Understanding the NBA: Explaining Advanced Offensive Stats and Metrics

Adam Fromal@fromal09National NBA Featured ColumnistJanuary 26, 2012

Understanding the NBA: Explaining Advanced Offensive Stats and Metrics

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    There's no such thing as a perfect statistic, but there is such a thing as the perfect application of a statistic. 

    While some people believe too fully that there is nothing more to basketball than the "human aspect," others realize that numbers can explain a whole lot about the action on the court. Those that embrace the numbers generally tend to see their knowledge of the game increase, but only if they know how to use the stats.

    Now I do understand that some of the advanced stats and metrics can be a bit intimidating because they're unfamiliar and, in some cases, complicated. It doesn't help that we're force-fed traditional, sometimes useless stats by the media.

    Every time I see someone immediately dismiss an advanced statistic because it's "useless," it kills a little part of me. No stat is worthless if you know how to use it. 

    The following nine slides explain the most common of the advanced offensive stats and metrics. Check back later for the defensive and overall ones.

    And as always, feel free to leave any comments or questions in the appropriate section.   

    You can find all of these stats and more at Basketball-Reference.com, 82Games.com and HoopData.com.

Assist Percentage (AST%)

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    Where A=Assists, MP=Minutes Played, TMP=Team Minutes Played, TFG=Team Field Goals, FG=Field Goals


    Leading off this guide to advanced offensive metrics in the NBA is perhaps the most basic of the stats: assist percentage. I say perhaps "basic" because it's one of many tempo-free stats, or stats adjusted for pace and volume. 

    While assists in themselves are kind of useful to look at, assist percentage is a much better statistic to cite when trying to make a case for a player's skill in the passing department. Assist stats can be padded by two things: the amount of time that a player is on the court and the pace at which his team plays.

    A player on a fast-paced team like the Miami Heat or Washington Wizards is going to have more offensive opportunities to rack up counting stats, leading to elevated numbers of assists per game and assists per minute (which are also a better way of looking at assists than just assists by themselves).

    Similarly, a player who plays 35 minutes per game is going to have more opportunities to generate assists than a player on the court for 20 minutes per game. It may seem like common sense that averaging 10 assists per game in 20 minutes of action per contest is more impressive than averaging 10 assists per game in 35 minutes of action per contest, but that distinction is lost when only assists per game is cited.    

    Because assist percentage is free from the effects of pace and volume, it's a better indication of how effective a player is at racking up the dimes during each and every one of the team's possessions. 

    The stat essentially estimates (note: estimates, not calculates) what percentage of made shots by teammates were assisted by a player while he was on the floor.


    Without looking at play-by-play data, the best this stat can do is provide an estimate of the aforementioned percentage it is meant to calculate. Additionally, there is no way to measure and give credit for good passes that resulted in missed open looks.

    Just as with any assist statistic, a player is at the mercy of the skill of his teammates. 

    Example Usage

    "Steve Nash is currently leading the league in AST% at 57.3."

    How I interpret that sentence: It's pretty incredible that Nash is overcoming the effects of old age and worse teammates than he's accustomed to and still finding a way to assist over half of the field goals his team makes while he's on the court.  

Turnover Percentage (TOV%)

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    Where TO=Turnovers, FGA=Field Goals Attempted, FTA=Free Throws Attempted


    The second of the offensive tempo-free stats, turnover percentage, is free from the effects of tempo because it isolates the possessions in which the player in question made a box score impact.

    Before explaining exactly what this stat does though, I'd like to focus on the parenthetical denominator of the above calculation: (FGA+0.44*FTA+TO). This mathematical expression is the best way of quantifying the number of play results a player was involved in without simply going back through every box score and actually counting.

    There are three ways that a player can be involved in the end result of a possession. They can attempt a field goal (regardless of whether it's a two-pointer or a three-pointer), they can end up on the foul line or they can turn the ball over. However, simply summing those three results does not provide the number of possessions because shooters can attempt either one, two or three free throws on any given possession. 

    Box scores don't explain how many shots a player was fouled on, so we have no idea of knowing which fouls resulted in and-ones (for example) without looking through historical play-by-play data.

    Just trust on this one (I've read the studies and they're too complicated to explain in a short space) and accept the fact that the 0.44 multiplier is the best way of estimating the total number of possessions a player is involved in. 

    So now that we've got that out of the way, all this stat really does is calculate the number of turnovers a player will make in 100 individual plays.

    Turnovers and turnovers per game are both dependent once more on pace of play and the amount of time a player spends on the court. This rate statistic eliminates those detriments and focuses solely on the percentage of times a player turns the ball over compared to the amount of times they're involved in the play.  


    Turnover percentage still can't factor in the passes that a player makes that result in non-turnovers (i.e. assists or passes to other players who either miss a shot or don't shoot).

