Like every other analytics staffer contacted, Rucker is not permitted to discuss specifics about his team or any of their players, but he faces many of the same challenges detailed above in terms of trying to find the right balance in the questions his group is trying to solve, and then how to disseminate that information in the most optimal way.
“On the one hand, I think the analytics—the technical guys—they have a push responsibility to go through the data and find out . . . for themselves, to use their basketball knowledge, use the data set to gain some insights to some aspect of the game, and then hopefully push that to whoever is their more immediate consumer, which is usually the front office, the executive management level,” he said.
“But, at the other end, you do have kind of an end user, you do have a consumer, you do have somebody who is wanting something from this analytics thing, if you will. . . . [T]hey’re the ones paying for it, they’re the ones asking for things, and quite honestly, they do ask for specific things. ‘I want to know this.’ So, on our level, can we give you an answer to that, and if so, go about doing it? And at some level, it’s prioritizing between what they want to know and what you think is important to push, and just kind of finding a balance between those two things.”
Dean Oliver adds: “Any place I’ve been, I’ve tried to make sure that the communication, the translation between the words and the numbers—the basketball language—is clear, because you can do the greatest analysis behind the scenes, and if you can’t put it into basketball language, then it’s not going to get implemented right, even if they want to understand.”
But even when you do have end product that is framed in a way that can be used by the basketball side of the operation, that doesn’t mean that the information will be used. There are tons of limitations—even in the current data-intensive world of basketball—in the output an analytics team can generate on a regular basis. When you then factor in that merely a small percentage of that work likely even gets fully considered, let alone implemented, it’s difficult to pinpoint the specific value of analytics operations, even though every NBA team is investing in them to some degree.
As Rucker notes, there’s a difficult balance between maintaining the academic rigor of statistical exercises—which includes understanding and accepting the inherent uncertainty in most calculations involving such a dynamic sport played by humans with imperfect decision making—and expressing enough confidence and certainty in your conclusions that they will be taken seriously by the basketball part of the operation.
“That’s an extraordinarily difficult balance to strike between being intellectually honest and truthful, which is saying, ‘Hey, this stuff I’m talking about has all sorts of limitations and disclaimers and caveats’—the academic side, if you will.” Rucker said. “As a data scientist, if I’m going to be any good, [I have to be] astutely aware of the limitations in my data and the errors that come with anything I create.
“But you’re dealing with people that don’t function in academia, that don’t live in that world, so you can’t very well offer everything with error terms and uncertainties and risk. I think that you have to—to me, I guess the right balance is to continuously openly acknowledge that there are limitations. This is not gospel, this is not truth, this is hopefully we’re turning a flashlight onto a part of the table that we haven’t looked at before, and hopefully offering some insight, but that might not be, we might not be seeing what we think we’re seeing.”
And even when the information is good, and is presented well, and is well received by the decision makers, that’s far from the only information being considered when a team makes any choice, whether it be on game strategy, pro player evaluation, the college draft, or trades.
“It’s really up to the coach or the general manager to distill all the information, because they’re getting information from all different sides, all different types of information,” Alamar said. “They have the really, really hard job of figuring out what’s the best set of information to use and how to utilize it. And so that’s difficult, because we’re right more than we’re wrong, but we’re wrong sometimes, and if a coach or general manager is really good at what they do, and is honestly weighing all of the information and working through it, they may choose not to do it.
“Not because there’s a breakdown, but because they see other information that is counter to what we see as more compelling to them. The trick is to make sure that they’re honestly weighing all the information. And you get them to a place where they will take what you’re saying seriously and think about it carefully. As long as they’re doing that, then that’s all in basketball I think you can honestly ask for.”
And then, again, there is the human element in all of this. It’s entirely possible that a coaching strategy choice is correct, but a player blows an assignment and the play unravels. It’s possible that you can make the proper pick in the draft, but a series of external factors influence the player in a way that was unpredictable at the time. Rucker takes that uncertainty one step further, noting that it’s often difficult to isolate when analytics are even being applied by coaches, management, and players.
“If I give my wife a recommendation for a car, she goes to the car lot and inspects a bunch of different cars, and buys the one I recommended—I have no idea why she bought it,” Rucker said. “I can ask, but until that conversation takes place, I have no clue what kind of decision chain occurred there. Whether it’s my commanding and compelling recommendation, or whether . . . she did her own investigation, talked to some people, looked online, test drove the model, and it was the best one for her, it turns out.
“I guess it’s a similar decision for us . . . on the basketball court. Like, I know all the things I recommended, but when they occur on the court, does that mean [it was] because of me? I seriously doubt it. I think that it was a small piece, and maybe a helpful piece, but I also don’t know . . . in the absence of that recommendation, does it happen anyway? Possibly.”
