Written by Ben Heller, ‘Rocketscience’ is a column devoted to basketball analytics.  Ben Heller can be contacted at heller.benjaminj@gmail.com.

ESPN’s John Hollinger already made somewhat accurate trade grades (insider only) – though I believe he underrated Brooks’ upside – so I’ll avoid any type of “grading” here with a “stats-light” rundown of the deals last week:

Brooks Trade

Aaron Brooks will recover from this injury (the Suns have an excellent training staff), and when he does, Pheonix will be very happy with this trade.   Much like the Battier trade, the Rockets exchanged a rental for future assets.  We weren’t willing to pay Brooks and probably aren’t going to make the playoffs, so it makes sense to get something in return that will carry into next season.

As for Dragic, he’s the type of player that will impact the game one way or another.  Much like Lowry, he pushes the tempo and has both a high assist ratio (32.25% this season) and high turnover ratio (20.68%).   As he matures, the hope is that he will sharpen his decision making and cut down the turnovers.  My biggest concern, however, is that he has been largely more successful the past two seasons as a shooting guard.   Here are a few notes:

1.       Last season (considered by some as his mini-breakout year), while shooting a 52.7 eFG%, he was assisted on 39.6% of his shots.  That is a high number for typical point guards, which means that others were creating a lot of his shots (ie. Nash).  This season, his shooting has dropped to a 46.8 eFG%, and only 28.6% of his made shots are assisted.

2.       His net PER* this season is -3.7 at point guard, and +2.0 as a shooting guard.

3.       His most effective 5-man unit** this year had Nash at point guard.  However, it was his 9^th most common combination (by minutes played) in Phoenix, and the only unit in the top 10 most common with Nash playing beside him.

Battier Trade

We did not follow through with the Battier trade so that we could snag an underperforming Hasheem Thabeet and somehow turn him into a respectable player.  It was possibly for the pick, but a late first-rounder several years from now doesn’t have much value now.  The other day Clyde Drexler fittingly said this trade was addition by subtraction.  By allowing Budinger to start and Terrence Williams to enter the rotation, the Rockets will start getting more out of its prospects.

In his two games as a starter, Budinger is averaging 17.5 points per game, but expect that number to fall a little bit.  He’s shooting 58% from the field and 50% on 3-pointers which, while encouraging, is more likely due to a boost in confidence than something to rely upon moving forward.  His per-48 minute scoring has increased since becoming a starter (27.5 vs. 21.6), but his attempts per-48 minutes have actually decreased (15.0 vs. 19.1).   That can be explained by his new role as a starter, as he now has to find his shots after Scola, Martin, and Lowry.  Moving forward, expect him to put up modest, but efficient scoring numbers.

Conventional wisdom says that adding Budinger and subtracting Battier will hurt the Rockets defensively.  Against my better judgment, there are indications that Budinger has actually been more effective defensively than Battier this season.  According to 82games.com, Battier has allowed opponent small forwards to shoot 52.1 eFG% and 16.0 PER, while Budinger has held opponent small forwards to 45.4 eFG% and 12.9 PER.   A similar metric is the On-court, Off-court opponent eFG% (a team stat instead of individual).  Opponents have shot 48.2 eFG% with Budinger on the court this season, and 51.1% when off.  When Battier was on the court, opponents shot 51.0%, and 48.6% when off.  Battier is getting older.  Since 2005-2006, Battier has never had a negative on-court/off-court net opponent eFG% for a season until this year.

As for Terrence Williams, I am not overly optimistic.  Despite the constant comparisons to T-Mac (which I still do not understand), the other T will never be a star (see what I did there?).  Here are a few reasons:

1.        No stats:  He’s finally getting playing time.  What has he done so far in just over 17 total minutes?  He’s made 4 of 12 shots, turned the ball over twice, gotten blocked once, and committed two fouls – all of which can be summarized with a -13 plus/minus, which he managed in two Rockets wins.

2.       Body language:  He doesn’t put his hands up when playing on-ball defense.  He pouts when things don’t go his way.  He doesn’t always hustle, especially after making a bad play.

