# Should he shoot? Looking at the data of selfishness – Part 3

In part 1 and part 2, we looked at selfishness from two different perspectives, one a graphical chart and one a more traditional table. I’ve combined these two visualizations into this single chart. It looks much like the first chart, but an added slider allows you to filter by players’ SE rank. Thus, you can quickly identify, say, the top 10 players in terms of SE without having the leave the visual view. I plan to update this data every once in a while and, when I do, will only present the results in this view.

I’m now going to use these data to make some suggestions about how offenses, specifically the Houston Rockets offense, should operate. My comments are based on a few assumptions.

1. Players selfishness and eFG% are negatively correlated. In other words, the higher a player’s selfishness, the lower his eFG%. This is due to players’ shot selection becoming poorer by taking more shots. Here’s a graphical presentation of what I mean:

The more selfish this player is, the lower his eFG% is

2. The strength of the relationship between selfishness and eFG% is different for each player. Some can take more shots without a huge change in eFG%, while some will see a huge change in eFG% by taking more shots. In math, we would call this the slope of each player’s line. In economics, we would call this the elasticity of each player’s eFG%. Here’s a graphical representation of what I mean:

Can take lots of shots without a large decrease in eFG%

Big drop in eFG% by taking a few more shots

3. Some players are just better shooters than others (or at least shooting better presently). Everything else being equal (i.e., they take the exact same shots under the exact same circumstances), player A will have a higher eFG% than player B. In math, we would call this each player’s constant. Here’s a graphical representation of what I mean:

Good shooter, notice he starts out higher on eFG%

Poor shooter, notice he starts out lower on eFG%

Here’s my premise. An inefficient offense is one in which the players are far apart on their eFG%. This means that, in the team’s current offense, some players have a much better likelihood of making their shots than others at the players’ respective rates of selfishness. In this case, players who are shooting better than others should be more selfish, and players who are shooting worse than others should be less selfish. Thus, a perfectly efficient offense is one in which the players have very similar eFG%s; basically the players would be situated in a near vertical line on the chart. Every team has this theoretical line. Let’s call it the line of awesome. Here’s what it would look like:

Notice how all players are very close to the line of awesome

Where on the x-axis (eFG%) a team’s line of awesome would cross depends on the shooting abilities (constant) of each player. How high or low each player would be on his team’s line of awesome depends on each player’s capacity to absorb more shots without decreasing his eFG% (slope, or elasticity). If players’ are close to their team’s line of awesome, this means that every player is being as aggressive as he should within his own capacity relative to everyone else on the team.

OK, enough jabber. Onto the Houston Rockets. Here’s the Houston Rockets offense from the chart:

The good news is that everyone is actually above-average in eFG% and is kind of close together vertically. In fact, if you compare the Rockets to other teams, the Rockets are doing quite a bit better than most others. Some teams just look completely hopeless. However, the Rockets can still make some improvements.

The two players that appear to be farthest away from the Rockets’ theoretical line of awesome are Harden and Beverley. As it stands, every additional shot that these two take has a less likely chance of going in than an additional shot taken by five of their teammates. So even though James Harden is shooting the ball at a reasonably good rate, it just so happens that his teammates, at their current rates of selfishness, are shooting the ball at an even better rate.

The simply stated solution is for Harden and Beverley to pass the ball more when they touch it. But that doesn’t mean Harden should start passing up fast break dunks. And it doesn’t mean Chandler Parsons should just chuck the ball every time he has it and expect his shots to magically fall. It means that Harden should not take the most difficult shots he currently does, and that Parsons et al should take the least difficult shots that they currently pass up given their capacities and styles of play. So Harden should keep taking fast break dunks, but pass up the double teamed step-back 18 footers that he takes. And Parsons should take the somewhat-contested three-pointer he’s on the fence about.

About the author: Richard Li is an independent researcher and consultant. He likes numbers and pictures.

• thejohnnygold says 2 YEARs ago

Everything you need to know about our turnover problems. Note the highlighted usage rates for our top 4 culprits. It goes from the highest with Harden, to Howard, to Lin, to Asik. To clarify, this means Asik is worst, then Lin, Howard, and finally Harden.

• thenit says 2 YEARs ago

Lin averages close to 3 as well.

