statistical analysis in baseball

Why Was Moneyball Such a Big Deal?

Michael Lewis’s hit book Moneyball gave readers an inside look to the Oakland Athletics front office operations when they began using revolutionary strategies to field their team. Prior to the 2002 MLB season the A’s had the third lowest total salary total in a league where perennial winners paid players, who were perceived to be better, top dollar in order to foster success.

Using Statistics in Baseball

The executives in the A’s organization knew it would be impossible to increase their budget as a way to become competitive, so they looked to alternative methods. General manager Billy Beane and his assistants like Paul DePodesta began using more meticulous statistical analysis to find value in players that the rest of the league overlooked. Inspired by the works of Bill James and the Society of American Baseball Research, the A’s were able to find statistics used to evaluate players that were overvalued, such as stolen bases and runs batted in, and those that were better predictors of success, like on-base percentage.

At the core of the A’s innovations was the simple idea of finding undervalued assets using statistical analysis. Whether this involved acquiring players that were older or those who had injury problems in the past, the A’s attempted to reverse conventional baseball thinking using statistics.

Moneyball highlighted this process and brought the idea of using math in sports into mainstream thinking. With the success of Lewis’s book, many people found a new way to get involved in sports. Gone were the days of sports being restricted to only those who were athletic anomalies, and in with more statistical based decision making across the board.

Gaining an Advantage

Moneyball brought data analytics to the forefront of the sports world and allowed small market teams to gain competitive advantages in an unfair system. Shortly after the work done inside the A’s organization, other teams such as the New York Yankees and Boston Red Sox hired data analysts, and now teams dedicate entire departments to statistical research. Additionally, Paul DePodesta, who helped begin the movement in Oakland, now applies the same strategy in football as the chief strategy officer for the Cleveland Browns.

Before Moneyball, there were still avid fans who obsessed over numbers and made their own calculations, but after their work became known to the public, everyone in the industry had to accommodate a new type of fan.

Entertainment companies had to supply the public with new advanced stats, and began employing more and more data analysts to do so. This expansion also began to open a new frontier for private companies to collect data and consult with teams to provide an edge. With the advent of statistics everywhere in sports, almost every job in the industry leverages data on a daily basis. From agents using statistics to earn their clients better contracts, to managers deciding who to start each game; all decisions in sports rely on data.

The influence of Moneyball on the public is extremely evident in the case of the MIT Sloan Sports Analytics Conference. Since its creation over a decade ago, the conference has done nothing but grow and is now heralded as the premiere gathering for sports data. The three thousand attendees, thousands on a waitlist, and the recent partnership with ESPN, all show the profound affect that Moneyball had on the industry, and the tremendous influx of data science in sports.

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