3.       Defense:  I’ve seen him miss two rotations badly in the past two games (one of which almost got Brad Miller posterized).  He’s also not very consistent on the ball or in boxing out.

Here’s a simple, but perfectly appropriate quote from former NBA Finals MVP Chauncey Billups on Sunday, “Most of defense is just effort and being willing to do it.”  By the time a player gets to the NBA (with a few exceptions), defense is no longer x’s and o’s, but merely a confrontation between human nature and willpower.  T-Will knows what he’s supposed to do, but he doesn’t do it.  He’s the kind of guy that thinks everything is just happening to him, while throwing up his hands and making excuses.  For the sake of the Rockets, I hope he decides to start taking ownership and becomes the player he thinks he already is.

* own PER minus opponent counterpart PER, courtesy of 82games.com

**1.49 Off vs. .74 Def with a plus 19 +/-, 82games.com

Written by Ben Heller, ‘Rocketscience’ is a column devoted to basketball analytics.  Ben Heller can be contacted at heller.benjaminj@gmail.com.

I ran some regressions comparing win% (and just for fun, ESPN.com’s Hollinger Power Rankings) to each of the “Four Factors” to see which are most correlated to winning.  Guess what?  It was eFG% by a landslide.  Here is a summary table:*The neat thing about looking at differentials is it completely takes into account both offense and defense.   When taking this information and trying to apply it to individual players, it’s more difficult to find accurate defensive numbers (82games.com is perhaps the best that I have found), but looking at offensive numbers is quite easy.

On that note, what are some things that Shane Battier and Chuck Hayes have in common?  For starters, they both have “defense-first” mentalities, having excellent reputations as stoppers.  Also, they are both phenomenal locker room presences, and could possibly become future coaches under the right circumstances.  Something you may not have considered?  They are the most efficient scorers by eFG% on the Rockets, and rank near the top of the league.  Hayes ranks 16th in the league (56.3%), and Battier 19th (55.9%).**  Take those two players off the Rockets, who are averaging a 49.81 eFG% on the season, and the Rockets would go from ranking 12th in the league in eFG% to 20th.***

Sure, Hayes gets blocked over 16% of the time, probably because of his height and playing style.  But one player we may be seeking out of a Battier-to-Celtics trade? Kendrick Perkins, the league leader in getting stuffed, with an incredible 20.4% of his shots getting rejected.

It is likely that we feel pressure to pull the trigger on our expiring contracts to get at least something for their rental value for the rest of the season.   Battier has immense value for a team like Boston, but parting with any of their contributing players is not likely.  Something like Jermaine O’Neal, Avery Bradley, and a pick for Battier may something along the lines of what they are considering.

Whatever happens, I firmly believe that this team will crumble down the stretch if both players are dealt, and will suffer a worse second-half record down the stretch if either player is traded.

*A couple notes:  The “Diff” that you are seeing is the differential between own and opponent averages.  For example, Miami had a 51.56 eFG%, with an opponent 46.56 eFG%, yielding a positive 5.3% diff.  Also, the Hollinger number used for the regressions was actually 31 minus the Hollinger power ranking, just to flip the sign and be consistent with win%.

**25+ min/game minimum

***eFG% drops to 49.005% if you remove Battier and Hayes’ shooting.  I know this is an inexact science, but it is interesting nonetheless.  One potential flaw in this consideration is that Battier is assisted on 76% of his shots and Hayes is assisted on 52% of his shots.  Those are somewhat high numbers, speaking to their roles on the team offensively, and the type of shots they are attempting.  Namely, Hayes gets a lot of open layups and Battier gets a lot of open three-pointers.

Written by Ben Heller, ‘Rocketscience’ is a column devoted to basketball analytics.  Ben Heller can be contacted at heller.benjaminj@gmail.com.

