 (Taken from an MLBAM.com article on the tracking system)


Batting

For batting, real-time metrics will be exit velocity, launch angle, projected home run with distance, hang time, and fly-ball distance.

Base Running

Real-time base-running metrics are lead distance, acceleration, max speed, and home-run trot. “First step, route efficiency, stealing first step, and secondary lead distance will be available with a 12-second delay.” (MLBAM.com)

Fielding

Fielding metrics available live will be acceleration, max speed, and shift positioning; “12-second–delay metrics will include total distance on caught balls, first step, arm strength (catcher and fielders), exchange (catcher and fielders), pivot, and catcher ‘pop time’ (time to throw down to second base)”. (MLBAM.com)

Needless to say, it’s pretty cool stuff. With the 2015 season well underway, I’m excited to see what the inagural year-end reviews are on this innovative approach to sabermetrics.

Drive Home Safely,

Bryan White, MBA

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MLB Analytics : Benefiting Businesses

MLB Data

This post marks the beginning of the second topic I will discuss in my blog postings; the use of advanced analytics in the MLB to gain insight into both gameplay and actual player value. Previously, I had discussed how the MLB’s model for social media could be applied (and would be beneficial) to almost all firms in today’s business climate. In a similar fashion, I will discuss how it would be prudent for businesses to adopt 3 particular mindsets/ analytical practices that the MLB is using to decipher big data. Many of the best practices now embraced by GMs and team managers throughout the sport can, and should, be used by executives in all lines of business.

1.) Value the Data


For the majority of its vast history, baseball managers have made decisions almost entirely off experience and ‘gut feeling’. This gut feeling was a justifiable explanation for just about any decision, ranging from the starting lineup to a pinch hitter or which relief pitcher to bring in from the bullpen. Now, with the understanding of big data through advanced analytics, nearly every in-game decision is driven by longstanding data records showing players’ statistics and tendencies. If a manager makes a critical in-game decision in baseball’s modern era, he’d better have data-supported reasoning.

The business takeaway of this is simple, be more data driven in decision making. Not saying that past experience isn’t important or applicable, but a willingness to take advantage of data you have at your disposal must be present.

2.) Be Open-Minded to New Metrics & Methods


Traditionally the hitting aspect of the game was solely evaluated on home runs, RBIs and batting average. For pitchers, wins and ERA dominated the scene. Nowadays, new metrics have been introduced that have changed how we have traditionally labeled a player as “effective”, and this has sparked quite the debate. It started slowly, with a handful of teams valuing on-base percentage (the prevalent statistic in the innovative book Moneyball) over the longstanding batting average. This has placed enormous value on players like Mike Trout, who thrive on the basepaths.

A similar approach needs to be embraced in the corporate realm. Traditional data does have its place, but the analysis of new forms of data such as text, social media, etc… are available that give an even more accurate picture of the climate of an industry.

3.) Prediction


Baseball teams have historically scouted, evaluated, and compensated players based on their production in previous seasons. The better a player played in the past, the greater his salary in the present and future, when contracts began to lengthen in years and ‘guaranteed money’ became a thing. By the end of a lengthy contract, teams were often overpaying for players whose best days on the diamond were well behind them (think Carlos Zambrano for all you Cubs fans out there). However, the increased use of analytics has enabled teams to become better at evaluating a players’ future performance (and when they might plateau), and structuring their contracts in accordance.

Likewise, businesses should combine traditional business intellect with predictive analytics. With so much big data now available to be interpreted, companies can make informed decisions not based on what has occurred, but what’s most likely to occur based on the trends data can illuminate.

Each of these embraces of modern analytics can be as beneficial to the corporate sector as they have been to America’s past time. All it takes is an inquisitive mindset, and a little deviation from the status quo, to gain lasting competitive advantages and industry insights.

Drive Home Safely,

Bryan White, MBA

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For the Love of the Game…

Prince Fielder celebrates a walk-off HR during his playing years with the Milwaukee Brewers.
Prince Fielder celebrates a walk-off HR during his playing years with the Milwaukee Brewers.

Hello all,

There are few things in society today that captivate individuals like competitive sport. We become so fixated at the results of sports competitions that we allow it to consume our afternoons, weekends, Monday morning office conversations, and social media feeds. With the NFL deep in its post-draft offseason and the NBA playoffs winding down, baseball fever will shortly be in full swing. Soon, ballparks all across the continental United States will be flooded with families and high school/college students looking to get the most out of their summers. Naturally, spectacles such as this are both highly lucrative and highly marketable.

When Bill James and Michael Lewis began pioneering the ‘Moneyball’ movement, they knew they were on to something. However, they couldn’t have possibly fathomed how universal it would become. As more and more teams place emphasis on stats like WHIP (Walks/Hits per Inning pitched) and OBPS (On-Base Percentage plus Slugging), the need for advanced analytics continues to skyrocket. “Big Data” has deeply embedded itself into baseball, and with exemplary players like Mike Trout cashing in, the importance to unlocking its secrets has become essential. 

At the same time, the social media realm has become one with the professional sports world. With shows like ESPN’s ‘SportsNation’, the art of the clever sports tweet has reach a new high. Combining this with how active sports figures are on social sites like Twitter, fans are starving for a greater social presence from their beloved organizations.

My name is Bryan White and I am an MBA candidate at Radford University. Baseball has always been a passion of mine, having played since the age of 4 until my collegiate career concluded at Milligan College. My playing years have taken me to various college campuses and cities all across the U.S., and I bleed ‘Cincy Red’ March through October. Over the next few weeks, I will be discussing how major league baseball organizations are using advanced marketing analytics and social media interaction to enhance both fan experience at the ballpark and improve on-field quality. Topics that I hope to cover will include team Twitter feeds, corresponding promotional events, advanced data analysis, and how sabermetrics like OBP and player efficiency rating have affected prospect scouting and contract negotiation.

To add to the social media experience, each day I create a post I will be inserting the ‘ baseball stat of the day’ via @MLBStatoftheDay. Thank you for viewing and I hope you enjoy the content that I am able to bring your way!

Drive home safely,

Bryan White, MBA