How To Be A Better Basketball Fan
I’m not really sure what to do with this intro, so why not just scrap it and get to the point? You came for the title, not necessarily me.
Ok.
There are a lot of people out there who want to learn more about basketball; they want a deeper understanding of the game. Contrary to what the title might have suggested, I am not, in fact, the ultimate gatekeeper of basketball knowledge, nor the arbitrator of absolute basketball truth. None of that stuff. However, I do have something to offer. Not too long ago, I was a pretty dumb fan with a likewise understanding of the game. Luckily enough (through Twitter), I stumbled across an incredible network of writers, podcasters, and video creators. And now, sometime later, I am not that dumb of a fan. How did I do it? Well, two steps. No, actually three. It doesn’t matter. Anyone can become a better fan, they just need to know where to look. Whether you just found out about the sport, have been a casual fan for years, or simply realized that you may be missing out on the finer details, this is for you. Here, I’m going to detail my journey out of the cave. Not through a personal recounting, but rather by re-capping the various resources that helped me understand - and as I would later find out, appreciate - basketball on an entirely different level. This thing - resource, article, etc. - is exactly what I wish I had when I made the decision to peak beneath basketball’s surface. Feel free to skip around, as this is a resource with no sort of chronology. Otherwise, let’s go!
- Table of Contents (feel free to control-F, or skip, around) -
Re-Wiring Your Mind
Fantastic NBA Statistics and Where to Find Them
The Basics
Do’s and Don’ts
The Stat Sites
How To Interpret Stats & A Basketball Philosophy Tie-In
Two 20-Point Scorers
Basketball Philosophy - Roles, “Fit”, and Synergy <- (Important)
Rules of Thumb
Player Comparison
Getting Smarter - What To Read (Coming Soon)
Step 1 - Re-Wiring Your Mind
This is arguably the most important step. It’s where I was stuck for a very long time, before the way in which I consumed basketball was viciously destroyed, as my reborn basketball mind rose from the ashes. That might have been a tad bit dramatic, but I think you get the point; I was red-pilled. So, what actually is this magic remedy for ignorance?
A book that goes by the name of “Thinking Basketball”. It’s a relatively short read at 180 brisk pages, but is full to the brim with new insights. Thinking Basketball won’t actually teach you that much about basketball - it doesn’t offer any technical knowledge. Instead, it’ll prepare you for the technical stuff by giving you a lens through which you can consume anything ‘basketball’. After I finished the book (which I did in a couple of days), I felt like I was following an entirely different sport. So please, if you’re a new/newly invested fan, order the book and read it (right after finishing the article and reading everything else on the site, of course). After you’ve read it, lend it (or recommend its purchase) to everyone you know who likes basketball. I seriously cannot recommend it enough. Consistent with its name, it will teach you how to think about basketball.
I understand that you may not have “Thinking Basketball” at your side right now, but also that summarizing all of the book’s best ideas here would be wrong. However, I’d like to share one idea with you, inspired by the book, before we move on: Being a good player means helping your team win. In the same vein, being a good offensive player means helping your team’s offense, and the same goes for the other end.
This seems obvious at first, but let it sit in for a second. We often use scoring (and hopefully, efficiency), as a proxy for being a good offensive player. And while there is a lot of overlap between high-volume scorers and good offensive players, the two are not binary, because, once again, the only thing that matters is the team’s scoring. It’s a bit hard to actualize what I’m saying here, but this graph from Ben Taylor, the author of “Thinking Basketball”, does a pretty good job of it:
An idea to fuel the concept of how this all works - the opening of “Thinking Basketball” talks about Wilt Chamberlain. Specifically, how, despite being the most efficient scorer on the team, the team’s offense actually performed better in the season where Wilt shot less often. Anyway, enough of me ripping off Ben’s content - go read the book.
Step 1.5 - Fantastic NBA Statistics and Where to Find Them
This section may not be helpful to everyone, but if you’re just getting into the NBA, I think it’s worth a read. Now, whether you love ‘advanced statistics’ or won’t touch them with a 10-foot pole, it’s still a good idea to have a better idea of what they are and are not.
For those who have some time to kill, Thinking Basketball has a fantastic introduction series on stats; but if not, I got you. Let’s start off with The Basics:
Per-Possession is the golden mean of NBA stats. If you want to compare two teams’ offenses, simply stacking up their point-per-game averages doesn’t work. That is because each team plays at a different pace - pace meaning the number of possessions played per game - so it’s only fair to measure an offense by looking at how efficiently they use those possessions. These measures of offense and defense are called Offensive Rating (ORTG) and Defensive Rating (DRTG), respectively. Their formulas are quite simple:
Offensive Rating = (Points/Possessions) * 100, which gives you points per 100 possessions
Defensive Rating = (Opponent Points/Possessions) * 100, which gives you points allowed per 100 possessions
This applies on the individual level as well. _____ per game, or _____ per 36 minutes, still fails to adjust for pace, aka how many possessions a given player actually got to play. If you want to compare stats between two or more players, ‘the’ way to standardize their numbers is by using per-75 (per 75 possessions) stats. We use 75 possessions as a benchmark because a regular game has ~100 possessions, and this is simply a continuation of the per-36 minute logic, that stars play about 75% of the time.
However, sometimes even per-75 doesn’t do proper justice. Certain stats are better represented as percentages, such as blocks, which can only happen after a shot attempt; thus, BLK% (Block Percentage) divides blocks by opponent shot attempts (and on some sites, only 2-point attempts), rather than simply all possessions. Likewise, OREB% (Offensive Rebound Percentage) divides offensive rebounds by the number of available offensive rebounds (aka, team misses).
Scoring Efficiency is often misrepresented. Throw FG% (Field Goal Percentage) out the window, because you will never use it again. You see, FG% doesn’t take into account which shots were worth 3 points and which shots were worth 2. This matters, because a player who takes a lot of 3’s, which naturally have a lower conversion rate than 2’s, will have a lower FG% despite potentially scoring more efficiently. We can account for this by using EFG% (Effective Field Goal Percentage):
EFG% = (FGM + 3PM * 0.5) / FGA, where the ‘M’ abbreviation stands for made. This equation counts made 3’s 1.5 times more than made 2’s, because, well, 3’s are worth 1.5x more than 2’s.
