CHASING PERFECTION: A Behind-the-Scenes Look at the High-Stakes Game of Creating an NBA Champion
By Andy Glockner
Da Capo Books. 274 pp. $25.99.
You know you’re serious about winning basketball games when you rely on Israeli missile-tracking technology.
That technology, involving cameras that analyze the real trajectories of missiles compared with their expected paths, eventually migrated to sports — first soccer matches, recording the movements of every player, and then basketball, hovering over every NBA court, logging the motion of players in three dimensions and collecting the data in real time.
“The NBA’s decision to install the cameras in every arena has pushed the league headfirst into the Big Data era,” Andy Glockner writes in “Chasing Perfection,” his revealing — if somewhat narrowly cast — look into the world of advanced analytics, training technologies, roster management and peak fitness strategies for professional and collegiate basketball.
If you’re used to the usual basketball stats — points, assists, rebounds, blocked shots, free-throw percentage and the rest — get ready for a whole new vocabulary. Glockner introduces you to gravity scores and paint touches, offensive efficiency and defensive playmaking. And, of course, there’s real plus-minus (RPM), which, as we all know, is an improvement on regularized adjusted plus-minus (RAPM), which in turn tweaked the original plus-minus statistics, “which were a rough approximation of how many points better or worse a team performed while a player was on the floor, adjusted for his teammates on the court with him.” Got that?
Hoops fans loyal to pro franchises, college mascots and curmudgeonly coaches will discover an entirely new subculture of the game: the cluster of tech, nutrition and data-analysis companies orbiting the league — outfits such as Second Spectrum, Synergy Sports Technology, Kinduct, Peak Performance Project (P3 to those in the know) and of course SportVU, which works on those motion-capture cameras. They’ve become as much a part of basketball as March Madness brackets and endless NBA playoff series.
Michael Lewis’s 2003 book, “Moneyball,” brought sports analytics into the popular consciousness, making Oakland Athletics executive Billy Beane a folk hero and turning “sabermetrics” into a household word (at least in households obsessed with baseball). Glockner points out that basketball is harder to break down. “Baseball is a game of discrete, one-on-one, well-defined interactions between a hitter and a pitcher . . . it’s still a much simpler sport to analyze than basketball, in which each play on the court involves ten players moving in dynamic, undefined, unlimited patterns.” Nonetheless, there is a rich tradition of hoops data geekery, dating back to 1959, when the University of North Carolina’s Dean Smith, then an assistant coach, wrote a book chapter on how to evaluate defenses and offenses not on point totals per game but on a per-possession basis.
Though “many basketball lifers are reluctant to believe what a computer tells them,” Glockner writes, some of the most successful NBA teams in recent years, such as the San Antonio Spurs and the Houston Rockets, are also those that have gone all-in on analytics. For the five-time league champion Spurs, the key in recent years has been managing the playing time of the team’s aging stars, calculating ways to gradually reduce their workloads without sacrificing wins. For most teams, the trade-off is inevitable, but the Spurs pulled it off during the 2013-14 season without any impact on the team’s win-loss record, Glockner writes, thanks to the quality of their bench players and skillful management by longtime coach Gregg Popovich. “That’s an amazing advantage,” Glockner marvels, “especially in a league where being healthy in the playoff is paramount.”
The Rockets, meanwhile, have bought into “Moreyball efficiency,” named after team executive Daryl Morey — a style of offense that may not be the most aesthetically pleasing but that produces points efficiently, relying on baskets in the paint area (close to the hoop, thus high-percentage shots) and on three-point shots, especially from mega-star James Harden.
The story of how the Rockets decided to sign Harden is another illustration of analytics in action. Previously a super-sub for the Oklahoma City Thunder, Harden played in the shadow of stars Kevin Durant and Russell Westbrook. Would he blossom as the first scoring option on his own team? Turns out, during the 460 minutes when Harden was on the court without the two stars, he scored 36.2 points per game per every 36 minutes played, along with 6.2 assists and 4.7 rebounds. “Now, 460 minutes over eighty-two games is not a ton to go on, but those numbers were extremely promising for Harden’s potential to be a No. 1 option,” Glockner writes. It worked out for the Rockets — over his first two seasons, Harden averaged more than 25 points per game, leading the team to the Western Conference finals in 2015.
Of course, all this scoring and strategizing means little if players can’t stay healthy over the grind of an 82-game regular season. “Players are learning more and more about themselves through video and data visualization, are seeing how things like diet and sleep can impact their performance, and are learning how having healthy joints and role-specific workout plans are lengthening and improving their careers,” Glockner explains.
He tells the story of Atlanta Hawks guard Kyle Korver, who remade his career thanks in part to P3, which helped him improve his shooting form. “I almost threw up,” Korver said after he saw video of himself from multiple camera angles at the P3 facility in Santa Barbara, Calif. “I was horrified at my own mechanics. I got chills. I’m like, ‘I’ve been doing that every time I jump?’ ” Now he moves his family to Santa Barbara every summer so he can work out at P3. They work on boosting his vertical quickness. “It doesn’t matter if he can [vertical] jump forty inches. It matters if he can get to twenty-four inches first,” a P3 specialist explains, because that’s where Korver releases his jump shot.
Glockner, who labels Korver the NBA’s “most perfected player,” indulges in a little hoops poetics when describing Korver’s post-P3 shooting stats: “His three-point shot chart on NBA.com looked like a minimalist painting, with all five regions outside the arc bathed in the sweet light green of outperformance.”
The analytics revolution is spreading to the college game, where coaches such as John Calipari, evangelist for the University of Kentucky Wildcats, have found religion. Blessed with an overabundance of player talent, Calipari had to find ways to spread the minutes around and keep everyone happy. “Calipari’s hard sell to his players was that NBA personnel care about percentages and rates more than gross numbers, and his players would have a huge opportunity to post impressive stat rates” if they played in shorter bursts of time, Glockner writes. With the help of a director of analytics, the team tracks innovative stats such as “defensive playmaking” (steals plus blocked shots divided by total fouls), compelling players to exert greater effort on all facets of the game.
There are some blind spots in “Chasing Perfection” — the women’s game, whether professional or collegiate, is an afterthought, and the notion that college student-athletes need to do anything other than play hoops is barely entertained — but Glockner highlights two points worth remembering as the analytics gurus rush the court. First, there are serious privacy concerns as experts consider whether to track players’ biometric and health data, including through regular blood tests. And second, the more relevant data measurement becomes to the game, the more important human interpretation and communication become, too.
“As good as a data team can be in managing and exploring data to solve team questions . . . 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,” Glockner writes. Those audiences are owners, general managers, draft personnel, coaches and, most important, players.
“When you try to explain analytics and data to a player, they think, ‘Whoa, whoa, whoa, basketball is not about numbers, basketball is about being primal, it’s about emotion, it’s about mental toughness’ and most players don’t think there’s any link to the data,” former Duke University standout and NBA veteran Shane Battier says to Glockner. “In actuality, all analytics are a way to explain all those things: heart, determination, toughness. And you just have to look at it in a different way.”
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