Basketball Analytics
It’s more complex than you think
From 2013 to 2016, the Philadelphia 76ers had an overall record of 47 wins and 199 losses. The franchise looked as though it was drowning, and the fans lamented that their hometown had become the butt of the jokes on ESPN. But general manager Sam Hinkie had different plans for the Sixers.
How analytics is changing the NBA
Basketball analytics are rejected at the collegiate level and the professional level by many. How can you possibly use algorithms to improve a basketball team?
When analytics propelled the Golden State Warriors and the Cleveland Cavaliers to the most-watched NBA Finals since the age of Michael Jordan, people started paying attention. “The most-watched Finals since the age of Michael Jordan ended with victory for the Golden State Warriors over the Cleveland Cavaliers,” Stated Terrance Ross, reporter at The Atlantic, “both of which are teams that have heavily incorporated data analysis into how they play the game.” The huge accomplishment of using analytics to propel both teams to the NBA finals was eye opening to those who doubted basketball analytics.
But have you ever watched a basketball game on your television and seen statistics depicted in the picture above? These short informational pop-ups occur many times over the course of one televised game, and I always found the information intriguing. Behind each of the three second pop-ups is a complex plethora of information that goes into gathering the results as shown above.
In the NBA today, each team uses roughly five highly complicated cameras during their game to keep track of every player’s movements and statistics. Once each camera has recorded the necessary data, it creates a visual, as shown above, and statistics of each player. As stated by Zach Lowe, reporter at Grantland- a website that is mostly devoted to sports, “Fifteen NBA teams have purchased the cameras, which cost about $100,000 per year.” NBA teams understand the importance of analytics and are willing to spend the money to insure they win more games. But you don’t need expensive equipment to do analytics.
College Basketball Analytics
The data analysis procedure is simplified, and much cheaper at the college level. Colleges would rather use analysis as a way of understanding results of the game, while the NBA prioritizes analysis.
Gathering basketball analytics is more than a person counting a player’s assists and points, yet, the process does start there. I recently interview Danny O’Connor, who is one of my coaches at the University of Delaware. I asked him about the steps it takes to get to the data analysis they are trying to accomplish.
During our scrimmages he uses an excel template to calculate efficiency points, or the total calculated score of a player’s individual statistics. He plugs in a variety of data points like assists, turnovers, points, and rebounds, and from there each player gets their efficiency score, The higher the number, the better the player did. This process changes during games though.
“The person that keeps track of the boxscore and the person that records events in the book give the information to our sports information director,” O’Connor stated, “and from there we get play-by-play results and a sheet of total percentages and rates of each player and the team.”
Not only do the coaches review the results of our team after we play, but they also review how the other team did as well to understand why the game resulted as a win or loss. I asked Coach O’Connor, “Just how important is data analysis?”
“Basketball analysis is important to help support an answer, but it is very difficult to just look at a statistic and make an assumption about the result of a game. Rather, it is more beneficial to help prove theories that the coaches have during the game using data analysis.”
In other words, college coaches use statistics as a way of figuring out why things happened the way they did. An example of this is defensive efficiency. The University of Delaware basketball coaches use a four point scale to determine each defensive possession and then average all of the possessions together. Four is a three point shot, and one is a non-contested lay-up.
“If we average above a two we most likely win games,” O’Connor emphasized, “however, if we face a team that is efficient at the three-point range, then the data may look good, but the result might be different than expected.”
After all, collegiate programs use basketball analytics as a way to recap what happened, the NBA utilizes it in a much different way.
Why go through all the trouble?
It seems like a lot of work to gather statistics. However, it is essential because the way NBA basketball is thought about and played is changing, and breakthroughs in analytical processes are the catalyzers. During the 2013 season, every NBA team used, or started to use, some level of data analysis. Since the examples of franchises depending on analytics to help their team have been countless.
Terrance Ross explained:
“The Houston Rockets — led by general manager and analytics buff Daryl Morey — are renowned for their use of data. The team rarely shoots long-range two-point jumpshots, as they believe it to be one of the worst strategies in basketball. And their reasoning makes sense: The shots are too far away from the rim to be rendered a high-probability scoring opportunity, yet not far enough — as in behind the three-point line — for the risk to be rewarded with an extra point.”
The Houston Rockets, in other words, found a system that they thought would help them win games. In turn, they put all their dice into the system and got a great reward out of it; Nevertheless, some other teams did not listen to the analytics and had to pay the price. A lot of the analytics discusses the importance of the three point shot. It is so important that data analysis fanatics point to the 2017 NBA finals: the last five finalists were also the top five best three point shooting teams during the season. In the same article, Ross emphasized:
Los Angeles Lakers head coach Byron Scott, said that he would be eliminating a reliance on three pointers from the Lakers’ strategy. It was a move rightly condemned at the time as archaic — perhaps proven by the fact that the Lakers went on to finish this campaign with the worst record in franchise history… On the flip side, the 2015 Championship-winning Warriors were the league’s best three-point shooting team during the regular season. It’s almost impossible to disregard the success and importance of the three-point shot today.
Ignoring data analysis, somewhat like the Lakers did, creates a bad result. Moreover, if you use analytics correctly, great things happen. If you don’t believe me, believe the 76ers.
You may frequently hear Philadelphia 76ers fans, including myself, yell, “TRUST THE PROCESS,” but I never knew that the obnoxious chant originated because of Hinkie and his vision for how the Sixers would utilize data analysis. He Traded Jrue Holiday, the team’s superstar, to acquire draft picks that he thought would fit the analytic mold he wanted, and as time went on his methods stayed the same. Looking at the present year, the 76ers got the first pick in the draft and now has a young, yet potentially powerful, team that seems almost perfect. Although Hinkie was recently fired, he is credited with flipping the franchise around. It took several years, but Sixers fans trusted the process of analytics and are now loving the outcome.