But Harden and Howard was both in top 10 in turnovers per 100 touches which I think is more accurate measure than per game.

• Richard Li says 2 YEARs ago

I agree that Harden should probably pass to Howard more. However, I think Howard's eFG% is a little inflated because he seems to turn the ball over quite a bit. I'm not sure what the actual stats are on his TOs but I feel like he dominates 1 on 1 but turns it over when double teamed. Drawing a double team should be a good thing, though, as long as he passes out of it.

If we're going to talk turnovers, we can't excuse James Harden. He averages 3.6 TOs per 36 minutes, which is actually higher than Howard's 3.2. Maybe another reason he should pass the ball.

• Steven says 2 YEARs ago

Dwight averages about 3 TO's per game which equates to roughly 1 out of every 5 post touches.

Overall, his 16.6 TO% is in line with his career averages and usg%. It's just part of the package.

Anyone else remember the "team" he took to the Finals. It was the second worse team to ever reach the finals (LeBron's swept team being the worst). Skip to My Lou was the PG (Nelson was hurt, Lowry was brought in for Rafer, wow Morey was stealing players even back then), a rookie Courtney Lee, Hugo Turkolgu was the playmaker and Rashard Lewis the stretch 4. Talk about casting fear into the other team.
• thejohnnygold says 2 YEARs ago

Dwight averages about 3 TO's per game which equates to roughly 1 out of every 5 post touches.

Overall, his 16.6 TO% is in line with his career averages and usg%. It's just part of the package.

• bluemars says 2 YEARs ago

I agree that Harden should probably pass to Howard more. However, I think Howard's eFG% is a little inflated because he seems to turn the ball over quite a bit. I'm not sure what the actual stats are on his TOs but I feel like he dominates 1 on 1 but turns it over when double teamed. Drawing a double team should be a good thing, though, as long as he passes out of it.

• redfaithful says 2 YEARs ago

Great stuff as usual!

Two questions:

1. Visualization - can you create a 3D bars version of the teams graph where each team has a bar whose height corresponds to the win%? It could reveal currently hidden win% related patterns.

2. Tried to think about ways to measure defensive selfishness, to create a similar graph which shows how much each player contributes in 1x1 defense against help defense. No ideas so far :( Do you have any thoughts about that?

• Red94 says 2 YEARs ago New post: Selfishness revisited
By: Richard Li

[caption id="attachment_13850" align="aligncenter" width="300"> Click to view a full-sized, interactive version[/caption>

Last month, I took a lengthy look at selfishness in the NBA.  I wanted to identify which players were the most selfish, and whether that selfishness correlated with success. Since we're at the half way point of the season, I decided to revisit the same concept with updated data, and also analyze the data from a team level in addition to the individual level.

Technical information

This is largely explained in the initial post, so I'll be quick. The measure of selfishness I'm using is touches per pass (TPP). A high number indicates more selfishness (touches the ball more before passing it), and a low number indicates less selfishness (touches the ball less before passing it). Players' TPP are plotted against their effective field goal percentage, because if you're not going to pass it, then you better make your shots. All units are in standard deviations. Players were only included if they played at least 25 games and averaged at least 22 minutes per game.

A slider in the upper right allows you to toggle between the two times when I've collected data. You can also filter by team to examine each team individually. Mouse over for more data about individual players.

At the top left is a tab you can click to view the same graph but from a team level instead of an individual level. The size of each team's dot indicates that team's winning percentage.

Limitations

Data for players is not weighted by games or minutes played. Players who have switched teams are shown on their current teams. Data is also calculated from the beginning of the season through specified dates, not in separate segments. In other words, the data for January 20th is not from December 3rd to January 20th, but from the beginning of the season to January 20th.

Data for teams is complete, incorporating all data from every player who has logged a minute. However, players that have switched teams via trades are not included in the team analysis.

Observations

Looking at the individual chart, the Houston Rockets have not changed their offensive strategy very much since December 3rd. The most noticeable difference is that Dwight Howard has becomes a little more selfish and a little more effective from the floor. That's certainly a good sign. Everyone else has actually regressed slightly in their eFG%. Time will tell whether players are either going through a slump, or are simply playing at their real levels now.

