3 lessons to learn from analytics in sportsThe 2018 NBA Finals are set, pitting the Cleveland Cavaliers against the Golden State Warriors for the fourth year in a row. The Warriors built themselves a superteam to reach the finals, while the Cavs built themselves around a superstar in LeBron James.

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How do you beat a superteam…or a superstar? The Warriors and Cavaliers were both stretched to the limit in the conference final round by the Rockets and Celtics, respectively. Houston and Boston, who both lost in Game 7s, are frontrunners in the NBA’s analytics revolution, where teams use data to try to get the upper hand. Even though the Rockets and the Celtics didn’t reach the NBA Finals, there are still lessons analytics leaders can learn from their success this year.

Analytics in sports

In a sense, the NBA is catching up to Major League Baseball in its use of data. Whenever someone talks about the increased use of analytics in sports, credit is given to the 1990s Oakland A’s. And while those “Moneyball” teams were the first to capture the public’s attention—and certainly the first to make it to the big screen—really what the sports world is doing is just catching up to what’s been happening in the business world for decades.

The data used for analytics might look different, depending on the organization and industry it’s in. But the overall goal is the same—using that data, whether it’s three-point shots made in basketball or number of patients re-admitted to a hospital in healthcare, to help the business succeed. In sports, success means wins. And championships.

Whether it’s the NBA Finals or the World Series, teams are reaching the pinnacle of their sport by applying the same analytics strategies a non-sports entity might use in a different—ahem—arena.

Start at the top and get buy-in from everyone in the organization

The organizations in sports that have most benefitted from analytics are the ones in which everyone is on board, starting at the top. When Theo Epstein took over the Chicago Cubs as president of baseball operations, he targeted and brought in Tampa Bay Rays manager Joe Maddon to lead his team on the field because he knew Maddon was the right man to execute the organization’s plan.

Once the leadership is on board, it’s also a matter of finding the right players. Employing the defensive shift, a favorite strategy of Maddon’s, doesn’t matter unless your pitchers believe it will work and pitch to the right spots. The same is true in the NBA. Houston Rockets General Manager Daryl Morey hired Mike D’Antoni as head coach and brought in James Harden based on the statistics the team dissected. Harden’s abilities matched what the front office believed was the approach the team needed to execute on the court.

Lesson for businesses: a tech department can only go so far without the blessing of a CEO. It’s important that analytics initiatives have buy-in from the very top ranks, and that all the stakeholders are bought into those initiatives and will execute on them.

Defining metrics

It is important in business to know that everyone is looking at the same data and interpreting it in the same way. That’s what’s happening in sports front offices. Teams are assessing tons of data to work their way toward the end result of wins and losses. In the 2017-2018 season, for the second straight year, the Rockets set an NBA record for three-pointers attempted and made. Their analysis stresses high-percentage and high reward shots, so they take the most three pointers in the league—especially from the corner, where the three-point line is closest to the basket. When they’re not shooting threes, they are taking high-percentage layups—a big reason they brought in Harden. They do not take many mid-range jump shots.

What can businesses learn from this? It’s important to define the metrics their organizations will measure themselves on, and then execute on those metrics day in and day out.

Work towards a specific goal

In business you can’t do everything at once, so it’s important to first focus on one goal that analytics can help you achieve. In sports, the one piece of data fans care about is how many wins the team ends up with. The goal, from fans to the front office, is the same – to win a championship. And these days it’s harder to find teams that aren’t heavily relying on analytics to get the job done. The championships—the ultimate ROI, so to speak—don’t come immediately: The Rockets have found their path blocked by the Golden State Warriors, but the team did win ten more games in 2017 – 2018 than in the previous year, finishing with the best regular-season record in the NBA, and advancing one round farther in the playoffs than the year before. In 2016, the Cubs won their first World Series in more than 100 years after spending years building the team they thought had the best chance to succeed based on data…a model culminating in the same result for the Houston Astros in 2017.

Lesson for business leaders: determine a goal at the outset of an analytics initiative. This will help provide structure and a “mission” for analytics that guides every decision.

All that said, sometimes the best strategy is to just make sure you have LeBron James on your team. You can bet the Celtics will spend the off-season crunching the numbers to try to figure out how to stop him.

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John Sucich

John is a writer and guest blogger on the Dimensional Insight blog. He writes articles on topics ranging from sports to education to technology. John graduated from Boston University with a bachelor's degree in broadcast journalism.
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