Data Analytics: How Billy Beane Transformed the Sports Scene Forever
Every person in sports has one thing in common: they want to win. For years, winning was determined by ownership, front offices, and coaching. Their decisions regarding which players to draft, trade, develop, and coach had a significant impact on the outlook of the franchise. Then, in 2003, everything changed.
Oakland Athletics’ General Manager, former player Billy Beane revolutionized the world of sports forever. Beane used sabermetrics to discover the secret to success in baseball and improve the often imperfect science of sports. This was the first known use of the prioritization of statistics and data to make personnel decisions in professional sports. Beane’s thought process was simple. He theorized that a team with a high on-base percentage was a team more likely to score runs and, as a result, more likely to win more games. Beane built his team around that central tendency and helped the Athletics find success. Ever since Beane’s introduction, sports analytics has not only revolutionized baseball’s modern era but professional sports as a whole.
Today, every major professional sports team has at least one analytic expert, most frequently supported by an entire analytics department. The current sports analytics market has an evaluated net worth of $774.6 million, a small price in comparison to its expected growth. Due to analytics’ profound impact on baseball, basketball, football, soccer, and most other sports, the market is expected to grow at an astronomical compound annual growth rate of 31.2% by 2025, increasing its worth to well over four and a half-billion dollars.
This exponential growth is a result of the competitive advantage that analytics provides a team. Mathematicians record hundreds of categories of stats on each individual player, crunching those numbers in order to provide an overall assessment of the athlete’s compatibility with the team and help make the work of scouts and general managers easier. Analysts create an overall profile of a player to determine if that player is worth drafting, signing, trading for, or even cutting.
The increased popularity of data analytics has even trickled its way down to the fans. Websites like FiveThirtyEight have over 20 journalists counting and crunching numbers for fans to gain a better understanding of an upcoming game, series, or season. Additionally, they track and project player performances as well as overall win-loss records and game results. The increased accessibility that these websites provide to fans has certainly contributed to the rampant run analytics has taken throughout athletics.
Basketball has also been heavily impacted by the widespread use of data analytics. National Basketball Association (NBA) teams now use a form of a technology called “Player Tracking” which evaluates the efficiency of a team by analyzing individual player movement, on and off the ball. Each team now uses six cameras, installed in the catwalks of arenas, to track the movements of every player on the court and the basketball 25 times per second. This data provides a plethora of statistics on speed, distance, player separation, and ball possession. However, the way in which the data is used, determines how effective it can be. The sheer volume of data that is currently collected makes decision-making difficult for NBA franchises and results in some teams better utilizing their data than others.
Besides helping teams win, data analytics also drives customer engagement. Teams are running data-driven campaigns to understand what and when fans are watching, via app logins and online video views, in order to maximize their fan engagement. Additionally, this data is used in order to improve the in-stadium gameday experience, concession sales, improve parking lot congestion, and increase the front and back-office intelligence and overall understanding of their athletes and fanbase.
Most recently, data analytics has made its way into the National Football League (NFL) in a fascinating manner. Harvard University senior Ella Papanek is a research and strategy intern who assisted with Cleveland Brown’s analytical preparation for its 2021 AFC wild-card game versus the Pittsburgh Steelers. The NFL has quickly become a data-hungry league with websites like Pro Football Focus and Pro Football Reference popularizing the globalization of analytics. Papanek developed a player projection model for Cleveland’s analytics team to assess and plan for the upcoming game accordingly. Papanek is indicative of the ever-expanding market of data analytics and the countless job opportunities developing in the field.
While Billy Beane thought he was just going to turn around an abysmal Oakland Athletics team, he instead revolutionized sports forever. Data analytics has become an integral part of all major sports and provides coaches, general managers, and other stakeholders with a competitive advantage in predicting outcomes and assessing individual player performances. Professional sports have just recently scratched the surface of data analytics and the opportunities and benefits that will one day amount from it are endless.