The Ball is in Your Court Now — The Use of Analytics in Basketball
Written By — Shreyas Ramani
Former CEO of Google, Eric Schmidt once said, “There were 5 Exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days.” There is controversy surrounding this quote as most people speculate that the exact statistics of the data is wrong. Nevertheless, it is true that we have a remarkable amount of data in our hands. This data can be retrieved and processed by various calculations and algorithms, and this is done by analysts.
Companies hire analysts for a variety of reasons, from conducting market research to improving the performance of multiple products, to managing the organization’s finances etcetera. However, data brings change to much more than just the commercial side of our lives. The amount of information that companies have about who and what we are as social units is so vast that it reshapes the very fabric of our societies.
Take outdoor sports for example. The criteria that determines the winner is assumed to be talent, hard work, physical and mental toughness, and intelligence on the playing field. But over the years, sports has become a booming business where billions of dollars are spent yearly. Organizations are willing to do whatever it takes to make their teams win championships. And thus, most large sports organizations today have an analytics department, scrutinizing every minute detail to give their teams a better chance at winning.
Consider the sport of basketball. Base level statistics have always existed, and as the field of statistics advanced, we have been able to theoretically calculate anything we have wanted to. There is a criteria called ‘+/-’ which numerically gives us the impact of a player when he is on the court versus when he’s not. We even have the statistics of how many miles a player has run in a particular game. With this data, analysts find out what type of offence and defense best suits their team.
Moneyball, a concept first introduced in baseball where organizations use math and logic to win games is not new to sports. But in basketball, it was the General Manager of Houston Rockets, Daryl Morey, who popularized the analytics movement in the game. A data analyst himself, Morey’s most fundamental insight involved taking an increased number of three-point shots. Three-pointers in basketball are more difficult because they are made further away from the basket. Morey recognized that the 50% uplift in points received for the three-point shot (compared to a two-point shot) made it more mathematically efficient than almost all two-point shots, other than dunks and lay-ups. Over the last five years, the Rockets have taken 88% of their field goals either in the paint area or beyond the three-point line, almost completely eliminating the mid-range shot.
A basketball team that used analytics a bit differently, however, were the Philadelphia 76ers. Philadelphia 76ers hired a man named Sam Hinkie as their General Manager, who used analytics to reconstruct the entire organization. The 76ers owners and fans had seen a lot of good players in the team, but it had been a long while since they had won a championship, which was now Hinkie’s goal. While the 76ers were a decent team at the time, they were nowhere near to being identified as a championship team. Hinkie took the dataset of every single NBA championship team since the birth of the NBA and found a common theme. To win a championship, an organization needs ‘star players’, more precisely top ten players in the league. There are a few exceptions to this but the vast majority of the time, championship teams have at least one or more top 10 players. There are three ways to obtain a Star Player; through free agency, through trade, and through a draft. The first two options posed problems; hence it was down to the draft. To obtain a player with star potential through a draft, the team must have a higher pick, and to get that pick, the team needs to have a lower seed in the previous season. Thus, Hinkie wanted to trade the team’s best players for multiple draft picks, and planned to tank for numerous seasons to get high draft picks.
In the first year of ‘the process’, since the Sixers had traded all their experienced players, they were pretty terrible in the 2013–2014 season which landed them the third pick in the 2014 draft and with that college sensation Joel Embiid was picked, despite his injury at the time. Normally teams consider it risky to pick an injury-prone prospect but since the Sixers planned to tank for multiple seasons, they didn’t mind waiting for Embiid to recover. Embiid missed the first two seasons of his career due to injuries and only played 30 games in his third, but the wait was worth it as he turned out to be one of the best centers in the game till date. But the wait also meant that between the years 2013–2016, the Sixers had terrible teams which led to the team losing a lot of games, very low fan attendance and lot of losses. And thus on April 6 2016, Hinkie was fired by the owners of the Sixers.
Embiid has always supported Hinkie and blames himself for Hinkie’s firing, so he nicknamed himself ‘the process’.
A lot of controversy surrounded Hinkie’s move. The league called this move unsportsmanlike, and the Sixers incurred financial losses due to bad games, not to mention the decrease in fan attendance. Despite Hinkie eventually losing his job, according to many, he put the team in the best position to succeed. As of the publishing of this article, the Sixers haven’t won a single championship since Hinkie’s firing but they are in a good position to compete for the same right now.
However, while both the Rockets and the Sixers have had regular season successes, both teams are yet to make the NBA finals. Many veteran managers and coaches are thus against the use of analytics in the game, and state that to win basketball games, talent and hard work beats any kind of advanced planning. But that’s where they’re wrong, because progress in any fashion is still progress, and when the ball is in the court, any kind of analytics helps, and the longer payoff might just be worth the wait.
