All of these types of decisions—the hiring of a coach and general manager, free-agency decisions, trade choices—are very complicated and have to be made in concert across an organization. When done correctly, with the Spurs being the most widely held example, they can produce symbiotic beauty and extended excellence, but in the wrong setting, conflicting egos and agendas can quickly rip a franchise apart. As D’Alessandro noted before this Pelicans game, the educated risks the Kings took over his first eighteen months are the type a franchise like Sacramento—far from a premier free-agent destination—needs to pull itself out of a decade-long mire after nearly winning the NBA title in the early 2000s.
“Look, if Rudy Gay is playing in Toronto right now and is a free agent next year, what chance do we have to sign him to a three-year deal, like we just did? We don’t have a chance to do that. We don’t,” D’Alessandro said.
Throw in the club’s decision to offer Cousins—who had struggled with maturity and frustration issues even as he began to emerge as the most gifted center in the league—a five-year maximum extension the year before, and the Kings were running very hot on roster-building gambles. The team’s philosophy on Cousins was simple: you don’t get your hands on talents like him very often, and once management decided to make him the centerpiece of the organization, they had to treat him as such financially instead of asking him to wait and prove he could live up to that kind of deal.
There was risk involved in investing so much money in a young player who had made some mistakes in comportment, but it was a reasonable risk given the potential upside.
“We’re not a big market,” D’Alessandro said about Sacramento’s standing in a league with franchises in Los Angeles, New York, Chicago, Miami, and many other large, desirable cities. “So, [we need to] be willing to seem stupid, because you have to do things that maybe are on the fringe of what other teams can do. And you do them with the idea that [only] some are going to work. Even in the deals I’ve done so far, some have worked, some haven’t.
“As a GM here, I have to be much more willing to say, ‘Don’t be wedded to your ideas.’ [Owner] Vivek [Ranadive] has a saying like, ‘Do you want to be right, or do you want to be successful?’ So be willing to acknowledge that, hey—and I think here, especially, in small markets—you need to be able to work those edges and be willing to be wrong and put yourself out there and say, ‘It’s OK, because the next one, I might be right and it might be a bigger thing.’”
After Ujiri left Denver for a return home to Toronto (and a much bigger paycheck), it was expected by many that D’Alessandro would inherit the general manager role in Denver to carry on the Nuggets’ success. That was even after ownership—which had officially transitioned from Stan Kroenke to his son, Josh, to satisfy NFL cross-ownership requirements involving Kroenke’s St. Louis Rams—had dismissed NBA coach of the year George Karl after a 57-win 2012–13 season that ended prematurely in a first-round playoff loss to the Golden State Warriors.
D’Alessandro admits he was deep in the process to finalize an agreement with the Nuggets, but a deal still hadn’t been reached when Ranadive, who bought the Kings in 2013, repeatedly called to offer D’Alessandro an interview for the open Kings position. Sacramento had been searching for a general manager for a number of weeks, so D’Alessandro didn’t expect the interview to be much more than a chance to continue to grow his own experience set.
In fact, the possible alliance got off to an awkward start when D’Alessandro, who had just finished putting his presentation together around midnight the night before he was set to fly to Sacramento the next morning, got an e-mail from Ranadive detailing what the owner wanted to discuss in the sit-down. D’Alessandro says he pulled an allnighter to assemble the new materials, got an hour of sleep, and flew out to meet with Ranadive, where the two had a very open exchange of ideas and questions about how to rebuild the Kings. D’Alessandro walked out of the meeting feeling like he wasn’t going to get the job, since Sacramento was so far along in its own process, but that he told his wife that he “had a friend here. I know that, because the guy’s a great dude.”
Soon after, D’Alessandro was hired to help lead the Kings’ revolution, which continues to include unique and sometimes offbeat concepts about how to improve the team. The example that got the most media attention (and ridicule) during 2014–15 was Ranadive’s public admission that he wanted the team to consider a four-on-five defensive strategy with a basket-hanger who would remain at the offensive end of the floor. Most NBA observers believe this approach would get shredded in the long run as teams countered defensively and exploited the greater space of four-on-four basketball at their offensive end, but to D’Alessandro, the ideas weren’t the thing in Sacramento. It was the process of discovering them.
“I think Vivek has had a really open approach, an approach that—and I do this in my office, too—anyone in the office, all the young guys running around, can walk in my door and say, ‘I have an idea’ and throw it at me,” he said. “Anytime. I don’t care if you work at the front desk. And everyone knows that. It’s funny to me, you find that personalities start to shine that way. I find that you start to see things in people that maybe you didn’t envision before.
“Because ideas are where it all starts, and so I think Vivek is an incredible ideas guy,” D’Alessandro added. “He comes up with these ideas, and they blow me away every time. We’re just having a meeting, and Vivek’s going to come in, we’re going to be doing some stuff that we’re going to send to the league, and I told someone, ‘Have a notepad, write down everything he says,’ because when he says it, sometimes, I’m like, ‘Oh c’mon.’ And then I’ll go back and think about some of the stuff he said and like, you know, there’s a germ of an idea that you can turn into something big.”