But wait, what about free throws? Even though free throws are counted apart from field goals, they are still more or less an extension of one’s scoring game. So, it would only be right to include them in our measure of efficiency, bringing us to TS% (True Shooting Percentage), the ultimate measure of scoring efficiency. Now, this doesn’t give you a license to disregard nuance - Mitchell Robinson was not last season’s best individual scorer; TS%, just like every other number, needs context. Hell, a higher TS% doesn’t always equate to being a better scorer. However, if you want to cite how efficient a player’s scoring is, use TS%. It is THE measure of efficiency
TS% = Points / (2 * (FGA + 0.44*FTA)). Now what is up with the 0.44, you ask? Well, not every pair of free throws is the result of being fouled on a shot. Sometimes, you were fouled on a 3, or made the shot you were fouled on, or went to the line for a non-shooting foul because your team was in the bonus. The 0.44 coefficient knows all of that; over numerous samples of data, 0.44 accurately relates the number of free throws attempted to the number of times you were fouled in the act of shooting - go with it. The ‘2’ in there is just to turn it into a percentage so it’s easier to digest.
So please - never, ever, ever, use FG%. If you want to show how a player gets it done from different areas, simply use 2P% and 3P%, because (we will get to this in a second).
(Also, something I wanted to write but couldn’t find the right place for. Due to offensive inflation, when comparing efficiency marks across multiple years/eras, it’s best to use rTS%, or relative True Shooting, which is TS% relative to the league average during the year in which the data was collected. The same goes for ORTG and DTRG.)
Contextualizing Scoring is a daunting task. Looking at a box score makes everyone’s points look the same, even though the players took different paths to get each bucket, and may have contributed varying amounts to that process. The first good benchmark is ASTD%. Not to be confused with AST% (assist %), ASTD% (assisted %) measures what percent of a player’s made shots were assisted on by a teammate. A lower ASTD% means that a player self-creates more of his own looks, while a higher ASTD% means that more of a player’s looks are created by teammates (excluding the occasional bogus assist, as assists are not flawlessly collected). For reference, the league-average ASTD% over the past three years is ~60% (however, the number of shot attempts, not makes, that are assisted is almost certainly lower, as assisted shot attempts are generally easier attempts and hence go in more). For further contextualization, those ASTD%’s can be broken down by zone.
(The data is from pbpstats.com, a site that will be revisited later. Here, ‘Rim’ is measured as 0-3 feet, SMR, or short mid-range, as 4-14 feet, and LMR, or long mid-range, 15 feet to the 3pt line, with all ranges being inclusive.)
Similarly, looking at a player’s attempts (frequencies) and percentages broken down by the aforementioned zones can tell you a lot about that player as a scorer. When I first looked at these stats - removed from the aesthetics behind them - cycling back and forth between volume and efficiency, a very large insight hit me smack on the forehead. Just like making shots from a given zone is a skill, so is generating those shots in the first place. It’s commonplace to see players that take and make tougher shots, such as pull-ups, fadeaways, floaters, etc., described as having more ‘skill’. Instead, you should be asking yourself why the given player is taking those difficult shots in the first place. Perhaps a deficiency in another area is what’s causing these tough attempts to go up in the first place. The scoreboard doesn’t care how you scored it, just that you did.
No player better illustrates this concept than Zion Williamson. Over the course of his young career, Zion’s FG% at the rim is barely above league-average and definitely below the league-average for his position. Many players have similar or better %’s than Zion does. However, Zion has a rim frequency of 83%, nearly triple (!!) the league-average rate. Hence, Zion is an incredibly efficient scorer. Getting to the rim at that insane rate is a skill - it’s something he does better than any other player, ever. So is holding up that respectable conversion rate over 13 rim attempts a game, in which teams most certainly know that he’s coming. So please, don’t write off those who thrive in the paint as 'athletic’ players and those who live off a diet of tougher shots as ‘skilled’ ones.
This doesn’t mean that having the ability to take and make tougher shots doesn’t have its value - as Giannis’s recent playoff outings have shown, being able to score in multiple ways, keeping the defense on its toes, is still very important. Just don’t veer too far in either direction; be nuanced.
This is why, as I alluded to earlier, I don’t find 2P% to be such an irrelevant stat, namely when comparing two high-volume scorers. I like that it summarizes the totality of what a player does inside the arc, because both the good and the bad are necessary parts of the equation.
Now before we go over the best stat sites and what they offer, there are a couple of Do’s And Don’ts, mainly don’ts, that I should first go over:
Do Not use PER. PER is an archaic metric that measures… nothing? I like stats that measure something tangible - as stats are supposed to do. Now, what does PER measure? I’ll wait. It’s essentially a fancy way of adding together all the counting stats. It measures nothing and has no use. Next:
Do Not use individual DRTG. I see individual defensive rating thrown around wayyyy too often for my liking (which is never). It means nothing. The metric was created before today’s tracking data existed, and hence doesn’t actually measure anything. If you don’t believe me, take a look at how it’s calculated here. If you don’t want to try to make sense of that, I’ll give you the gist - individual DRTG is based on several factors that any given player has intermediate to no control over. I am extremely cautious with defensive metrics in general, but this one is a special offender. So please, never use this in any context. Not to compare players, not to rank an individual player, nothing.
Do Not take one-number metrics entirely at face value (or use them to compare players). Personally, I’m not the biggest fan of these one-number impact metrics, but if you are going to use them, then at least make sure you use them properly. As the great Seth Partnow recently said in an article - “[E]ven the best ‘single number’ metrics are not measuring how good a player is. Rather they are measuring how effective they have been within the scheme and role in which they have been deployed.” This quote was in reference to defense, but it really applies to both sides of the ball, and does really well in capturing my gripes with one-number metrics (for reference, these are generally built around on-off plus-minus splits). Because the data used for these metrics is collected in a certain setting (opponent + teammates + scheme + role), the conclusions that you take away from the data only apply in that same exact context, despite many metrics’ attempts to filter out the noise. Read that last line again and again until it’s been drilled into your mind.
