In the history of NBA free agency, there have been worse moves — particularly when you consider the crazy money that teams have shelled out to big men over the years. And through a certain prism (one that used to be the norm not so long ago), it even seems perfectly reasonable. But the Oklahoma City Thunder’s decision to match Portland’s maximum-level ($70 million) offer sheet to center Enes Kanter received mostly scorn from the Internet after it was announced late Sunday.
At a glance, Kanter is the kind of young post player whose services teams line up around the block to pay for. The list of big men who snagged at least 15 points and 8 rebounds a game as 22-year-olds, as Kanter did last year, is littered with Hall of Famers, to say nothing of players whose numbers Kanter matched (18.7 PPG, 11.0 RPG) after a midseason trade to the Thunder. Decades ago, Kanter would have been seen as one of the league’s rising stars.
Today, though, players are judged on their advanced metrics in addition to per-game averages and the eye test. And few players benefit less from this development than Kanter.
Granted, it doesn’t take supercharged data to suspect Kanter of playing poor defense. He has a reputation for ineptitude at that end of the floor, and his block totals are routinely anemic. But defense is also a complex area of the game that statistics have traditionally been ill-equipped to measure accurately. And without reliable data, defensive deficiencies were easy to deny or downplay as more opinion than fact.
Modern advanced stats, though, help quantify the defensive inadequacies of players such as Kanter with far greater precision than was previously possible. Without Real Plus-Minus (RPM), for instance, you wouldn’t know that Kanter had the worst on-court defensive influence of any center last season. And without SportVU player tracking data, you wouldn’t know Kanter allowed the highest field goal percentage at the rim of any qualified1 big man a year ago. The recent advent of deeper NBA data has made it tougher for poor defenders to hide their shortcomings.
Surprisingly (at least to me), Kanter’s offense also suffers on the sabermetric front: He doesn’t appear to help his teams score as efficiently as would be expected from his basic statistics. Only a few players have scored as much, and with as much efficiency,2 as Kanter has over the past three seasons, but it doesn’t seem to matter. During Kanter’s career, his teams have scored 1.5 fewer points per 100 possessions with him on the floor than without, and — perhaps not coincidentally — he had the second-worst offensive Box Plus/Minus (BPM) of any player in the aforementioned group, and the fifth-worst offensive RPM.
The single most important component of a player’s on-court offensive influence3 is scoring efficiency, and that’s not a trouble spot for Kanter. But even more important (when taken collectively) are a player’s assist rate and his ability to get to the line and to take 3-point shots, and Kanter sets the team back in both areas.
That may not seem important because Kanter is still personally scoring points, but basketball is a tricky sport that way. The fascinating thing that happens when you search for links between component categories and overall offensive performance is that unexpected relationships fall out of the data. A player’s passing can amplify (or diminish) the potency of the threat his scoring talent represents; his ability to stretch the floor or collapse defenses into the paint can open up opportunities for teammates. Kanter’s own numbers might not be affected, but his weaknesses show up in his team’s rates of shooting efficiency, turnovers and, ultimately, offensive success.
The idea of players being hollow stat-stuffers is hardly new, but the ability to quantify it with enough certainty to resist the lure of the potential “20 and 10” guy4 at the negotiating table is a novel development. Too novel, in fact, since OKC did eventually cave and match Portland’s offer to Kanter, putting the Thunder above the luxury-tax line they’d traded James Harden to avoid less than three years earlier. But if the rapid acceptance of advanced metrics is any indication, Kanter might be one of the last of his kind.
In other words, don’t be surprised if the days of a player cashing in on hollow numbers are, well, numbered.