If you were to look at a mainstream NBA box score today and compare it to one from 30 years ago, you'd be hard pressed to find many noteworthy differences in what is tracked. With the relatively recent addition of plus/minus excluded, most readers have been looking at the same exact postgame statistics since the day they were born.
TrueHoop at MIT Sloan Sports Analytics Conference
As teams utilize more and more new methods to gather data from games, ranging from Synergy Sports Technology's video charting to STATS LLC's in-game camera tracking, savvy fans are left wondering when all the data will reach their fingertips, specifically in the instant post-game format they've grown so accustomed to consuming.
The "Box Score Rebooted" panel at MIT's Sloan Sports Analytics Conference this Saturday had a heavy baseball tilt, with ESPN's Dean Oliver being basketball's lone representative on the four person panel. Baseball has long been ahead of basketball in its statistical tracking, though much of that is due to the very different nature of the two games.
In contrast to baseball, where the static and isolated nature of the game produces seemingly endless amounts of useful raw data on relevant events, basketball is a dynamic and fluid game with 11 constantly moving parts – 10 players and the ball. This often makes it difficult to quantify certain basic events on the court, and even harder to properly assign responsibility among the players.
How does one distinguish the weighting of value between the passer and scorer on assisted field goals? When Jason Kidd makes an unchallenged pass to Dirk Nowitzki shooting a contested, fade-away, mid-range jumper, but Steve Nash gets in the lane, draws a double team, and kicks it out to a wide open Jared Dudley in the corner, are both of those passes providing equal value? How about if only Dirk's goes in - was Nash's worth nothing?
Indeed, Oliver pointed to proper division of credit and blame being among the largest challenges facing the advancement of statistics in basketball, and said he's actually spent some free time reading legal theory books trying to get a better handle on the issue.
While basketball will always face an uphill battle in untangling variables to apportion credit on the court, there is more potential for advancement in the area of collecting more reliable raw data in the near future, something that has plagued basketball's box score for some time.
With the exception of the notoriously subjective "assist," the conventional box score otherwise consists of largely objective facts, but there is a limit to how much more objective data can be extracted from the game beyond the basics, which is a large reason the box score remained stagnant for so long. Websites such as 82games.com, Hoopdata.com, and basketball-reference.com, among others, have made some modest advancements in pushing the limits of the objective data that can be gathered from the game in recent years, but there's only so much more that can be done in that fashion.
The real advancements to be made in the evolution of the box score and advanced basketball statistics will likely have to come from greater technology, such as the in-game camera tracking that's now installed in one third of NBA arenas. While this new technology provides a treasure trove of data that may be the key to better quantifying the box score's much-neglected defensive end of the floor, it once again goes back to the question of how to assign responsibility for events among players, to say nothing of the incredible difficulty of working with the immense amount of data coming from six cameras each snapping 25 frames per second.
For these reasons and others, most of the advancements in better quantifying the NBA are likely happening behind the walls of the most forward-thinking front offices in the league. Some teams already have employees hand-charting every single game in the NBA, recording various statistics not publicly tracked to try and get an edge on the competition. Others are likely going to work on the data coming from cameras, trying to measure how good players are at boxing out what players are the best at staying in front of their man on the defensive end.
Teams could already be creating their own defensive points per possession numbers for players based on their in-game charting, parsing up credit and blame for every play in the game based on who's involved and to what extent. They could also be solving our earlier conundrum about Nash and Kidd, crediting "assists" based on the expected value of the shot the pass creates rather than the inconsistent end result that's beyond the control of the passer.
Because teams have more of an incentive to utilize data to get an edge on their competition, a larger budget to develop solutions, and more confidence in using their own methodology to determine the division of credit and blame among players, the public is at a large disadvantage in seeing the most useful statistical advancements reach them. Still, the field of sports analytics is growing exponentially, and many of the advancements seen from teams will eventually make their way to the public in some form. In the mean time, there is still some that can be done with what is publicly available, and fans will just have to wait and see where the next innovation comes from.