If you choose to parse through some one-number metrics you’ll find that players with a team built around their heliocentric role probably get overrated by these metrics because of, well, context. Now let’s go with the opposite - looking at KD’s impact metrics this year, he appears to be a clear cut below the league’s top crop. We know that’s not true though; so, what’s at play? Well (especially since trading for Harden), the Nets’ organizing principle is “48 minutes of high-level offense”. Because (post-injury) KD creates almost all of his value on offense, his offensive impact would determine his ‘value’ as a player. However, when KD goes to the bench, Brooklyn’s one-man shows (and I mean this in a good way) get to cook against weaker defenses, diminishing the offensive drop-off on paper.
Defense is even harder to measure. Beyond the role and scheme stuff, fluky opponent 3P% or FT% can really muck up small-to-medium-sized data samples in non-luck adjusting metrics. And that’s before we even take into which teammates a player regularly plays alongside, as well as the relative strength of opponent offenses when he’s on the court vs when he’s off it. There’s no real shortcut to evaluating a player’s defense; you have to watch the film. As a guy who knows a thing or two about basketball, Daryl Morey, recently said, “I would say public-domain, all-in-one defensive measures are all really bad. I think internally, several teams have some pretty OK ones, not good. Defense is hard…it’s so dependent on what the coach wants them to do.”
So, what can these all-in-one metrics be used for? If you were just getting into basketball and wanted to find out who the best players were, a list sorted by advanced metrics would be more effective than, for example, a list of players sorted by ppg. Rather than an exact measurement tool, these metrics are weather vanes - they’ll point you in the right direction, giving you a general idea of how impactful a player is. They should not be used to compare players - Player A is not better than Player B because his RAPM is higher. And finally, if you are going to use some all-in-one metrics, you may as well look at a bunch of them. Thankfully, BBall-Index’s free Impact Metric Comparison Tool allows you to do just that.
Do Not put too much stock in lineup stats, especially 5-man ones. 5-man lineups are usually composed of very small samples, making them incredibly fluky. @rd11490 has written about this, illustrating how quickly a 5-man lineup can go from world-beater to bottom-feeder. Furthermore, when looking at any lineup data, make sure to always check each team’s 3P%, especially opponent 3P%. Opponent 3P%, give or take several percentage points, is mostly luck; so, if you see a lineup that opponents shot 27% from 3 against, natural shooting variance is a more plausible explanation than, say, those 5 players discovering the secret to disrupting opponent shooters (by 10 percent!).
Let’s take a look at a recent example of what happens when people don’t understand what these defensive ‘metrics’ really mean (not to pick on the person in the example; it simply came up at a convenient time).
Beyond this first tweet being full of missteps, what I really want to focus on is the follow-up. This is true - CJ’s individual defensive rating, which is primarily based on how his team performs defensively while he is on the floor, is below (better than) the Trail Blazers’ average defensive rating. Yes, this is more or less citing pure on-off data, I process that I warned against earlier, but let’s entertain the proof for a second. When digging into what’s behind an impact, one of the first things I always do is take a peek at the Four Factors.
(For those who don’t know, the Four Factors, coined by Dean Oliver, are the 'four factors’ that constitute a team’s ORTG or DRTG. They are - EFG%, OREB%, TOV%, and FTAr, aka free throw attempt rate, which is free throw attempts per field goal attempt. All offensive/defensive success or failure can be attributed to these four factors.)
So, via CleaningTheGlass (I site that I will break down somewhere below), here is how CJ is affecting those Four Factors, culminating in Portland’s defense being 5.1 points better (-5.1, as on defense, fewer opponent points is better) per 100 possessions.
What should stand out is that almost all of CJ’s defensive impact is due to an incredible -5.2% decrease in opponent OREB% while he’s on the court! However, based on what we know about the 6’3 McCollum, defensive rebounding is neither his strength nor responsibility. Perhaps CJ has blossomed into an impressive rebounder under our noses? Well, from what can be quantified, he’s right in the middle of the pack when it comes to defensive rebounding among guards, and has boxed out a grand total of 7 times all season long. Rather, we can point to CJ playing 85% (1685/1985) of his possessions with either Enes Kanter or Jusuf Nurkic on the floor, while the team as a whole has only played 75% (3748/5025) of their possessions with one of the two on the court. And this all comes, not to forget, on one of the worst defensive teams in the league.
CJ’s case is more the rule than it is the exception; hopefully, I was able to illustrate why you should completely ignore some defensive metrics, and take others with a grain of salt. It’s ok not to have watched every single player play defense, and occasionally not have the answer to a certain question. There’s no shame in asking someone how a player has been faring on defense. On the other hand, there is some shame involved in misusing a stat to cover for a lack of homework.
The Stat Sites
Basketball-Reference
If you’re an NBA fan, you’re probably familiar with basketball-reference. It’s one of the first links that come up when you put a player’s name into Google. In the same vein, BballRef’s player pages are its main calling card, as they have all the basic counting stats, which you can look at through the per-game, totals, per-36 [minutes], or per-100-possessions lens. The “Advanced” section of their player page gives TS%, rate-adjusted counting stats (such as OREB%, STL%, etc.), FTAr, and 3PAr (percent of your FGA that are 3’s). Next up, the “Adjusted Shooting” section gives you a players’ various shooting %’s in relation to league-average, most useful for TS%. Scroll down a little more, and the “Shooting” section breaks down a player’s FGA and FG% by shot distance, as well as giving you their ASTD% on 2’s and 3’s.
