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3 Underrated Analytical Metrics in the NBA

Ben Dowsett breaks down three underrated metrics that help us better understand the NBA.



Increased mathematical proficiency in basketball has given way to a plethora of different figures and statistics attempting to complement and often define our understanding of the game. All-in-one metrics like PER were a big part of this initial push, with their ability to combine many smaller statistics into one larger one that can broadly define a player or team’s value. Plus-minus statistics are more of a recent rage in the public sphere, which are useful in a whole different context, and there’s a vast world in between: everything from broad metrics to the most detailed and minute descriptors possible.

All these different figures vary wildly in terms of value, whether descriptive or predictive in nature. It’s easy to draw conclusions from a particular stat that it’s not designed to reach, an unfortunately common part of the statistical process among more casual fans and analysts. And while it’s less common, the other end of the stick is true also; there are metrics out there that still don’t get enough recognition for the value they provide.

Let’s take a look at three lesser-known stats, at least within the public consciousness, and see how they can help us gain a greater understanding of the game without reaching past their constraints.

Open Shooting Numbers

As the NBA has begun sharing small snippets of SportVU camera data with the public over the last few years, one of the simplest nuggets they’ve released is basic defender distance numbers for every shot taken on an NBA floor. We can tell how far away a player’s closest defender stood for any shot he’s taken since the 2013-14 season. NBA.com defines coverage as “very tight” for a defender within 0-2 feet, “tight” for 2-4 feet, “open” for 4-6 feet and “wide open” for anything beyond six feet. The consensus among those who use these numbers frequently is that these are generally reasonable proxies for how truly open or guarded a guy is on a given shot – particularly the four-foot mark, around which a legitimate jump is observed over large samples of shots that indicates it’s truly a close inflection point between “open” and “guarded.”

These metrics are imperfect, of course. They track only players’ torsos, meaning a guy with particularly long arms might be better at contesting shots than his raw SportVU data would indicate. They also say nothing regarding whether a defender’s hand was in the air or close to the ball, which can also be important. But over a huge sample during the last few seasons, they’ve proven to be the closest thing we have to a real indication of which players and teams are best shooting with certain levels of pressure.

The most easily applicable area here to our on-court understanding is likely within open and uncontested shots. The conditions for a wide open shot aren’t ripe to as many confounding factors – if the closest defender to a jump shot is seven feet away as the ball is released, it doesn’t matter how high he’s jumping or how long his arms are, making all shots of this nature at least relatively similar. In contrast, judging contested attempts in the same vein is much more difficult; such analysis might include layups, for instance, which frequently will feature a defender within a foot or two but not actually challenging the shot.

What this newer data allows us to do with far more specificity than ever before is answer the question of which teams or players are truly the most talented shooters in a vacuum. A very basic example: One would likely call the Warriors the best pure jump-shooting team in the league, right? Turns out one would be supported by the numbers – per NBASavant, the Dubs are head and shoulders above the rest of the league for “open” jump shots outside 10 feet. On the other end of the spectrum, as one would expect, the Philadelphia 76ers bring up the rear for this same category.

The broad implications of all the public SportVU data are vast, but open shooting is among the most reliable and easiest to track for even the casual fan.

Better Pace Metrics

When we discussed certain teams zigging where Golden State has zagged with regard to speed of play as a specific Warriors counter a few weeks back, one of the chief elements was a more detailed definition of “pace.” The typical figure cited for pace, housed on NBA.com and other major sites, is simply possessions per-48-minutes among both teams in a given game. As we noted, though, this can make it tough to highlight an individual team’s tempo preferences – the opponent at any given time may have very different goals or tendencies, making it an incomplete metric.

A website called inpredictable.com has solved that issue in one swoop. Using detailed scraped data, this site separates pace into offensive and defensive categories based on average time of possession. We can see that the Warriors are the fastest for isolated offensive pace, averaging just 13.4 seconds per possession, while the Jazz are the slowest at 16.1 seconds. The creators are also kind enough to separate these possessions by prior actions – time of possession (and efficiency) following a made opponent shot, following a team defensive rebound or following a forced turnover.

This isn’t an underrated metric as much as it’s a lesser-known improvement on a more common one. Raw pace stats can tell us something, but there are very few cases where this more isolated form won’t be more informative and valuable.

Rim Protection

Many areas of NBA.com’s SportVU tracking come with some amount of noise, and rim protection figures are no exception. As with shot defense data above, simply tracking whether a player was within five feet of the rim while defending a shot can be an incomplete exercise because the level to which they’re actually “contesting” the shot can vary wildly even within that small space.

In the case of interior defensive figures, though, a couple factors combine to make them among the most robust available of all SportVU metrics. First, the number of shots attempted at the rim with a defender nearby is so high that minor inconsistencies (say, guys who don’t put a hand up quite often enough) will be teased out over time and reflected in long term figures only if they’re truly detrimental factors in how well a given player defends the rim.

Second, and more importantly, work by smart and generous folks in the statistical community has even further increased the specificity with which we can understand these numbers. Nylon Calculus houses a rim protection section which, rather than focusing simply on percentage allowed at the rim, includes a couple other vital factors as well. They track the percentage of all shots taken at the rim while a given player is on the floor that said player contests, and also separate rim protectors based on the position they play – data over the years has shown that there’s a big difference in expectation for interior defenders even between centers and power forwards.

Combining all factors, they’re able to come up with a much more descriptive final statistic: position-adjusted points saved per-36-minutes. That is, how many points does a given rim protector “save” his team at the rim on a per-minute basis above or below the league average at his position?

There are always a few surprising outliers, but the lists tend to conform closely with who we’d expect to see among the league’s best and worst at this particular skill over larger samples. Guys like Rudy Gobert, Andrew Bogut and Serge Ibaka are virtually a constant atop these rankings, while known defensive liabilities like Al Jefferson and Andrea Bargnani are typically at the bottom. In a game where scoring at the rim is more important than ever before, accurately assessing which defenders are best at preventing opponents from doing so is a vital part of our analysis.

Ben Dowsett is a Deputy Editor and in-depth basketball analyst based in Salt Lake City. He covers the Jazz on a credentialed basis for Basketball Insiders, and has previously appeared in the Sports Illustrated and TrueHoop Networks. He can be found on Twitter at @Ben_Dowsett.

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