Five years ago, Brad Stevens was the boy wonder of college basketball head coaches, having led unfancied Butler University to the national title game in both 2010 and 2011 while not looking very much older than any of his Bulldogs players. Stevens had long been rumored as the possible savior at Indiana University, his home state’s flagship program, and there even were some rumblings about him being a possible candidate to replace Hall of Famer Mike Krzyzewski at Duke whenever he finished there, so it wasn’t totally shocking when the Boston Celtics poached him in the summer of 2013 to lead their rebuilding process. Former head coach Doc Rivers had pushed his way to the Los Angeles Clippers in the wake of multiple trades that left the Celtics’ roster short on talent but long on future draft picks and cap flexibility, and the Celtics were excited about how much the young and extremely bright Stevens could bring to the table coaching a young and transitioning team.
It’s hard to overstate how well Stevens did at Butler, even after taking over a successful program that had grown under the command of Thad Matta (now the highly successful coach at Ohio State) and then Todd Lickliter (who left for Iowa, but didn’t last long there). In his six seasons in charge of the Bulldogs, Stevens went 166–49, never won fewer than twenty-two games in a season, and made five NCAA tournament trips, including the shocking back-to-back title-game trips with squads led by Gordon Hayward (now a blossoming star with the Utah Jazz, who was a lottery pick after leading the 2010 team) and Shelvin Mack (a guard with the Atlanta Hawks).
While Stevens’s coaching reputation blossomed thanks to all of the success he had at Butler, he also was one of the earliest adopters of advanced stats on the college level. While at the school, he hired Drew Cannon, a former intern of Dave Telep (now the scouting director for the San Antonio Spurs after being a long-time scouting analyst for high school players), who had been combining traditional scouting with analytical slant in written work. The move was the first strictly analytics hire at the Division I level, and helped cement Stev
ens’s reputation as a creative thinker in addition to being an excellent strategist and program CEO.
When Stevens was hired by Boston, he elected to bring along Cannon, who was just a year removed from graduating from Duke University. When the move was announced, Stevens told the Boston Globe that “what Drew has a great ability to do is not only to analyze but communicate it. He can break things down into the simplest terms. He’s got a sense for the basketball side of things and he’s a good communicator to me with it.” Since then, the two have combined with general manager Danny Ainge, vice president Mike Zarren, and director of basketball analytics David Sparks to form one of the most respected and cohesive analytics staffs in the NBA.
With Stevens still working through the transition into the pro game and the Celtics being both long on smart thinking and short on roster talent and stability, how Stevens thinks about the use of analytics across the Celtics’ operation is pretty unique and informative. While his depiction of what his staff gets in terms of pre-game prep doesn’t seem particularly unusual, his own utility from the stats and the way his staff communicates info to the players foots with the very practical, mature approach that he carried with him from the college level.
“They’re really receptive,” Stevens said about the Celtics’ players, who receive their scouting information and analytics breakdowns only via iPad. “I don’t think they need [too much]. This is a great balance, because it’s a beautiful game played with great pace without really any breaks when it’s played really well, other than the timeouts that are allotted to each team. And so you have to make decisions on the fly, and you have to be able to apply what you know on the fly. So what you know has to be limited to what’s important. And if you present what’s important, then the guys really like that. If you over-present, then you can de-simplify the game, and that’s not what you need to do. Or that’s not what I think is best.”
In discussing his approach to communication, Stevens semi-jokingly made reference to the famous quote from seventeenth-century French philosopher and mathematician Blaise Pascal, who loosely wrote, “I would have written a shorter letter, but I didn’t have the time.” From the coaches’ meetings on down to interactions with the players, Stevens feels it’s his and his staff’s responsibility to boil down the most important information they receive into the shortest, most concise and implementable base points, while leaving the time and flexibility to adjust as needed.
Stevens noted that as a still-learning NBA coach in just his second year at the pro level at the time of our conversation, he had to spend some extra time on opposition scouting so he could continue to get comfortable with opposing personnel. He also said he spends more time on his own team’s planning and preparation than he typically did at Butler, where the time available between games in a college schedule lends itself much more to game plans designed to defuse what an opponent does well. During the eighty-two-game regular season, with many back-to-backs and all of the travel between games, many teams mostly focus on their own execution. (That changes during the postseason, when teams have a specific opponent for a series of games and more consistent time between games.)
Stevens’s focus is helped by both his own affinity for advanced stats and the team the Celtics have put together. Stevens said that so far in his tenure, there have been very few things that Cannon, Sparks, and their staff haven’t been able to provide for him in fairly short order. That said, Stevens is still a coach first and foremost, and coaches not only have innate instincts for ideas, but also like the visual benefit of video beyond what numerical reports can suggest.
“So I get the data, [and] the data reaffirms or argues against what I already think,” Stevens said. “And 99.9 percent of the time, it just affirms it. So what it is, is a validation, rather than a . . . I don’t take any data without film, nor do I take any film without data. But if I had to throw one out, I’d probably throw the data out because film is so . . . I think film is such an important learning part of how teams play and how teams like to play, who affects you, how does it affect you, how do people match up when certain guys are in the lineup, or out of the lineup. All that other stuff, you just can’t get as much from the data. Now, the data is really important because it can help put you over the top, it can give you a small edge as you’re defending, or a small edge as you’re attacking, whatever the case may be, but I am not of the belief that it’s more important than film.”