    Therefore, it's still a fairly limited stat because it only focuses on the true outcomes of possessions when that player is involved. 

    Example Usage

    "John Wall's TOV% of 18.8 is even worse than his rookie mark of 18.6."

    How I interpret that sentence: After posting a pretty poor TOV% during his rookie season, John Wall is actually turning the ball over more per 100 possessions this season. That's one area of his game that he really needs to work on. 

Offensive Rebound Percentage (ORB%)

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    Where ORB=Offensive Rebounds, TMP=Team Minutes Played, MP=Minutes Played, TORB=Team Offensive Rebounds, ODRB=Opponents Defensive Rebounds


    Whenever a shot clanks off the rim, there are four possible outcomes: The ball could go out of bounds and be counted as a defensive team rebound; the ball could bounce of a defensive player and go out of bounds to be counted as an offensive team rebound; the ball could be pulled down by a defensive player and be counted as a defensive rebound; or the ball could be pulled down by an offensive player and be counted as an offensive rebound.

    If you add up all four of those results, you account for all of the potential rebounds in a game.

    Offensive rebound percentage calculates the percentage of available offensive rebounds that a player grabs while he's on the court.

    This is the last of the commonly-used offensive tempo-free rate stats and much like the previous two, it doesn't account for pace or volume.   


    Once more, it's too much trouble to go back and retroactively look at all historical box scores. No one really wants to do that.

    Therefore, this is merely an estimate, albeit an accurate one.  

    Example Usage

    "DeMarcus Cousins' ORB% of 16.4 leads the NBA during the 2011-2012 season, even beating Kevin Love's 12.5."

    How I interpret that sentence: The big man for the Sacramento Kings grabs the offensive board nearly a fifth of the time that his team misses shots (which happens quite a bit). 

Effective Field-Goal Percentage (eFG%)

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    Where FG=Field Goals, 3P=Three-Pointers, FGA=Field-Goal Attempts


    Field-goal percentage (FG%) was once one of the better stats for estimating shooting ability up until the popularization of effective field-goal percentage in the 1990s. 

    The only difference between the two stats is that three-pointers are weighted more heavily in eFG%. Seeing as three-pointers are worth three points and two-pointers are worth two points, this makes sense.

    That may be the most ridiculously obvious sentence I've ever written. 

    Don't make the mistake of thinking that the multiplier in front of three-pointers should be 1.5 though. Essentially, it is in the above formula because three-pointers are counted one time in field goals and another 0.5 times on the other side of the addition sign.

    So, as for the merits of effective field-goal percentage, tell me which of the following players you'd rather have:

    Player A attempts 10 shots from the field, all from within the three-point arc, and drills five of them.

    Player B attempts 10 shots from the field, all from outside the three-point arc, and drills five of them.

    Player A, who was responsible for 10 points, has a FG% of 50 percent, just like Player B, who was responsible for 15 points, despite shooting the same number of times. However, Player A's eFG% was still 50 percent while Player B's was a much better 75 percent.    


    While I like eFG% as a stat, there is still a measure of shooting that is significantly better. If for nothing else, that's because it takes free-throw shooting into account as well, unlike eFG%. 

    You'll see what that stat is pretty soon. 

    Also, the penalty for missing a three-pointer is the same as the penalty for missing a two-pointer because all attempts are weighted the same. 

    Example Usage

    "Ray Allen is currently leading the NBA in eFG% at 63.5 percent."

    How I interpret that sentence: Ray Allen's FG% of 50.2 percent is impressive enough, but once you look at his three-point shooting prowess, his eFG% is even more impressive. 

True Shooting Percentage (TS%)

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    Where PT=Points, FGA=Field-Goal Attempts, FTA=Free-Throw Attempts


    There are three ways that an NBA player can score: three-pointers, two-pointers and free throws. It just makes sense that the best measure of shooting percentage would take all three of those methods of scoring into account. 

    So, does true shooting percentage look at all three?

    As you can see by the "Field-Goal Attempts" and "Free-Throw Attempts" in the calculation, TS% clearly at least takes two-pointers and free throws into account. As for the 0.44 multiplier, the same reasoning applies as did for turnover percentage. You can find the full explanation on that slide.

    Three-pointers are a little harder to find in the formula, but they're still there, hidden within the word "Points." The maximum TS% is actually 150 percent and can only be achieved if a player hits each and every one of his shots and they're all from downtown. For example, if a player goes 1-for-1 and his only shot is a three-pointer, the formula will read and simplify as follows: 3/(2*1+0.44*0)) = 3/2 = 1.5.

    Because this stat does take everything into account, it's easily the best measure of shooting ability we have. Just for the record, it can also be called adjusted shooting percentage, effective shooting percentage, effective percentage, points per shot attempted and scoring efficiency.  


    Other than only accounting for shooting ability, and thereby not qualifying as an overall evaluation of a player's offensive ability, the only true limitation of TS% is that it's possible (although extremely unlikely) to have a TS% of over 100 percent.

