Until relatively recently, the success of professional sports teams was the product of a good ownership group, management team, coaching staff and heavy financial backing. Big money teams in big time markets such as New York, Los Angeles and Chicago dominated professional sports across the board. The winning traditions of the Yankees, Lakers and Bulls are all well documented. If these proud franchises have such a strong history of winning, why are teams such as the Kansas City Royals, Houston Astros, Golden State Warriors and the Cleveland Cavaliers dominating the so-called traditional super powers? A lot of it has to do with good fortunes in the NBA draft lottery, hometown players returning home (LeBron James), and the strict salary caps in most American professional sports. Although it isn’t the sole factor, the emerging role of analytics is helping to level the playing field.
One of the first and most documented instances in which analytics was used in sports was with the Oakland Athletics of Major League Baseball in the early 2000’s. Many know the story of manager Billy Bean getting rid of all the so called superstars on the team in favor of average “journeymen” type players, which was documented in the movie “Moneyball” starring Brad Pitt and Jonah Hill. These decisions had many around baseball scratching their heads. That was until the season started. They famously won 20 straight games during that season which saw them win the AL West by four games over the Anaheim Angels, before ultimately losing in the ALDS to the Minnesota Twins.
Many different teams have tried to mimic the philosophies of the Oakland A’s of 2001 and have produced mixed results. Statisticians mull over numbers day and night looking at things such as on-base percentage and wins above replacement. In basketball, another sport in which statistical analytics is relied upon heavily, they use stats such as shooting percentage and player efficiency rating(PER) to judge players. Different teams use these stats to try to figure out which players are worth their high price tags or which players may be a steal at their current price.
No league in professional sports has became more obsessed with statistical analytics than the NBA. Every movement of every player is tracked with six different cameras in the catwalks of each arena in order to measure things such as distance traveled, speed, separation from opponents and time on the ball. They call this “player tracking” and it has a large influence on how teams draft, sign free agents, and make trades.
The amount of statistical data on any given player can be overwhelming. What has been seen to set certain teams apart from the rest is their ability to select which data has the highest correlation to success on the field or on the court. A team like the Atlanta Hawks come to mind as a team that like the Oakland A’s, had little expected of them coming into the 2014-15 season, and shocked the basketball world by being the number one seed in the Eastern Conference. They fell short of their goal of an NBA Championship, but along the way they widened the eyes of the already attuned stat geeks of the NBA.
Statistical Analytics has been around for decades in the business world, but businesses are still looking at how sports teams use it to try and better apply it. Many successful analytic sport franchises have had three main things in common, aligned goals and understanding throughout leadership, a focus on the human dimension of decision making, and the exploitation of video and locational data. Now, the last point is tougher to translate to the business world but the first two are important to all aspects of decision making. Maximization of outcomes is a common goal of almost all firms. If everyone is not on board and giving full effort to a cause, then the maximum outcome will likely not be reached. The human dimension cannot be taken out of the equation no matter what you are dealing with. Humans make mistakes and do things that are sometimes unexplainable. Learning to handle the human element efficiently is crucial in todays environment.
Not just those in the realm of sports are jumping on the statistical analytic bandwagon. Gone are the days of trusting your gut and hoping for the best. In todays world, you need to be able to back it up with facts, and in this case data. Drawing upon lessons learned by sports teams has become a more common way of doing things here in the twenty-first century.