The answer to that question is beyond this post, but we can at least take a look at the team-level for wins and losses.  According to nbastuffer.com, there are 18 teams in the league with an analytics department, or at least affiliation with analytics consultants.  Without delving too deeply into the depth of each team’s analytical reliance, I compared the records of “analytics” teams vs. “non-analytics” teams with regard to above .500 and below .500 opponents.  Here is the full breakdown:

And here are the winning percentages:

I was hoping for a defining relationship that would be similar to the Houston/Portland problem, but found a somewhat different trend.*  It looks like teams that incorporate some form of advanced analytics have better records – both against good teams and bad teams.  On top of that, I think an argument could be made that the top teams are winning despite that handicap.  The Bulls are loaded with talent and have excellent coaching in Thibodeau.  New Orleans would be nowhere without Chris Paul.   Finally, the Jazz have one of the best coaches in the league and the hardest offense to guard in the league.

Of course, you could make the coaching/talent argument with some of the top analytical teams too, but of San Antonio, Boston, LA, and Dallas, how much of their talent was a result of their draft position and how much was a result of a keener eye?  Besides Duncan, the Spurs’ best players are Ginobili (57^th overall), Parker (28^th overall), and Hill (26^th overall).   The Celtics found Rondo at 21^st overall, LA got Kobe at 13^th, and Dallas traded a Tractor Trailer for Dirk Nowitzki.

I’m not sure what else to conclude from this, other than 1) the Rockets’ woes against above .500 teams should not be attributed to the team’s penchant for advanced analytics, and 2) getting poor draft position is no excuse for losing.

*One way to take a better look at these records would be to expand the data back to include a couple more seasons, and to make some adjustment for the team’s overall record (because, for example, the Spurs are going to have a good record against both good and bad teams).

Written by Ben Heller, ‘Rocketscience’ is a column devoted to basketball analytics.  Ben Heller can be contacted at heller.benjaminj@gmail.com.

Take all of those emotions – the self-doubt, disappointment, solitude – and tack on millions of dollars worth of pressure to perform well.  That’s what Aaron Brooks is dealing with.  After this season, Brooks will become a restricted free agent, which means he has a very strong incentive to be out on the court and showcase his abilities.   The market for point guards the past few years has been generous, to say the least, with Mike Conley (5yrs, $40 mil) leading the way.  There is a decent chance that, if he can at least show that he is capable of being the player he was last year, he can find his way into a large deal (at least relatively large within the new CBA).   That would force the Rockets into a tough decision of either potentially overpaying Brooks or losing a valuable asset and receiving nothing in return.  Either way, Brooks gets paid, and gets to play for a team that just proved they really want him.

If I were Aaron, this is how I would be looking at this situation:  tough it out during this injury and do what it takes to show that you can still play.  Aside from his team needing him and his impending contract situation, there are more tangible reasons to believe that Brooks came back way too soon from his ankle injury.   A lot of basketball players are in a constant state of pain-management, with more of a sliding scale of toleration than a black and white road map.  For a tough player like Brooks, the possibility of him taking something to numb the pain before games is not out of the question.* Given his aforementioned situation, any relief that allows him to play is a blessing.  The only problem with numbing the pain for a game (or not numbing the pain and just sucking it up) is that it prolongs the injury, and makes it especially painful the following couple of days, which leads me to an observation I made about Brook’s per-48 minute productivity this season:

When Brooks gets more rest, he performs better.  He is more aggressive in finding his own shot, and makes a significantly higher percentage of his looks.  Unfortunately, he has a contract to worry about, so must be out on the court regardless of how his ankle feels.

When asked if he felt he still had something to prove, Brooks said, “I guess I do…I’m a work in progress. I’m not satisfied with myself. I’ve got a lot of work to do.”**  For now, I just hope Aaron works on getting healthy.

*I am most certainly not referring to anything banned or considered unethical, it might even be Advil.

**source: Houston Chronicle

I did two things with this analysis.  First, I compared totals of certain minutes-adjusted statistics (we’ll broadly call it “productivity”) from prior seasons to this season.  Those are already aggregated at a number of different websites, and this time I went with Hoopdata.  From that data I can conclude if there is a trend in productivity from season to season.  Next, I broke down the past couple of seasons on a per-game basis, paying no attention to whatever particular season in which the games were played.  That way I could see if there were differences in productivity due to the “role” or “mindset” of Lowry from season to season, or if it is simply a product of minutes played.