For further depth (around the top of the page), these basic stats (raw and advanced) can be viewed through game logs (game-by-game) or splits, the latter of which stratifies a given season’s data in various different ways. If you want to know more about a player’s shooting, the “Shooting” page, which gives you a shot chart along with various splits, the most intriguing of the bunch being ASTD% by shot distance.
You can also view lineup data, although basketball reference is not the go-to destination for that data. If you go to a team’s page, you can see the individual stats for each player on the roster, which can be quite useful from time to time.
To conclude: Basketball-Reference gives you all the basics, embedded in a site that’s pretty straightforward and easy to navigate.
NBA.com/stats
NBA.com has a lot, and I mean a lot, of stuff to offer. So, let’s start by taking a look at what makes NBA.com different from the pack.
Go to NBA.com/stats, click “Sortable Player Stats” on the side, and you’re in. Now, what is the main stuff NBA.com has to offer? Well, click on the word “General” at the top of the page, and click on “Playtype”. Here, you can see how players fare when finishing (as defined by a shot attempt, free throw attempt, or turnover by the player) one of 11 playtypes, as tracked by Synergy. You can see PPP (points per play), possessions a game, FREQ (what percent of a player’s playtype usage the given playtype constitutes), and more. This tracking is, for the most part, extremely reliable. The 11 different playtypes are as follows: P&R - Ball Handler, Spot Up, Transition, Off Screen, Handoff, Isolation, Cut, Putbacks, Post Up, and P&R - Roll Man (it will always show you Isolation at first; to change playtypes, simply click on “Isolation” to bring up the menu and then click on your desired playtype). All along, make sure to keep in mind that these only count plays that the player finished with a shot attempt, free throw attempt, or turnover.
Now, click back on “Playtype”, except this time, select “Tracking”. By default, it will take you to “Drives”. As the title suggests, this will show you all relevant data regarding a player’s drives (I think that this only counts drives in the half-court, which is why Giannis may be so low). Regardless, this is incredibly useful, as the data is descriptive and measures tangible actions. Skip ahead and we get to “Passing”, which is glorious. The data is incredibly informative, providing context beyond plain assists, which are quite obviously flawed. In case not everything registers with you: Potential Assists, are, well, potential assists, regardless of whether the player made or missed the shot. Secondary Assists occur when a player passes the ball to a teammate, who within one second and without dribbling, records an assist; a hockey assist. Adjusted (ADJ) Assists are the combination of normal assists, Secondary Assists, and Free Throw Assists (when you pass to someone who goes to the line within the same parameters of a regular assist). Next, we have “Touches” with shows time of possession, touch, and dribble stats. This can be useful on its own, but is especially useful when looked at in tandem with other measures of production.
Clicking back on “Tracking”, now go to “Defense Dashboard”. As I said earlier, defense is incredibly hard to measure; however, we can use specific stats to illuminate certain parts of defense. The “Defense Dashboard” shows you the number of shots a player contests as well as the FG% on those contested shots, and those contests can be filtered by distance from the hoop (<6 feet, <10 feet, >15 feet, 2’s, and 3’s). To wrap it up, we have some fun stats in the “Box Outs” and “Hustle” sections, with my personal favorite being deflections, which are what you think they are, and can be found in the “Hustle” section.
Finally - there are many different types of tracking lenses through which you can view shooting attempts. You can view all players through a certain lens, but just to get an idea of all the filters that do exist, check out SGA’s shot dashboard here (touch time, dribbles, shot-clock time, and closest defender are among the different categories within which shot attempts can be broken down by).
pbpstats.com
I simply do not have the time to go over all that pbp offers. All I have to say is that if you have a question, pbpstats has the answer. Everything, from assists to shots to rebounds, is stratified by location (corner 3, above the break 3, long midrange, short midrange, and rim) thanks to tracking data access. Everything is incredibly detailed. You can view stats from multiple seasons grouped together, single seasons, filtered by dates, player stats, team stats (with a league average at the bottom), per-game, per 100 possessions, totals, etc. You can pull literally any concoction of lineup data, shot data filtered by anything, and download it all as a CSV. If you have a question about a pbpstats capability, feel free to reach out to someone; they might be able to help.
We’re starting to get into the paid sites territory, so I’ll kick it off with the paid version of pbpstats.com. I don’t actually have it, so I’m not speaking from experience here, but I’ve talked to people who do have it (hello, @crumpledjumper). Essentially, it takes nba.com’s exclusive tracking data (that we just went over above) and gives it the pbpstats makeover, allowing you to sort, filter, and view it in ways that nba.com doesn’t allow you to. This includes being able to use nba.com’s various shot filters. The other thing you unlock is hand-tracked passing location data (from the site’s founder).
CleaningTheGlass.com
Cleaningtheglass is the one paid site here that I actually do use. There are no raw numbers here - everything is represented as a %, and each player’s percentile in a given statistic, relative to their position, is shown. CTG’s player profiles (you can check out the section for free here, which should also give you a good idea of CTG’s clean and intuitive aesthetic). They also have a player’s shooting frequencies and accuracy broken down by the five zones (rim, short midrange, long midrange, corner 3, and above the break 3’s), with percentiles, of course. You can see ASTD%’s by the three zones (rim, mid, and 3) as well. While other sites have this, CleaningTheGlass presents this information in the most digestible way by far, thanks in special part to grouping different stats in different sections. Less is more. CTG also has team/opponent stats, focusing on the following areas: The Four Factors, shooting zones and frequencies, half-court offense (and putbacks), and transition stats (with these being incredibly helpful, as they show how many points a team adds per 100 possessions through transition, PPP, and frequency based off how the play started (as well as general frequency). CTG also has very detailed lineup data; although you can only view data one season at a time, you can see a wide variety of stats for each lineup, with solid player-specific filters when looking at team’s lineups (you can also see lineups from all around the league). And, if you’re ready to use it responsibly, you can see a wealth of on-off data for each player. However, we arguably haven’t even got to CTG’s main calling card, which is that it filters out garbage time!