The Rockets are still somewhat close to achieving their theoretical line of awesome. Given Howard's emergence, James Harden should probably make it a point to be less selfish. As it stands, he was the only player besides Howard to increase in selfishness. Unlike Howard, however, his eFG% did not increase. A team like Charlotte is actually very close to achieving their theoretical line of awesome. Unfortunately for them, their line of awesome appears to be pretty far left on the eFG%. They just don't have the offensive talent to score a bunch of points, even though they're playing efficiently relative to everyone's capacity.

On the team chart, the Rockets as a whole are slightly more selfish than average, but are also shooting the third highest eFG% in the league, undoubtedly due to their three-point volume.

Winning percentage does not seem to correlate with selfishness. This probably isn't a huge surprise since the chart does not consider defense at all. More interesting is that selfishness also does not appear to correlate with eFG%. While there are excellent offensive teams who are very unselfish (Heat, Spurs), the least selfish teams are pretty putrid offensively (Bobcats, Utah). That probably indicates that there's a difference between passing to get a good shot and passing because no one can shoot.

• Richard Li says 2 YEARs ago

Thanks for the great discussion, everyone. Lots of neat ideas!

@bluemars

I would love to plot players' elasticity. Unfortunately, game-level data from SportsVU is unavailable, or at least unavailable to me. So we're a bit limited in what we're able to do. I also can't identify where a team's line of awesome would be without knowing what the players' elasticities are. It's a shame, because something I would really like to chart using this same analysis is the Lakers offense pre- and post- Kobe's return. I think the results would be very telling.

I'm generally not a fan of the assist statistic. I think it has the pitfalls of baseball's error and save all rolled into one. First, the definition of what is and is not an assist is subjective and varies from one arena's scorekeeper to another (I think I read that the Clippers scorekeeper severely overcounts assists). Second, it's dependent upon the recipient of a pass making a shot. Great passes but missed shots don't count as anything.

@thejonnygold

Generally speaking I think a player like Russell Westbrook can do what he does without hoisting the ill-fated shots at the end. He can penetrate and create for his teammates but does not have to shoot a low eFG% himself. As a general caveat, what this cart does not capture is pace/volume. There is a point at which a larger number of bad shots results in more points than a smaller number of good shots. And this would skew the chart such that players who can get up and down the court faster would be taking more poor shots. Maybe this is what Westbrook is doing.

@Sir Thursday

I agree that each player's elasticity will be different. And I certainly think that Harden's capacity to absorb more shots without suffering a precipitous drop in eFG% is greater than everyone else's on the team. But like bluemars said, this is reflected in the concept of the line of awesome. Not every player shoots the same amount on the line of awesome. They just shoot the same eFG%. For example, let's say the Rockets line of awesome is as 50% eFG%. Harden might shoot 20 times per game and still reach 50% eFG%, whereas Terence Jones might shoot 6 times per game to reach 50% eFG%. You just don't want any one player to be much higher or lower than the team's line of awesome given his current selfishness rate. That would imply the player is either over or underutilized, and that the player should adjust his selfishness rate until that is no longer the case.

• Sir Thursday says 2 YEARs ago

I think you're right and I did make a mistake in how I was thinking about this (regarding percentages vs. absolute values).

However, I think it's still slightly more complex than you make it out to be. In the scenario you suggest, by moving some shots from Harden to Parsons we increase Harden's eFG% from 50%-51% and decrease Parsons' from 60%-58%. Because of this, you can't just consider the shots that have been redistributed - you have to factor in that all of Parsons' shots are less likely to go in and all of Harden's more likely.

The strength of this effect will depend on the differences in elasticity between players - I was imagining that there might be much wilder variation in terms of eFG% than in your example above. Asking, say, Garcia to shoot three more times per game would knock more than a couple of percentage points off, I think. But that point is moot unless we have some hard numbers to pore over. Nevertheless, the optimum distribution is still not going to be perpendicular - this effect will deform it slightly, since we approach the line there is less to be gained from moving still closer but the elasticity effect will remain.