Per Season Productivity – Data

Click to Enlarge

First things first, a few of Lowry’s productivity metrics by season are actually teetering on career-worst levels.  Career lows include TS% (51.8%), DRR (9.7%), And1% (1.4%), FTR (.38), and charges (took his first of the season vs. Orlando…his first!  Through 41 games last year he had already taken 32 charges).   Other stats that are below his average are ORR (4.3%), FT% (72%), FG% (40.6%, though his eFG% has not been bothered due to his taking and making more threes), and from ESPN.com, Points/40min (13.4), and Rebounds/40min (4.8).

It should be noted that he has made improvements in three-point shooting and assists, but I think those improvements only reinforce my analysis:

Per Season Productivity – Analysis

Before I begin, let me say that there are an incredible number of variables that are not controlled in this sample, including injuries, coaching strategy, supporting cast, time of year (only the first half of this season), shoe brand, etc.  Understanding that all NBA stats (especially ones you see from me) are noisy, let’s pretend these are somewhat reliable and can actually allow us to draw conclusions.

From what I see, there is a significant drop-off in all of Lowry’s “hustle” stats, which can loosely be defined as stats accumulated through a combination of effort and a willingness to put your body in harm’s way.  On offense, driving to the basket and drawing a foul requires more effort, and puts a player in more dangerous situations, than passing or settling for a three-point shot.  On defense, the ultimate hustle stat is perhaps charges taken,* as it requires both effort and incredible exposure to injury (or at least pain).   Well, is it really just a coincidence that immediately after signing a fat contract, Lowry’s hustle-related productivity has plummeted?  He is taking (settling for) more threes, taking less free throws, grabbing less rebounds (I’m especially concerned with his ORR, which has really been his bread and butter), and taking significantly less charges.  If that is not a concern, I don’t know what is.   In my mind, a big part of what differentiates Lowry from other point guards in the league is his success in the aforementioned categories.

One possible explanation for this drop off in productivity is that, given his increased minutes and importance to the team, he is both conserving energy so that he can play the whole game and limiting his risk of injury so that he will be there for us every game.  The first point is what I’m about to test, but think for a minute about the second point:  in his young career he has witnessed first-hand two superstar teammates suffer career-destroying injuries, and then the starting point guard of his team lose his job after an injury (interpret cause-effect however you want).  From that angle, he is not only protecting his longevity in the league, but also perhaps looking out for our best interests by limiting the chances of another heart-breaking Rockets injury.**

Game Log Productivity – Inputs

The only way to debunk the “fat contract” and “self preservation” theories that I have just proposed is to show that Lowry’s productivity is more a product of minutes played in that particular game, rather than expected minutes (or average minutes) of that entire season.  In an attempt to control for Lowry’s progress as a player,*** I only included game logs from the past three seasons in the data set.   I compared minutes played to some selected “hustle” stats – TRR, Charges, and FTA.  I’m going to do a simple linear regression for each variable independently, with minutes played being the independent variable and TRR, Charges/48min, and FTA/48min being the dependent variables.  For each, I looked to see if there is a significant relationship between minutes played.  The idea is that if there is a significant (negative) relationship, it’s just a coincidence that Lowry’s hustle numbers are down this year, because his productivity numbers are a result of playing time (something that has increased significantly this year).  If there is no relationship, however, we must conclude that his fall-off must be due to some other reason – maybe even one of my theories.

Game Log Productivity – Analysis

After looking at several different angles with his data, it looks like there is no significant relationship between minutes played and hustle productivity.  Correlation numbers between minutes and the three stats were all insignificant.  I did some more statistics-based calculations and did not find any significant relationship.  Here is a simplified chart showing Lowry’s productivity in banded ranges of minutes:

As you can see, there is nothing to look at, but the lack of relationship is just as informative.  Regardless of Lowry’s playing time, he is generally consistent in his productivity.  The argument that he is conserving energy when he plays big minutes clearly is not valid.   Instead, Lowry’s dip in productivity this year – especially in those stats related to hustle – must be attributable to something other than his playing time.

* On a side note, I believe taking a charge to be the best defensive play in basketball (with zero research to back up that assertion).  It draws a foul, eliminates a high-percentage attempt, and forces a turnover.  It is criminal that this stat is not part of the box score.  While I’m on the subject, it should actually be two stats – successful charges and attempted charges (that resulted in blocks), and then a ratio.