Bball-Index.com
I don’t actually have Bball-Index, so I’m not speaking from direct experience here, but based on the graphs that their Twitter account puts out and browses through their Glossary, Bball-Index is fantastic. They take in tons of data (including all the tracking stuff that NBA.com has), contextualize it, manipulate it, and spit out metrics that tell you how good a player is, rather than how well he’s producing. One of my favorite things about them is that they go very, very deep; for example, although they have “Overall talent” grades, such as a player’s “Finishing talent”, you can still see how a player fairs in the various individual components of that metric - take this example below:
To be honest, part of the reason I don’t use bball-index is that it feels like I’m cheating. It just gives you soooo much info.
Synergy/InStat
These services cost a lot, as in, to the point where they can only be justified if you actually work in basketball. They have an obscene amount of tracking data, and can answer virtually any question, such as, for example, how many points per play (PPP) does a given player’s team score when he passes out of the P&R after the defense commits? Or, how many PPP do the Hawks score when Capela rolls out of the P&R? How about when he slips? Those are the types of answers that lie behind their paywall.
The Best of the Rest
Ultimately, there is an endless number of ways to record, interpret, and visualize NBA data - no one site can do it all. Beyond the sites I mentioned, there are lots of individual web apps that can do one or two things for you that cannot be found elsewhere. Saving me some work, Brett Kornfeld recently decided to compile all of these onto a google sheet here, with an explanation of each tool to boot. It’s a great collection, and I would definitely recommend checking it out.
Step 1.75 - How To Interpret Stats & A Basketball Philosophy Tie-In
Now that we know what the good stats are and where we can find them, it’s time to talk about how to perceive those stats. As I mentioned earlier, being a good offensive player means helping the team’s offense. Purely looking at a box score, not only is it hard to relate statistics to impact, but understanding how that impact came about is a challenge in and of itself. With that being said, let me present an example where I try my hand at the aforementioned task.
Two 20-Point Scorers
In this example, we’re going to be looking at 20-21 John Collins and 20-21 DeMar DeRozan (stats accurate as of the date I’m writing this). I chose these two players because they both average ~22 points per 75, and hence may look similar on paper. So, let’s add context via some simple statistics:
As we can see, Collins scores more efficiently, with his +6.1% rTS toppings DeRozan’s +1.5%. However, the overwhelming majority of Collins’ looks are created by others, whereas DeRozan self-creates most of his own, with his 29% ASTD% being a top mark in the league. Suddenly, despite near-similar scoring averages, DeRozan and Collins are starting to look very different as scorers! To throw in even more numbers: for every 36 minutes they spend on the court, DeRozan controls the ball for 5.7 minutes as opposed to Collins’ 1.7. Hence, despite both adding around 22 points a night, the points come about through two wildly different avenues, via the fulfillment of two distinct roles. Right about now, I’d like to introduce some basketball philosophy that may or may not be new to you.
Basketball Philosophy - Roles, “Fit”, and Synergy (aka, Basketball Interplay)
IMPORTANT EDIT:
In the year since publishing this piece, my views on the topics I’m about to discuss below have changed a little bit. Traditional roles, formulas, and structures (even the ones below, to some extent) are more-or-less obsolete. However, for someone just getting started with the sport, assuming a total, fluid understanding of all things between the player and the greater team’s ecosystem is absurd, and I do think that some rough groupings might have some initial value as training wheels of sorts. They can be used as crutches until one is fully fluent in offensive nuances, upon when they should shed their training wheels and take off.
(Note: the following is quite important). When looking at some-to-most players (offensively), you can think of them as somewhere between an offensive initiator/creator and a play-finisher:
A “creator” is a player who creates quality shots for himself and others, usually by putting himself in a prime position to score and/or draw extra attention. In special part due to the evolution of the modern game, thinking of players as ‘scorers’ or ‘playmakers’ is (for the most part an) inaccurate and outdated way of thinking. As teams’ best players are increasingly fed the ball, many of the league’s top offensive players are beginning to fit the LeBron/Harden/Luka model. It would be reductive to label these players as ‘scorers’ or ‘playmakers’, as they’re elite in both areas. Rather, they are ‘creators’, breaking down the defense over and over again, each time choosing to pass or shoot based on how the defense reacts to them. The right mix of scoring and passing chops is key, as having too little of either one can make you too predictable, putting a ceiling on how many on-ball reps you can effectively use. To spell it out: a great scorer will demand extra defensive attention (or should, at least). However, if he can’t make the right pass quick enough, setting up his team in a position to score, then, he’s faced with choosing between a difficult attempt and a turnover/idle pass that gives the defense time to recover. In the same vein, a gifted passer can’t set up his teammates if he himself is not a threat to score.
A quick aside on that: we often interchange passing, playmaking, and the like to the point where the words have come to more or less mean the same thing. As I just-just said a gifted passer’s capacity to create for others can be limited by the extent to which he is a threat to score. And at the end of the day, we care about what you can do in a game, not what you can do in an empty gym. Thus, a nice little term to use when referring to the practical application of one’s passing ability is “functional playmaking”. A good real-life example of this discrepancy is Lonzo Ball and Trae Young. Despite possessing similar levels of passing ability (aka, being able to exploit the same types of passing windows with similar speeds), Trae is a much more functional playmaker than Lonzo because he actually has the requisite off-the-bounce scoring gravity to create those windows in the first place. This is why I find the ‘playmaker’ label a bit misleading, among the many other gripes I have the way basketball is covered.
On the other hand, a “play-finisher” is a player who plays off the gravity/space created by others, punishing the defense for sending extra help and “finishing” the possession by putting up a good shot attempt. On paper, these are the players who may have a high ASTD%, a high proportion of shots taken with less than 2 dribbles, or a high proportion of shots taken after 2 dribbles or fewer. When watching a game, these are the players who catch lobs/finish layups or take catch-and-shoot 3’s, all open to some degree, thanks to the creator who drew in their defender in the first place.