The Kings continued to push resources into better and more creative decision making with the fall 2014 hiring of Dean Oliver, the father of the modern analytics movement, from his role as director of production analytics at ESPN. Ranadive, like a number of new NBA owners, made his fortune in technology, so the work of Oliver and his charges were to be a rapidly increasing portion of what the Kings considered as they weighed their next risk/reward decisions, and the whole management team, including more-traditional advisors like former NBA star Chris Mullin, were to become more aligned philosophically.
“We’re in our infancy, we’re in year one, we can’t have it all done, and Dean just came on,” D’Alessandro said at the time. “I think we’ll have a fast infancy because I think we have really qualified people, and I think we have an incredible support cast in our ownership group. So in that regard, I feel really good about where we’re positioned.
“But, in the way I’m looking at it, there’s so much of it that we have already, the question is: How do you use it? And how does each area use it? And I think, as the general manager, I’m trying to figure out how to create the most flexible way of having [the data] tell its story.”
Unfortunately for D’Alessandro, and perhaps the Kings, the story would quickly take a very different turn.
What seemed like a solid plan that was being implemented well started to unravel a couple of weeks after this conversation. What exactly went down over the next six months isn’t 100 percent known, but the craziness started when the team elected to dismiss Malone in late November, during a period when Cousins was out of the lineup with viral meningitis. There was much debate at the time about whether management favored a faster tempo than what Malone was playing with a roster designed for more of a halfcourt approach, and local and national media differed on whether D’Alessandro or Ranadive himself was responsible for the move.
Subsequently, the Kings promoted assistant coach Ty Corbin to interim head coach, may or may not have asked Mullin to take over as coach, elected to make Corbin the coach for the rest of the season, kept losing games and looked terrible in the process, were forced to remove Corbin from the job, and eventually hired Karl, with whom D’Alessandro had worke
d in Denver.
None of it really made any sense, and it all became more confusing when Ranadive brought back former Kings center Vlade Divac in a front-office role and then quickly handed the basketball operations over to him without telling anyone else. Mullin quickly left the Kings to take the head coaching job at St. John’s, his alma mater, and D’Alessandro, having been neutered, quietly returned to Denver after the season to take a business and team operations role under owner Josh Kroenke. In late July 2015, it was reported that the Kings would be releasing Oliver, while also looking for a new analytics person to replace him. They did well to land Roland Beech, but it still was very curious.
The whole Kings saga is a cautionary tale of mismanagement, but there was a lot going into the buildup of the analytics approach that was worthwhile. All of the decisions they made—swapping out Thomas for Collison, gambling on Gay, maxing out Cousins, the debate over tempo, and so forth—were rooted in analytics as part of a team-building plan. Maybe Divac and his staff will find a method that works—and they need to quickly, because they (perhaps recklessly) invested a lot of the Kings’ future in some third-tier free agents for the 2015–16 season—but there clearly was a breakdown in the process with the old regime.
Sacramento’s journey to wonk and back is illustrative in an exploration of how analytics move through an organization, and how many things can derail them. The next section provides some additional perspectives, from different layers involved in this kind of decision making and implementation.
With the deluge of on- and off-court data now available, basketball data analysis is rapidly becoming, as Daryl Morey has suggested at the Sloan Sports Analytics Conference he co-chairs, “only constricted by money, time, and the questions you ask.” The bigger challenge for every NBA team lies in how to value, disseminate, and use the information they can generate.
Information-gathering and -sharing structures for NBA teams differ wildly, but at a baseline, the operations are very complicated and nuanced. The possible data pieces a team can gather include in-game data from SportVU, in-game proprietary data being tracked by staffers, in-game/trend data from Synergy, practice data coming from Catapult or other wearable technology devices, practice data being tracked by staffers (the 76ers, notably, track every shot, including free throws, taken in practices), medical data, sleep data, salary and cap data, college and international scouting data, NBA pro personnel data, and advance scouting data.
All of that different data can be parsed in an enormous number of ways, and there are different constituents for each kind of data, all of whom consume and subsequently communicate findings to other constituents in very different ways. Sometimes, a report immediately finds its end user. Sometimes, the initial reader is a conduit to the eventual end users. Some people want very complicated, nuanced answers. Some need very simple ones. The possibilities of how and what to do with the data being collected by NBA teams are effectively endless, and the communication network has to be tailored to the wants and capacities of the target users. To make it more complex, team management often is hiring data staffers whose expertise stretch well beyond the hirers’, making ongoing evaluation of the data team’s work all that much more difficult.
As a quick example of how complicated one single decision can be, take an instance of the work of Ben Alamar. Alamar is a former professor of sports management at Menlo College in California who rose to prominence in the sports analytics world thanks to seven years of NBA work, first as the director of analytics with the Seattle SuperSonics/Oklahoma City Thunder and then later as a consultant with the Cleveland Cavaliers. In his 2013 book Sports Analytics: A Guide for Coaches, Managers and Other Decision Makers, Alamar discusses the process he undertook in 2008 to try to help the Super-Sonics (who were moving to Oklahoma City that summer) evaluate UCLA guard prospect Russell Westbrook, who was entering the draft after two seasons of college ball.