One of the biggest challenges of Stevens’s second season was what to do with point guard Rajon Rondo, whose overall skills had eroded some after a serious knee injury in January 2013 and whose lack of shooting ability, whether it was from the perimeter or the free throw line, made spacing and scoring very challenging for a roster that didn’t have much quality shooting.
When asked about how the team’s data helped him find an approach that worked for Rondo, a gifted passer when he was right (along with a markedly mercurial temperament), Stevens took a positive and diplomatic approach.
“Who best complements him, right? [There’s] guys in this league for a reason, [and] those reasons are all different depending on the guy,” Stevens said. “And I think that every one of them has incredible strengths and incredible ability that makes them amongst the 450 best players available, and I think that you try to find—if somebody has something that’s outstanding—you try to find a complement for that, and that’s what I see in trying to piece a team together.
“I’ve kind of always looked at teams that way because there’s only so many of the Kevin Durants or the LeBron Jameses around. There’s only so many guys who can do every little thing well, and there’s guys that can challenge them on a given night, but it’s hard for anybody to do it for eighty-two games.”
Rondo’s welcome eventually wore out in Boston, and he was traded to the Dallas Mavericks, where he continued to struggle and ultimately was booted from the team during the Mavericks’ first-round playoff series with the Rockets. He ended up as one of the Kings’ summer signings on a one-year, $10 million “show me” deal.
Somewhat surprisingly, Stevens’s views foot fairly closely with the aforementioned Stan Van Gundy, he of the animated analytics diatribe. While standing courtside at a morning shootaround before a game in Denver, Van Gundy laughed about the perception of that Sloan appearance before saying, “No, I like the analytics. I think the analytics are very helpful. I think there are some people who think the analytics are everything. I don’t think that. I think it’s a big part of the puzzle, I think you have to give a lot of credence to what the analytics say, but it can’t be the only thing you have. I think there are a lot of intangible factors, putting the team together, chemistry.”
Van Gundy’s setup in Detroit at the outset of his debut season there had analytics information being filtered to him through assistant coach Charles Klask, about whom Van Gundy said “still tends to give me a little too much information. What I really want is him to distill that information down to the stuff he thinks is important and that I can use. . . . Both in terms of coaching and player personnel, I think the biggest challenge in analytics right now is to figure out what is really important.”
Van Gundy and his staff also entered the 2014–15 season with a significant roster challenge: figuring out how to play low-post-focused bigs Andre Drummond and Greg Monroe, as well as Josh Smith, who was much better suited for the power forward spot than small forward alongside those two guys, for spacing and shot selection reasons. The Pistons quickly “solved” part of that issue by cutting Smith from the team, causing a charge of over $5 million to hit their cap in each of the next five seasons for a player they no longer had. They then rode out the rest of an uneven season with Drummond and Monroe before the latter left for Milwaukee in free agency.
As Van Gundy noted in his Sloan discussion, much of his concern with analytics is the integrity and sourcing of the data, and that extends to the current trend in the league with how player workloads are being measured and reduced in order to improve
effectiveness. Van Gundy notes that Michael Jordan was playing “thirty-eight minutes a night and eighty-two games a year” during his final three championship seasons in the late 1990s, and now we have better conditioning and awareness about how bodies work, and practically no players are able or asked to play that amount. There’s also a practical sidebar to Van Gundy’s questions about workload versus rest, and how critique of a coach like Tom Thibodeau, who had significant success with the Chicago Bulls before being let go after the 2014–15 season and was known to play his starters very heavy minutes, bothers him.
“In 1983, I was coaching Division III basketball in Vermont and there was an exercise physiologist in the [physical education] department, and I was twenty-four years old. He said, ‘Can I talk to you?’ and I said ‘Sure.’ He was a really nice guy and he showed me like four or five studies, because he thought I practiced too hard. It was about going hard day, easy day, hard day, easy day . . . and there were studies with track and swimmers and they were better and the whole thing.
“I got it. I understand all that. But our game isn’t just who runs fastest or who jumps the highest. You’ve also got to be able to execute offensive and defensive schemes. I can’t do that without practice time. Swimming and running are just the physical part.
“I think it’s one of things that, when people get on a guy like Tom Thibodeau about overplaying people, the part they’re missing out is that they’re assuming that if those guys did less, they would still execute at both ends the same way, and I don’t buy that. One of the reasons they are as good as they are and execute the way they are is they spent more time at it than other people.”
Tom Penn spent eleven years as an NBA executive, the first seven with the Vancouver/Memphis Grizzlies as assistant general manager/legal counsel, and then four with the Portland Trail Blazers, first as assistant general manager and then as vice president of basketball operations. Since 2010, he has been a basketball analyst for ESPN, specializing in salary cap, team-building, and draft discussions on SportsCenter and other programs.
Chasing Perfection: A Behind-the-Scenes Look at the High-Stakes Game of Creating an NBA Champion Page 15