ST

• bluemars says 2 YEARs ago

Sir Thursday, I think I understand what you are saying but I actually really like the notion of "line of awesome". The theoretical line of awesome that Richard Li is talking about is not necessarily a perpendicular line through the mean of eFG% for each player. In fact, this theoretical line may be lower than the mean eFG% precisely because of the argument that you make. Taking shots from say, James Harden, and giving them to Chandler Parsons may decrease Parson's eFG% more than it increases James Harden's. (Not knocking Chandler or James just using them because of their positions on the chart.) Let's say that taking one shot from James and giving it Chandler increases James's eFG% from 50 to 51% but decreases Chandler's from 60% to 58%. This is still a better situation because that shot has a 58% chance of going in versus a 50% chance of going in! This argument continues to hold until Chandler and James's eFG% are the same. In the end, James will be taking a lot more shots than Chandler, but we are at "optimal efficiency". Hence, the line of awesome!

Also, I appreciate the shoutout to my idea for measuring elasticity by player but as I mentioned in my post I'm not sure this would necessarily be a good way to measure whether a player should be shooting more. As I said previously,

"In this case, it would be tempting to say that low elasticity implies a player can maintain eFG% at higher shot volumes. However, there is the confounding factor that the player is choosing to shoot based on what is happening during the game. Suppose a player has very high "true elasticity", meaning if we told him to take more shots per game his eFG% would drop significantly. However, this player only shoots in situations where he has a good chance of making the basket. The player would appear to have low elasticity because the eFG% would be roughly constant even as the number of shots changes per game (due to the player having more good looks in some games rather than others).

"More than anything, I think this metric would measure a player's intelligence with respect to shot selection. If we see a high elasticity of eFG% then when the player increases the number of shots in a game, he is taking worse shots. If we see a low elasticity then the player is taking more shots because he is getting more good looks.

"If we could somehow get a measure of the number of good looks per game, we could control for this confounder and get a sense of the "true elasticity" (e.g. How good is a player at making difficult shots. Will this player be able to maintain eFG% if we told him to increase his shot volume?). Sadly, this measure would be very difficult to assess and certainly not widely available."

I am very much enjoying this data-oriented conversation :)

• thejohnnygold says 2 YEARs ago

I agree with you, Sir Thursday. For a while now I have referred to this (in my head) as the "Russell Westbrook Effect". He has long been panned for his poor efficiency, shot selection, and reckless play. Yet, he is the catalyst that makes OKC's offense go. His Tasmanian Devil attack wreaks havoc on defenses which opens up the floor for guys like Durant, Ibaka, Sefolosha, etc. His injury proved as much as OKC was unable to maintain their overall effectiveness once he went down last year.

Another thing I noticed was the San Antonio Spurs. Their "line" is nearly perpendicular to the proposed "line of awesome" (I presume that original line was conjured just to give a general notion and that individual teams' styles and players may necessitate a different orientation.) Further, only one of them ventured into the selfish zone which supports the notion that their offense skews the line of awesome because they play a more team-oriented version of the game. Only Kawhi Leonard crossed that selfish threshold. Meanwhile, Tim Duncan's eFG% was lowest alluding to him bearing the burden of carrying the offense at times. That last assumption may just be a result of a slow start to the season for him...I look forward to re-visiting this later and seeing how it has evolved.

Harden does bear this burden for the Rockets--and does so very well. I would need to take some time to research it, but in my head it seems that the players best suited to this purpose/role are also able and willing passers. Otherwise, the result ends up looking very stagnant. Carmelo and Kobe tend to fall into this trap. Both are capable passers, but the willingness doesn't always seem to be there. On the flip side, Lebron, Harden, Paul, Lin and (bear with me) Brandon Jennings fulfill this role very well. (I have watched most of Detroit's games this year and, aside from a terrible turnover problem, Jennings is playing great basketball on both ends of the floor.)

All of this definitely bears more investigation...

• Sir Thursday says 2 YEARs ago

I really like these articles - the data they present is very interesting! However, I have a slight quibble with the conclusion of the study. I don't think it's necessarily the case that the 'line of awesome' is the optimal offence for a team. In fact, I think the way the Rockets' offence is on that graph could well be the best way to set things up.