Westbrook was a tricky draft case because he mostly played shooting guard at UCLA (with the Kings’ Collison playing the point for those Bruins teams), but the Thunder wanted a point guard with their No. 4 overall pick to go with star-in-the-making Kevin Durant, who had just finished his rookie season. The team loved Westbrook’s physical attributes and mental makeup, but wasn’t sure he would transition to the NBA level as a primary ballhandler or distributor.
As such, the team needed a way to try to measure Westbrook’s passing acumen in college, and then project that to the NBA level. Standard statistics (like assists) were not going to provide the team with enough information to judge Westbrook’s decision making, so they needed to do some proprietary work to evaluate him more appropriately.
Alamar, through extensive film work, created a metric that looked at UCLA’s shooting percentages when Westbrook passed a teammate the ball versus shots that came unassisted or when other teammates made the pass that led to a shot. Alamar found that Westbrook’s impact on UCLA’s shooting was greater than the team’s point guard, Collison (who would be picked twenty-first overall in the 2009 NBA Draft), and stacked up favorably against both the performance of other prospects in the 2008 draft and a pool of established NBA point guards.
Once Alamar had data he was comfortable with, the challenge became communicating this new metric and what it meant to the decision makers in charge of the draft. It was enormously helpful to be able to show that Westbrook’s impact at UCLA was comparable (adjusted for context) to that of elite NBA point guards, as well as a projected elite point guard (University of Memphis’ Derrick Rose, who would be the number one overall pick in 2008). Also, being able to show that lesser NBA point guards scored worse on this metric than both the best NBA point guards and Westbrook also helped slot Westbrook higher in the minds of the brass.
Alamar wasn’t even in the team’s draft war room when they selected Westbrook, and Alamar’s analysis wasn’t (by a long shot) the only factor that encouraged the team to select him, but that didn’t stop a team official from emerging from the room after the pick had been made and yelling at Alamar, “You got your guy!” The pick has worked out brilliantly for the Thunder. Westbrook turned into an All-Star by his third season in the league, and made second-team All-NBA in the 2014–15 season. He’s not a conventional point guard by any means, but while being one of the most physically dominant and destructive perimeter players in the world, he also led the NBA in 2014–15 in percentage of teammates’ baskets assisted while he’s on the floor at an astounding 47 percent.
The above described one part of the work that went into the evaluation of one potential draft prospect, so you can see how expansive this can get. An analytics team needs to find the right balance between pushing information to the different end users, pulling information requested by those users, and communicating it in varying ways such that each end user will be as receptive as possible to the conclusions drawn.
“I think analytics is best when it works in concert with everybody,” said Alamar, who now is ESPN’s director of production analytics, having taken over the job from Oliver. “And we ask a lot of questions to find out what people are really interested in. And when people are actually asking us questions, that’s great because that provides us ways to demonstrate the value and know that our audience is going to be listening when we deliver something. What is difficult is when we know the answer that they’re looking for, and the answer that we come up with is different. That can be challenging. But in general, I think a process that works with and in conjunction with all our audiences—as opposed to us just doling out the data—is a better, more effective model.”
Per Alamar, the two main goals of an analytics group are to provide new and/or actionable information, and to save time for decision makers. As good as a data team can be in managing and exploring data to solve team questions, though, the effectiveness of the operation is judged heavily by its ability to communicate the findings to audiences that will range from completely open-minded to those looking for validation of their gut. Alamar provides a simple but f
airly common example in today’s NBA.
“Well, when a coach comes to you and says, ‘I think our problem is X, can you show me data that supports that, so I can show it to the player?’ It’s tough, particularly when that coach is new and you’ve worked with him for a couple of weeks, to come back and say, ‘Coach, no, actually you’re wrong,’ Alamar said. “If it’s not delivered well and it’s not delivered carefully, that’s a message that, ‘Oh, this guy doesn’t know what he’s talking about. I’ve been in the league for twenty years, I know that this is the problem. He’s just either dumb or he’s not very good at his job or he couldn’t deliver what I wanted.’ And so that’s a problem. Now, for the analytics person to find a way to support the coach’s answer, you don’t want to do that either because then you’re giving people the wrong information. So in the end, what you have to do is be really careful about how you present the information.”
Some current team analytics staffers echo Alamar’s sentiments. Alex Rucker started leading analytics for the Toronto Raptors in 2009, and his group developed one of the seminal analytics concepts that has made it to the public realm. In 2013, Grantland’s Zach Lowe detailed the group’s “ghost defenders” visual model which showed, in animated form, where Raptors defenders ideally would be on a play as the actual offensive and defensive players (and the ball) were shown moving around the court. While the model may have been more high-concept art than something that was highly implementable for human players, there were some interesting takeaways from the computer-generated data, including the suggestion that defending teams should double-team the ball way more often and more aggressively than they currently do.
Chasing Perfection: A Behind-the-Scenes Look at the High-Stakes Game of Creating an NBA Champion Page 14
