Hail and rejoice, fellow basketball nerds. Tomorrow is the day of our reckoning.
Since the NBA announced that it would be outfitting all 29 arenas with the tracking cameras that comprise the SportVU array, the question on the minds of many has been one of how quickly the viewing public would have access to the data. As something of a pessimist, I put the over/under at about 2 years.
And I was very, very wrong.
Wouldn’t it be beneficial to know how many “assist opportunities” your favorite NBA player created? The ones his teammate converted into baskets, plus the one his teammates botched, plus the ones that led to free throws? Sure, this statistic still relies somewhat on teammates — they have to get open. Or on the aptitude of the defense — if the opponent has signed a non-aggression pact, it’s easier to pass the ball. But a player’s assist opportunities are a far more telling measure of his passing performance.
Barring any last-minute glitches, hoops fans will have access, starting on Friday, to such passing stats, and a whole new set of data delivering new layers of insight into basketball. On NBA.com’s expanded statistics page, fans will be able to see and sort info from STATS LLC’s SportVU Player Tracking system.
It’s assuredly an exciting development, but one would be wise to temper expectations, especially in the early going. The data simply won’t be that robust come Friday, and though the sample size will grow faster than a magic beanstalk as the season progresses, even an entire season’s worth of games isn’t enough to draw hard conclusions.
And that’s the kicker with this technology — it isn’t about answers.
When the data set becomes more thorough, the information will undoubtedly be more useful. But it’s never going to be a magic bullet that will point you to some absolute truth about the NBA. Those who seek answers with SportVU are taking the wrong approach. A system of this nature and magnitude is about asking the right questions. It’s about finding the right perspectives and the right context.
It’s about taking a look at the fallacy of assists and saying that we can do better. It’s about combining ideas like expected points per possession with a tool that can effectively track every pass that happens on the court. From there, with enough data, the brightest minds in our community will calculate the expected value of each of those passes. This data is about seeing those razor-thin margins; it’s about the Miami Heat having a hypothetical expected offensive efficiency around 1.00 points per possession when Chalmers has the ball in his hands to start the play, and calculating the value of his different options as the Heat run through their sets and motions. When Mario Chalmers gets the ball to LeBron James, what result can we most commonly expect, and how much more efficient is the ensuing decision than the same outcome generated by a league average player? How does LeBron’s field goal percentage increase over his expected output when he comes off a screen with Shane Battier stashed in the weakside corner? What’s the opportunity cost of Chalmers being unable to make that pass, either through his own fault or to the credit of the defense?
It’s about asking how that defense is able to prevent efficient looks. It’s about asking whether a player has a greater or lesser impact by closing out an additional foot on a shooter or if his efforts are best spent by conceding that little bit of space and clogging passing lanes instead. It’s about looking at data that says there’s little link between turnovers forced and offense generated, then taking that catch-all categorization of turnovers and breaking it down. Does a team that forces turnovers on side-to-side passes from above the break to the corner generate more points on the subsequent possession than they would after an inbound pass following a made basket? Are the best live-ball turnovers, from the offense’s perspective, those that occur on passes into the paint which allow the offending team the time and opportunity to get back in transition defense? Is the most damaging turnover one from the post back to the outside, which generates a head of steam for the player who steals the ball and little resistance from a minimal number of defenders going the other way?
This data is about realizing that rebounds are a multi-axis system, that rebounding isn’t just about grabbing the ball when it’s within a player’s reach. Rebounding is about positioning and space and the interaction of 10 different players with the physical bounce of the ball. Which players box out so effectively that, while they may not grab what seems to be their share of rebounds, they create opportunities for their teammates to corral the miss by sealing off an opponent with the tenacity of Montresor? Which players cast the widest net in their reach for rebounds?
It’s about finding out who covers the most space and does so most effectively, be it in the open court or closing out on a shooter. It’s about finally putting numbers to the concept that Dirk Nowitzki bends a defense and creates openings for his teammates simply by existing. It’s about untold numbers of questions and lines of thought and concepts of what goes on during an NBA game.
So yes, fellow basketball nerds, herald the coming of this new age, and do so joyfully. But abandon all hope for answers, ye who enter here. You will not find them unless you ask the right questions. The information is here, and it will be available to all. Its worth, however, is only paramount to those who seek to avail themselves of its multitudes.