The reason I think that assumption needs challenging is that I don't think it's a given that you would see a constant slope on the graph for an individual player. There are a lot of role players in this league who would not be able to operate as the focal point of an offence. For these players, there would be a maximum USG% beyond which their efficiency would sharply tail off. If you are trying to rearrange shot allocations to make the team more efficient, you have to make sure the marginal gain in efficiency from decreasing the usage of a high-volume player exceeds the marginal loss from increasing the usage of these role players. This is not necessarily going to be the same as getting everyone to shoot the same eFG%, especially if increasing the usage of a player takes them over that efficiency cliff.

I propose an alternative way of looking at things. If you were able to draw a graph of elasticity for each player like BlueMars suggests, then you could identify where these efficiency cliffs are. In an ideal lineup, you could take each player on the court's optimum USG% and it would add up to 100%. Then you'd split up possessions accordingly. If it added up to more than 100%, you would have to decrease the touches of some of the players from their optimum. However, if the optimums summed to less than 100%, then you would have to select one or more players to handle some extra possessions. And you would choose the player whose efficiency doesn't fall off a cliff when he is given more load.

The above is an interesting situation because it is the one you find many 'Star' players who advanced metrics are disdainful of in. In a vacuum, yes you would want Carmelo to shoot a little less and distribute some of those possessions elsewhere. But if the rest of the Knicks are at their optimums then someone has to use some extra possessions and take the efficiency hit, and Carmelo is almost certainly the best player to do it on the team.

I hypothesize that the Rockets are a team in such a situation. Players like Casspi, Garcia and Jones are being asked to do exactly as much as they should be while they are on the court - any more and they would not be able to put up the efficiency they are doing at the moment. Harden is the guy picking up the slack, and as a result his efficiency suffers a bit.

Does that make any sense? It does in my head, but I'm not certain I've articulated it very well.

ST

• thejohnnygold says 2 YEARs ago

In response to the request for two different types of data I have some tidbits.

First, 82games.com offers some data on when shots are taken (early, middle, late shot clock); however, I have found their data sometimes questionable--so take it with a grain of salt. They also use what they call "crunch" stats which I believe measure end of game when the score is close shooting stats. I just took a quick glance at Parsons (as he is on my fantasy team and I lament every 30 ft. heave he takes at the end of the shot clock because our ball movement was terrible) and they say about 11% of his total shots are taken with less than 4 seconds on the clock. That does not mean they are all bad shots so, again, grains of salt.

Second, basketball-reference.com, has added a new feature that has lots of nifty little stats. One of these is basically points created. It tries to account for the points generated from assists (I doubt they count hockey assists). The data is only available for previous seasons right now. Here is Jeremy Lin's.

James Harden was credited with 1098 points off assists and he registered 455 assists last season which translates to 2.4 points per assist credited. I haven't done any comps for scale, but that seems very, very good. It certainly alludes to our penchant for kick-out threes and the success of those shooters. (On a side note, why don't passes that lead to made foul shots get credited for the assist? I don't understand that rule. Is it because technically there was no fg attempt?)

Shot selection seems to be something that can only be graded with the eyes. That would require watching games and subjectively keeping tallies for each player. Who wants to volunteer for that one? :unsure:

An example: I was watching a Bulls game the other day. It was nearing the end of the first half and the Bulls were trying to get one more shot in before the buzzer. Mike Dunleavy was camped in the right corner and got an outlet pass with about 3 seconds on the clock. He was about to put up the three, paused and realized there was no one between him and the basket as the other team was doubling up top. He brought the ball down, took two quick dribbles and dropped in a lay up at the buzzer. His awareness of everything going on was very impressive to me. None of that finds its way to the stat sheet.

• bluemars says 2 YEARs ago

I am a PhD student in data analysis and I approve of this post. Maybe you could rank teams by standard deviation of their eFG% giving us a sense of which teams are closer to their line of awesome?

I would also love to see elasticity by player, looking at the data on a per game basis. In this case, it would be tempting to say that low elasticity implies a player can maintain eFG% at higher shot volumes. However, there is the confounding factor that the player is choosing to shoot based on what is happening during the game. Suppose a player has very high "true elasticity", meaning if we told him to take more shots per game his eFG% would drop significantly. However, this player only shoots in situations where he has a good chance of making the basket. The player would appear to have low elasticity because the eFG% would be roughly constant even as the number of shots changes per game (due to the player having more good looks in some games rather than others).