There are, of course, exceptions. I’ll start with the big one. Wouldn’t my “creator” logic from above disqualify a player like KD, a prodigious scorer with lackluster passing ability, from being a top offensive force? Well, not exactly. The earlier note on the scoring/playmaking balance only applies to players operating with the ball. It is not very good at all if a player can only put himself into a position to score with the ball in his hands, but then can’t make the right pass when he draws extra defenders. However, what if a strong scorer/weak passer came up with a way to put himself in a good position to score without having to make a complicated passing decision? I present you with something called off-ball movement! (I would 100% recommend checking out the linked video that dives deeper into this concept, coming from none other than the Thinking Basketball Youtube Channel). It’s high-reward/low-risk - if a strong scorer/weak passer puts himself in a position to score and no one helps, then he can receive the ball and go to work. If he puts himself in a position to score and extra defensive attention does come, then the advantage can still be exploited by the right pass, as our strong scorer/weak passer does not have the ball in his hands and hence isn’t responsible for making the right decision. And beyond that, because off-ball movement, doesn’t, well, require the ball, probing around for the scoring opportunity off the ball doesn’t have to take time off the shot clock (aka, restrict scoring opportunities), as it can happen concurrently with an on-ball action on top of being the main action itself. Hence, off-ball scoring can scale up in a way that on-ball scoring can’t, as (simple math dictates that) there are 5 players on a team but only 1 ball. A guy like KD, whose ASTD% has hovered around 55% during his career, can live off a combination of on- and off-ball scoring, which allows him to score at an all-time rate while still handling lesser playmaking responsibilities. (Two interesting anecdotes here: 1. KD’s off-ball game allows him to scale, as we (perhaps regrettably) saw him take a team from all-time great to GOAT. 2. Noted in KD’s Greatest Peak video, Durant’s scoring efficiency noticeably dropped without his main co-star (Steph/Russ) on the court, which probably is indicative of his on-ball creation not being quite up there with the best of the best. Still, it’s a more-than-fair trade-off.)
If you look at the top scorers in the league, they are either prodigious passers or possess a significant off-ball component that adds some dynamo to their game (a random example I like: Bradley Beal, who’s been on a scoring tear since 2019, takes over half of his shots after 2 or fewer dribbles). You just rarely (never?) ever see game-breaking offensive talents lacking both passing and off-ball abilities. The guys who do often end up being 6th men, whose aesthetics and counting stats all-too-often overstate their impact on winning. (Fun side note - perceiving the game like this can help you with draft scouting, when imagining a player’s lower-level scoring might translate to the league).
A player like Draymond Green also fails to conform to this idea - he plays off of his teammates’ (Steph and Klay’s) scoring/shooting gravity, but rather than using that advantage to finish the play and score individually, he instead becomes another link in the chain, exploiting the scrambling defense by putting himself in a position to score, drawing even more defensive attention before finally passing to an open teammate for a great shot, not just a good one. This turns Draymond into a “creator” in his own right (or rather, a mix of the two), even though Dray does not possess the scoring ability/gravity to create his own advantages in an even 5v5 setting - he needs a teammate to create the initial advantage for him. It’s why Draymond and Steph have been such a lethal combo over the years - Steph bends the defense and Dray executes (Draymond is a safety valve of sorts for Curry, allowing him to outsource the playmaking/passing part of offensive execution). This unique skill set, based on the scenario (‘15-19 Warriors vs the ‘19-20 Warriors), can be either a blessing or a curse (not unlike KD’s on-ball/off-ball conundrum). To help connect theory to real, tangible basketball, check out some clips from the video below of Draymond doing everything that I just talked about.
(A small thing to notice in all of these clips - although Draymond can’t create advantages/command gravity by himself, his passing works so well here because, in a 4v3 setting (these usually start with some form of a Curry double), Draymond has an empty lane to roll into/dribble down, as Steph has already displaced Dray’s man for him. Almost all NBA players are a scoring threat in an open paint; it’s just getting there that’s the hard part.)
Many players fit that Draymond-ish role, creating offense (on-ball) against an already-bent defense, albeit in a more scoring-centric fashion. This is where the term “secondary initiator” or “secondary creator” comes into play. The Jazz are a great example of this, as they’ve cobbled together a top-3 offense despite lacking an elite, do-it-all offensive player; they create offense by committee. However, saying that they “play as a team” or “have good chemistry” completely undersells what Utah is actually doing. For example (please watch the video, it’s both quick and informative):
Many Utah possessions start off with Gobert setting a ball screen for one of Utah’s many capable ball-handlers/pull-up shooters. Gobert is a very large human, making his screens difficult to navigate. And once the screen has been navigated - in a way that doesn’t allow for a pull-up 3 from the ball-handler, often requiring the defending big man to play up to the level of the screen - you now have to worry about that same very large human (7’1” with a 7’0” wingspan, to be exact) rolling towards the rim and getting an easy dunk. Gobert’s rolls to the basket help compensate for Utah’s lack of driving threats (Mitchell, the best they have to offer, has trouble both getting to the rim and finishing while there); put together with Utah’s shooting gravity, and the Jazz can now imitate the gravity of an elite creator despite not actually having one. Advantage creation by committee.
In a similar vein, Utah divvies up the shot-creation duties as well. Let’s start out with a quick visual example:
As you can see, Utah doesn’t have a player who can carry entire possessions on his own, warping the defense before creating a favorable shot for himself or a teammate. In general, most good shots come from that process (warp defense -> shot created), but the process doesn’t have to be exclusive to one or two players. Rather, the Jazz utilize a robust collection of players who can shoot, dribble, and pass, together with a sharp offensive mind at the helm. As the clip illustrates, the advantage is initially created when Toronto momentarily commits two defenders to Mitchell. The first instance of “secondary creation” is when Bojan turns down the shot in favor of setting up Ingles; a lesser player would simply have shot it, as they may lack the on-ball skills to create a favorable shot out of the advantage. Ingles then keeps the advantage (which, just in case you forgot, essentially means that a defender is displaced) going, once again engaging in “secondary creation” (pump-faking, driving, and kicking-out), creating a wide-open 3 for O’Neal. The two clips below should help capture the immense value of the shoot-dribble-pass skillset:
(These sorts of players that can make these sorts of plays are incredibly valuable. Notice how all of Ingles’ touches in the clip(s) above don’t really come at the expense of others’ ones. Rather, they come within the flow of the game, seamlessly tacking on value to already-live possessions, which is where the true value of the secondary creator archetype lies.)