    Also, just like with effective field-goal percentage, all missed attempts count the same.   

    Example Usage

    "For the second straight season, Tyson Chandler is currently leading the league in TS%, this time with a mark of 77.1 percent."

    How I interpret that sentence: Chandler may not be the best shooter in the NBA, but this stat shows that he's the most efficient scorer, even though he doesn't ever make three-pointers.

    His effectiveness in the paint and competency from the free-throw line elevates him significantly.  

Usage Rate (USG%)

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    Where FGA=Field-Goal Attempts, FTA=Free-Throw Attempts, TO=Turnovers, TMP=Team Minutes Played, MP=Minutes Played, TFGA=Team Field-Goal Attempts, TFTA=Team Free-Throw Attempts, TTO=Team Turnovers


    This may be the most complicated looking calculation yet, but the concept behind it is really quite simple. Usage rate calculates what percentage of team plays a player was involved in while he was on the floor, provided that the play ends in one of the three true results: field-goal attempt, free-throw attempt or turnover.

    On average, a player will have a usage rate of 20 percent. Think about it and it will make perfect sense. 


    Only the true outcomes are measured here, so there is quite a bit left out. For example, a player like Ricky Rubio, who prefers to pass more than shoot will have a much lower USG% than a player who prefers to shoot.

    Yet, a player who passes the ball is still involved in a possession in my mind.  

    Example Usage

    "Kobe Bryant's USG% of 38.8 is the highest of his career and is leading the league in the category for the second straight year." 

    How I interpret that sentence: Kobe Bryant needs to pass more. 

Points Per Possession (PPP)

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    Where PT=Points, FGA=Field-Goal Attempts, FTA=Free-Throw Attempts, TO=Turnovers


    The numerator is clearly represented by the word "Points." There is really no explanation necessary there. 

    Per refers to the division sign. 

    We've already seen how possessions can be best estimated by what's written in the above denominator. The full explanation is provided on the turnover percentage slide. 

    This stat in its simplest form explains how efficiently a player uses his time with the ball to score. With the help of companies like Synergy, PPP can be further broken down into certain situations like isolation plays, pick-and-roll situations, etc. 


    This stat only refers to scoring efficiency and there's more than scoring to basketball, even on offense. 

    Other than that and the fact that the possessions are estimates, there aren't too many limitations to PPP. 

    Example Usage

    "Kyrie Irving's teammates are scoring 1.455 PPP when he passes out of isolation situations."

    How I interpret that sentence: This is yet another example of how impressive Kyrie Irving's rookie campaign has been, as he's clearly recognizing the defenses he's facing and making good decisions. 

Offensive Rating (ORtg)

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    Where PP=Points Produced, FGA=Field-Goal Attempts, FTA=Free-Throw Attempts


    Offensive rating is just the amount of points produced by a player per 100 possessions.

    Seriously. That's it.

    The reason this one is useful is that it's another tempo-free stat. Offensive rating eliminates factors like pace of play and minutes played per game.

    Unfortunately, I don't have access to the calculation of Points Produced. The formula can be found in Dean Oliver's book Basketball on Paper.  


    Because of the estimations made in both Points Produced and the formula for possessions, this is once more just a baseline and not an exact number. 

    This stat also rewards players who shoot a high percentage more than anything else, which is why you'll generally see low-usage big men high up on the leaderboards.  

    Example Usage

    "Ryan Anderson's ORtg of 127.9 is the second best mark in the NBA and further evidence that he is truly breaking out."

    How I interpret that sentence: Ryan Anderson has been an incredibly efficient player this season, but his usage rate of 22.3 percent probably has something to do with his high ORtg. 

Offensive Win Shares (OWS)

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    Where PP=Points Produced, LPPP=League Points Per Possession, FGA=Field-Goal Attempts, FTA=Free-Throw Attempts, TO=Turnovers, LPPG=League Points Per Game, TP=Team Pace, LP=League Pace


    As explained by Basketball-Reference, this is really a five-part calculation, the details of which can be found in the page hyperlinked to. 

    Win Shares are easily the best metric for evaluating the offensive play of a single player because it accounts for almost everything and scales the result so that one OWS is actually equal to one win added to the team's cause. 

    Points Produced takes all facets of the offensive game into account: points scored, assists and offensive rebounds. Moreover, the metric is tempo-free. 


    Compared to the rest of the stats included in this slideshow, OWS doesn't have too many flaws. The only true flaw is that while it accounts for pace of play, it's still a counting stat of sorts.

    Although different from counting stats like total points, there is still a clear benefit to players who are on the court for a lot of minutes. 

    Example Usage

    "LeBron James has generated more OWS than any other player this season, as his mark of 3.0 clearly shows."

    How I interpret that sentence: LeBron James is the best offensive player in the league.