More than anything, I think this metric would measure a player's intelligence with respect to shot selection. If we see a high elasticity of eFG% then when the player increases the number of shots in a game, he is taking worse shots. If we see a low elasticity then the player is taking more shots because he is getting more good looks.

If we could somehow get a measure of the number of good looks per game, we could control for this confounder and get a sense of the "true elasticity" (e.g. How good is a player at making difficult shots. Will this player be able to maintain eFG% if we told him to increase his shot volume?). Sadly, this measure would be very difficult to assess and certainly not widely available.

Also any thoughts on my suggestion about a chart with unselfishness on one axis and assists per pass on another? This way we get a sense of how much someone passes and whether those passes turn into points just like your first post showed how much someone shoot and whether those shots turn into points.

• goRockets says 2 YEARs ago

You should show this to Morey, he'd like it.

• Chichos says 2 YEARs ago

Amazing explination of the basics before moving onto the meat of the analysis.

One thought though, all shots are currently weighted evenly but we know that shots late in the shot clock have to be shot or we lose the ball to a 24 second violation. I think shots taken in the last 4 seconds or so shouldn't be weighted as heavily as the rest since. It would be the same idea as not counting half court heaves at the end of the half but obviously they still have to have some weight as they are part of standard offense.

If there is a way to see if Harden and Beverly are shooting a disproportionate amount of shots late in the shot clock that might explain some of their movement away from the line of awesome. I am especially expecting it from Harden since he purposely dribbles until there is no time left and then takes a step back or kicks it to his release valve, often Beverly, who has to immediately throw it up.

I'm not sure if time left on shot clock when shot was taken is a stat anywhere, but in an age where NBA offenses go through three stages of offense in 24 seconds it definitely needs to be taken into account.

• redfaithful says 2 YEARs ago

While the obvious focus is on Harden, this graph also confirms that Beverley's shots aren't falling like others on the team. Being the most unselfish by this analysis is great, but I sure hope he regains his scoring touch, hopefully soon.

• Rahat Huq says 2 YEARs ago

Very interesting and confirms the eye test. Harden could be MVP caliber if he bent his back on defense and stopped settling for bad shots. It took Lebron James until I believe age 26 to figure out the latter. Let's hope Harden gets it as he ages. Right now, I suspect he's still basking in being a team's #1 option, something he didn't enjoy from the start like other superstars did. Once the playoff losses pile up, he'll change. As far as the defense though..

• Red94 says 2 YEARs ago New post: Should he shoot? Looking at the data of selfishness - Part 3
By: Richard Li

In part 1 and part 2, we looked at selfishness from two different perspectives, one a graphical chart and one a more traditional table. I've combined these two visualizations into this single chart. It looks much like the first chart, but an added slider allows you to filter by players' SE rank. Thus, you can quickly identify, say, the top 10 players in terms of SE without having the leave the visual view. I plan to update this data every once in a while and, when I do, will only present the results in this view.

I'm now going to use these data to make some suggestions about how offenses, specifically the Houston Rockets offense, should operate. My comments are based on a few assumptions.

1. Players selfishness and eFG% are negatively correlated. In other words, the higher a player's selfishness, the lower his eFG%. This is due to players' shot selection becoming poorer by taking more shots. Here's a graphical presentation of what I mean:

[caption id="" align="aligncenter" width="360"> The more selfish this player is, the lower his eFG% is[/caption>

2. The strength of the relationship between selfishness and eFG% is different for each player. Some can take more shots without a huge change in eFG%, while some will see a huge change in eFG% by taking more shots. In math, we would call this the slope of each player's line. In economics, we would call this the elasticity of each player's eFG%. Here's a graphical representation of what I mean:

[caption id="" align="alignleft" width="225"> Can take lots of shots without a large decrease in eFG%[/caption>

[caption id="" align="alignleft" width="225"> Big drop in eFG% by taking a few more shots[/caption>

3. Some players are just better shooters than others (or at least shooting better presently). Everything else being equal (i.e., they take the exact same shots under the exact same circumstances), player A will have a higher eFG% than player B. In math, we would call this each player's constant. Here's a graphical representation of what I mean:

[caption id="" align="alignleft" width="225"> Good shooter, notice he starts out higher on eFG%[/caption>

[caption id="" align="alignleft" width="225"> Poor shooter, notice he starts out lower on eFG%[/caption>

Here's my premise. An inefficient offense is one in which the players are far apart on their eFG%. This means that, in the team's current offense, some players have a much better likelihood of making their shots than others at the players' respective rates of selfishness. In this case, players who are shooting better than others should be more selfish, and players who are shooting worse than others should be less selfish. Thus, a perfectly efficient offense is one in which the players have very similar eFG%s; basically the players would be situated in a near vertical line on the chart. Every team has this theoretical line. Let's call it the line of awesome. Here's what it would look like:

[caption id="" align="aligncenter" width="449"> Notice how all players are very close to the line of awesome[/caption>

Where on the x-axis (eFG%) a team's line of awesome would cross depends on the shooting abilities (constant) of each player. How high or low each player would be on his team's line of awesome depends on each player's capacity to absorb more shots without decreasing his eFG% (slope, or elasticity). If players' are close to their team's line of awesome, this means that every player is being as aggressive as he should within his own capacity relative to everyone else on the team.

OK, enough jabber. Onto the Houston Rockets. Here's the Houston Rockets offense from the chart:

The good news is that everyone is actually above-average in eFG% and is kind of close together vertically. In fact, if you compare the Rockets to other teams, the Rockets are doing quite a bit better than most others. Some teams just look completely hopeless. However, the Rockets can still make some improvements.

The two players that appear to be farthest away from the Rockets' theoretical line of awesome are Harden and Beverley. As it stands, every additional shot that these two take has a less likely chance of going in than an additional shot taken by five of their teammates. So even though James Harden is shooting the ball at a reasonably good rate, it just so happens that his teammates, at their current rates of selfishness, are shooting the ball at an even better rate.

The simply stated solution is for Harden and Beverley to pass the ball more when they touch it. But that doesn't mean Harden should start passing up fast break dunks. And it doesn't mean Chandler Parsons should just chuck the ball every time he has it and expect his shots to magically fall. It means that Harden should not take the most difficult shots he currently does, and that Parsons et al should take the least difficult shots that they currently pass up given their capacities and styles of play. So Harden should keep taking fast break dunks, but pass up the double teamed step-back 18 footers that he takes. And Parsons should take the somewhat-contested three-pointer he's on the fence about.

• ale11 says 2 YEARs ago

Very nice job, very interesting stuff and easily understandable. Keep it up!

• Richard Li says 2 YEARs ago

I, too, like the chart better than the tables. As you mentioned, and as I also mentioned in part 2, compressing a multi-directional chart into a one-dimensional list results in compressing information. Basically, some integrity is lost. But it does allow us to compare two players like Kyle Korver (low selfishness, super high eFG%) and Klay Thompson (super high selfishness, above average eFG%). In the end, it's just another way to look at the same information, one that has advantages and disadvantages. Some might prefer it, while others might not.

Part 3 will actually combine both the chart and the table into one chart, and to some extent the chart from part 1 and tables from part 2 were lead-ins to this final chart. Hopefully that will be an efficient way to fulfill more people's data visualization preferences.

• bluemars says 2 YEARs ago

I like your chart with selfishness and eFG% in the previous post. I find this chart to be more interpretable than the SE measure, which seems to be not much more than an attempt to project the selfishness vs. eFG% chart into one dimension. I think it would also be interesting to see a chart with selfishness on one axis and assists per pass on the other, allowing us to compare their selfishness with passing efficiency.

• thenit says 2 YEARs ago Good job, very interesting
• Red94 says 2 YEARs ago New post: Should he shoot? Looking at the data of selfishness – Part 2
By: Richard Li

In part 1, we plotted players' selfishness against their eFG%. Now we're going to turn the four-quadrant chart into a ranked list. The two measures we are focusing on are touches per pass (TPP, our measure of selfishness) and selfishness efficiency (SE, a combination of how selfish a player is and how well he shoots).

Because SE essentially forces the chart, which has data in all directions, into a straight line, some sacrifices have to be made. As mentioned in part 1, because SE uses the standard deviation of eFG%, it is great for analyzing the extremes (players who shoot really well and really poorly). However, players who are average shooters will have an eFG% stand deviation close to zero, and thus their SE will also be close to zero, or basically average.