Secondary creation can take place off the ball, too; take, for example, this Kevin Huerter bucket:
To expand even further on the concept, check out the next clip where Huerter will move without the ball, creating some space thanks to Trae Young’s gravity, then receive the ball, and finally, cap it off with some drive-and-kick to create an open 3 in classic Utah Jazz fashion:
Now, somewhere above, I talked about how you can still be an uber-elite offensive player without being a tippity-top on-ball creator, which is via the use of off-ball movement (hello, Curry and Durant). I’d like to momentarily both re-visit and re-contextualize that concept. While some players can truly create shots for both themselves and others while roaming without the ball (just like Curry, the Platonic ideal of an off-ball player, does in the clip below), the majority of off-ball movers work their magic primarily to score themselves. For the most part, I like to put off-ball movers/scorers in the secondary creator box, because:
Off-ball scoring is a portable trait, meaning that it can seamlessly fit into and enhance any lineup it’s added to, as off-ball scoring doesn’t monopolize the ball.
Like secondary creation, it’s arguably amplified when slotted next to on-ball action, as it gives the defense two plays to navigate and supercharges your ability to punish help defense (as Huerter did in the first clip).
Moving off-ball, though, isn’t just an effort-fueled skill, although effort most certainly helps. Check out this short compilation featuring Bogdan Bogdanovic creating open shots for himself without the ball, playing hide and seek with his defender while darting around screens:
(These plays all end up in Bogi getting a good look from 3, which is, by all means, a win for the offense. Even if one of these plays had faltered out, the real play is still going, as Bogdanovic doesn’t even have the ball! Coming off a screen has all the upside without literally any risk. It’s no coincidence that Bogdanovic and the Hawks have been thriving since Nate McMillan took over and implemented more off-ball movement into the offense.)
Another useful secondary skill is “extra passing”. “Making the extra pass” is an age-old basketball trope, but it takes a lot more than “the willingness to do so” or something like that. It requires lightning-quick decision-making, as you need to keep the ball ahead of the defense’s recovery. It’s a place where great passers without much on-ball creation ability can shine, as the defense is already bent, simply requiring the right gap to be targeted. Pairing passing ability with a respectable shot can result in good extra passing; two great examples of this from the 20-21 season are Nicolas Batum and Lonzo ball:
Being able to attack and create out of closeouts (like Ingles), make the “extra pass” (Batum/Lonzo), move/relocate without the ball (primarily around the perimeter, like Bogi and Huerter do above), or cut are all great ancillary skills, turning good possessions into great ones and piling extra pressure onto the defense. These “secondary creators” are easy to overlook, as their #1 appeal is being able to play off of an on-ball creator, amplifying the offense, an ability which they can’t always display (through no fault of their own). (Ultimately, not every player can be perfectly fit into a box; at the very least, however, we can make our boxes better).
Let’s now pivot back to standard, primary creation for a sec. Take a look at the Young-Capela connection below, a play that encapsulates a lot of what I’ve been trying to get at, all in one.
This play encapsulates so many things:
This is a perfect example of how playmaking and scoring are intertwined. Yes, Trae has incredible vision, but Capela never gets open if Young isn’t a threat from deep. This is like the Jazz’s process, but put all into one. Trae creates a good shot (his pull-up 3), altering the geometry of the court, and then simultaneously leverages it into a great shot, a Capela dunk (hence the term, shot creation).
This also shows why catching the ball in the midrange area, jabbing 10 times, and then shooting the ball with a hand in your has extremely diminishing returns. The defense will never send any help at you, and hence you won’t ever create a great shot for any of your teammates, which puts a ceiling of sorts on the offense.
This helps illustrate why ranking/comparing players is often stupid (I’ll get to this later); this play would not be able to happen with two Clint Capelas running the show, nor with two Trae Youngs. Understanding how different skills interact with each other is really important, especially when it comes to better understanding the X’s and O’s side of the game. It’s also why stats can’t always be taken at face value. Most bigs screening for Trae Young could put up 6 or 8 points every game. It’s important that, when looking at a box score, we don’t equate those points with the 6 to 9 points that Trae pours in from pull-up 3’s each game. A cool way to quantify this is with Peter Zanca’s Shotmaking App, with looks at a player’s shot quality, EFG%, and the difference between the two (although, it does omit free throws, which are incredibly efficient).
To wrap up the philosophy section, I want to tackle some things that I think are pretty important.
Rules of Thumb
MOTION IS IMPORTANT - A common misconception is, in my opinion, conflating 5-out basketball, or having 5 shooters on the court, with “spacing”. This obviously doesn’t apply to extreme situations, such as only having two legit shooting threats on the court, but rather when we get near the peak of spacing and nuance becomes more important. When you think of optimal spacing, the 19-20 (post-deadline) Rockets may come to mind. 5 shooters on the court at all times! However, as the Lakers’ round-2 defense against the Rockets showed (or rather, as Zach Lower chronicled; you need to read this, it’s basically my thesis here), static 5-out spacing isn’t really the peak of spacing; it can be gamed/systemically approached. Guarding statues, no matter what they shoot from 3, simplifies the defense’s task. Rather, it’s motion that creates space. Take this clip below, in which I examine how the Mavericks generated a wide-open 3.