With that being said, the results of TPP and SE are displayed in the following tables (click for a full-size interactive version).

All columns are sortable (except team, which you can filter). The first table shows players' touches per game, passes per game, TPP, and their TPP rank. The second table shows players'  TPP, eFG%, SE, and SE rank.

Thought 1 - Visual Team Chemistry

Using the visual representation, we can also analyze players’ tendencies from individual teams and begin to understand how those teams operate offensively. Houston, for example, has one selfish player (Harden), who fortunately also shoots a high eFG%, with everyone else in the unselfish/high eFG% quadrant (Howard is on the cusp). The Spurs take unselfishness to another level, with almost everyone in the unselfish half of the chart (only Kawhi Leonard is barely selfish).

Of course, the quadrant that teams do not want players in is II, selfish and low eFG%. That signifies ball-stopping, iso-inclined players whose shots don’t fall. The Knicks and Raptors both have two players in this quadrant (Anthony/Smith and Gay/Derozan, respectively). Probably not fun to be on those teams. Though no team is as selfish and horrible as the Sacramento Kings, who have a whopping four players in the quadrant.

NOTE: This data was collected before Rudy Gay was traded to the Kings. The Kings have now added arguably the most selfish and poor shooting player to inarguably the most selfish and poor shooting team (they didn't trade away any of their selfish/poor shooting players). This could become very disastrous and/or hilarious.

Thought 2 - Roles Matter

Expectedly, a player’s role is strongly related to how selfish he is. The most selfish players (i.e., the ones who pass the least per touch), as measured by TPP, tend to be ball-hogging, isolation-happy, prone-to-chucking wings. Players like Eric Gordon, Nick Young, Rudy Gay, Demar DeRozan (eek, Raptors), and Carmelo Anthony are all in the top 10. The least selfish players (i.e., the ones who pass the most per touch), as measured by TPP, are pure point guards who are poor scorers, like Ricky Rubio and Shaun Livingston, and hustle/defense guys, like Joakim Noah and Anderson Varejao.

For selfish efficiency, spot up shooters top the list. This makes sense, considering their job is to seek out extremely open (usually three point) shots and not pass them up. Thus, we see the likes of Kyle Korver and Klay Thompson in the top 10. Range-limited big men also congregate near the top, likely due to their high percentage shot selection (Drummond, Dalembert, DeAndre Jordan). At the bottom are aforementioned volume-scoring wings (Rudy Gay again, and JR Smith makes an unsurprising appearance), and also players who are having terrible shooting seasons, like the entire Brooklyn Nets roster.

Thought 3 - Defying Expectations

Since players’ roles greatly influence their selfishness and selfish efficiency measures, players who buck those trends, one way or another, should be acknowledged. Considering how central he is to pretty much everything, Lebron James’s SE is unbelievable. He is ranked fifth, sandwiched between three-point specialists and dunkers. There isn’t even another star wing player in the top 30. In comparison, Carmelo Anthony’s SE ranks him at 166. For the same reasons, Chandler Parsons (11th) and Trevor Ariza (13th) also have impressive SEs.

While paint-clogging big men tend to have high SEs, their stretch counterparts can become very inefficient. Pau Gasol, Kelly Olynyk, and Kevin Garnett are all in the bottom 30 for SE.

In part 3, we'll talk Houston Rockets using these data.

• Richard Li says 2 YEARs ago

It's not embedded. I tried embedding it and the size just wasn't big enough. Right now it's a static image in the post that links to tableau's site.

• NorEastern says 2 YEARs ago

Nice! It is going to take me a while to go through this in depth, but how did you imbed the tableau graph like that?

• redfaithful says 2 YEARs ago

Oh, forgot Rudy Gay and Carmelo...

• redfaithful says 2 YEARs ago

Great idea! The players far from the middle are most interesting - Klay Thompson, Nash, Battier, Korver and of course LBJ.

Could be interesting to look at it at the team level - calculate a team weighted average (weights being minutes), and create a similar graph for the teams. It will show team tendency to pass the ball against eFG%, should be insightful...