(The main takeaway here - space is created by motion. The open shot is created because THJ counter-intuitively cuts towards the ball, which should, in theory, clog up the paint, in this case, Luka’s driving lane. However, it does the exact opposite. As long as THJ is on the move, Batum will have to trail him, lest he lose track of THJ and concede a wide-open shot. The whole idea of spacing, really, is forcing defenders to cover more ground. It’s why the use of the 3-point line has “spaced” out today’s game. So, by similar logic, with Batum totally occupied, there are only 4 Clippers left to cover the entire court, stretching out, or rather, spacing out, the defense.)
Also, read this fantastic article by Mike Prada that dives deep into all things motion, approaching the topic by taking a look at each of the four 2020 NBA Conference Finalists.
2. 3P% =/= Spacing, Shooting Talent, or Anything Like That - 3P% seems, on the surface, like a near-perfect measure to capture how good someone is at shooting 3’s. However, that’s actually pretty far from the truth. A good rule of thumb is that:
Unless you’re a special 3-point shooter, in-game, players don’t really have the time to think about whether you shoot 35% or 37% from 3; all they’re worried about is whether the shot is going up or not. So, volume matters. And you know what else matters? Shot versatility. Shot versatility and volume aren’t a 1:1 measure, although the players that get more 3’s up probably have a few more tricks up their sleeve. Let’s take two Atlanta Hawks, John Collins and Bogdan Bogdanovic. Since the 2018-19 season, Bogi is shooting 38.6% on 6.5 3’s a game, while Collins is shooting 37.9% on 3.1 3’s a game. The volume rule of thumb tells us that Bogdanovic is the more impactful floor spacer, but let’s examine why; how did that rule come about? Well, go watch some John Collins 3’s, and then compare those 3’s to the Bogdanovic ones from above. While Collins is definitely one of the better big men in this regard, most of his 3’s still come from a standstill. Because he doesn’t move into gaps that often, nor attack closeouts off the dribble, teams don’t hug up on him like they do with other shooters. Sometimes, Collins functions more like a release valve, a guy who when left open on the perimeter can hit 3’s, but not really a top priority for the defense; the attention the Collins demands on defense varies from team to team. A better example of this is a guy like Brook Lopez, who despite being billed as a “floor-spacer” often ends up taking shots dictated by the defense. This is usually the case for big men due to three factors:
Not being able to attack closeouts,
Not being able to shoot off movement
Or having a slower release
(Henry Ward talked about this on Sense & Scalability). That gives the defense a massive margin for error, as they can ignore you up until you shoot, and then close out hard to contest the shot. However, when you can leverage pure shooting ability with any combination of the above traits, you can truly “space” the floor and open up opportunities for others, as Huerter does above.
(A couple of things to note here:
Solomon Hill’s unwillingness to let it fly, paired with his lack of off-the-dribble juice, allows the defense to sag off him; volume matters, folks.
Huerter uses off-ball movement to leverage his shooting gravity, creating a quick 3v2 advantage on the left side of the court.)
And this is all, of course, before getting to a whole ‘nother universe of 3-point shooting: pull-up 3’s. Looking at the % of a player’s 3’s that are assisted, alongside volume and accuracy can seriously help you out when trying to get a good idea of a player’s 3-point shooting. Another avenue is to check out nba.com’s tracking stats (as covered earlier), where you can see a player’s volume/accuracy for both C&S and pull-up 3’s. Often, on-ball creators are tasked with taking harder, deeper, off-the-dribble 3’s, which is why guys like Harden, Trae, or Luka can be massively underrated when simply looking at 3P%. Yes, a Luka 3 isn’t as efficient as a THJ one, but offense requires that pull-up 3’s be taken, and someone has to fire those pull-up 3’s. Rather than comparing Luka’s 35% to THJ’s 40%, compare Luka’s % on pull-up 3’s to his teammate’s % on pull-ups (spoiler alert: he’s the best they’ve got)
Now, with some of the many nuances of basketball finally explored, let’s pivot to one of my biggest gripes with basketball coverage: player comparison.
Don’t get me wrong, there’s nothing wrong with comparing players; it can be quite fun, and fun is most definitely encouraged. However, we all too often gravitate towards comparing players in a 1v1 context, occasionally overvaluing 1v1 skills (on-ball defense, isolation scoring) in the process; this doesn’t exactly come out of nowhere, as many people experience basketball in a 1v1 setting on the regular, but we need to learn to detach ourselves from that line of thinking. It’s really hard to compare players across roles, as two different players who man two different roles, for the most part, could each have a strong case at being more impactful than the other if presented with the right team context. And, when making these comparisons, my main issue is that an inflated emphasis gets placed on 1v1 skills. Let’s take two Jazz bench players: Jordan Clarkson and Joe Ingles.
Despite Clarkson being the current front-runner for the PPG award (otherwise known as the “6th Man” award), I would argue that Ingles is a better player. Sure, Clarkson can create more offense for himself if you give him the ball and clear out (or set a ball-screen for him), but Ingles, as you saw above, can seamlessly fit into and amplify any offense by shooting the lights out the ball, attacking closeouts, making smart/quick decisions and moving a bit without the ball. When comparing two players, we all-too-often break it down to the lowest common denominator - “put these two players on a team of bums and see who’s better”. Rather, I would encourage you to compare players through the lens of how they can contribute to a good/already-good team. Ingles can bottom out as an elite spacer/C&S threat, impacting the game without the ball up until you need him to do more, which is when he can put his shoot-dribble-pass skillset to use, creating offense like we saw him do above.
This is all for Part 1! (Or rather, this is all for the first edition, as Part 2 will simply be added on at the end here). Still to come is the second in your journey towards being a smarter fan. (Spoiler alert - the secret sauce is to read articles from people that are smarter than you). There, I will list a ton (like seriously, a ton) of the top writers to read if you want to improve your understanding of X’s and O’s, player mechanics, analytics, and more! (In the meantime though, make sure you read everything Nekias Duncan, Mike Prada, PD Web, and Caitlin Cooper have to offer). I’ll also sprinkle in all the film-watching advice I’ve been able to collect while working on this, as well as the behind-the-scenes process of how I watch and break down film, for what it’s worth. Thanks for reading, and stay tuned for more!