** I of course am staunchly against any type of self-preservation strategy in basketball, especially when it negates your (Lowry’s) biggest advantages on the court.

*** I lied; Hoopdata only went back three seasons for Lowry, so that’s all I have.

That being said, I was hoping to open the floor to you all regarding the use of statistics – both in the NBA in general and here at Red94.    Clearly there are several different uses for statistics.  Coaches, scouts, and management (and sometimes players) use statistics (at varying levels of sophistication..) to gain any advantage possible, whether it’s on the court or through player transactions.

From the fan’s perspective, the level of statistical depth depends on both the will and sophistication of the observer.   While it’s fun to play “armchair GM” (and I’ll be the first to do it), there comes the sobering reality that whatever conclusions you draw, the actual decision-makers will always be more informed with better information.   So, to the observer whose career does not depend on the accuracy of his conclusions, given limited data and resources, isn’t it almost futile to compete?  Gone are the days of any advantage being drawn from the antiquated box score – even advanced derived metrics like PER.

My question is, what is the biggest reason you all are interested in basketball statistics?  Is it more out of passive interest, the urge to play “armchair GM”,  or to just better understand the game? (or something else?)  Genuine responses are appreciated – I’ll try to cater future posts to your interests.

In an attempt to revisit the topic of shot locations, which I have covered in the past here, here, and here, let’s take a look at where the Rockets stand so far this season.

Rockets Offense:

Close 2-pointers

-26.7% of shot attempts are at the rim, 15^th best in the league (27.2% league average)

-19.8% of shot attempts are  <10 ft, 3^rd best (16.3% league average)

Long 2-pointers (considered by many to be “bad” shots)

-7.6% of shot attempts are from 10-15 ft, 25^th (9.1% league average)

-20.3% of shot attempts are from 16-23 ft, 26^th (25.0% league average)

3-pointers

-25.6% of shot attempts, 8^th best (22.5% average)

FTR

33.3 rating, 5^th best (30.9 average)

Analysis:

The Rockets have an obvious game plan that looks to maximize free throws, at-rim shots, and 3-pointers.  On top of that impressively low number of long 2-pointers (16.8 attempts per game), 4.5 of them are from Luis Scola, who is shooting an impressive 49% from that distance this year.  On paper, the Rockets are a borderline elite team offensively.  I am of the opinion that we usually don’t lose games because of our offense, which leads me to…

Rockets Defense:

Opp-Close 2-pointers

-27.4% of opponent shot attempts are at the rim, 11^th worst

-17.2% of opponent shot attempts are  <10 ft, 7^th worst

Opp-Long 2-pointers (looks good until you look at FG% given up from these spots)

-9.6% of opponent shots 10-15 ft, 8^th best (but 40.3 FG%, 9^th worst)

-27.1% of opponent shots 16-23 ft, 8^th best (but 42.0 FG%, 3^rd worst)

Opp-3-pointers

18.7% of opponent shots, best in the NBA, but 55.7 eFG% allowed, 9^th worst

Opp-FTR

30.6 rating, 16^th worst

Analysis:

These rankings suggest that the Rockets are doing two things.  First, we are chasing opponents off of the 3-point line – I saw Shane Battier do it about 8 times last night against Paul Pierce.  As I have mentioned before, 3-pointers are the highest percentage shot behind “at rim” shots and free throws, with a current league average of 54.1 eFG%.  Second, the Rockets are deliberately forcing opponents to take long 2-pointers, possibly by sagging once the opposing player is inside the arc.  Unfortunately when we leave them more open their FG% will increase, causing that game plan to have diminishing returns.  Furthermore, it seems like a good number of those 2-point attempts are close to the rim, which means that, perhaps at least partially due to our chasing players off the 3-point line, opponents are getting deeper into our defense than we would like.  This causes us to have a slightly below average opponent free throw rate as well.

What are the implications?  Nothing new, I suppose.  Adelman is an offensive mastermind, but puts less emphasis on the defensive end.  One takeaway might be that we are closer to being an excellent team than our record would indicate.  Imagine if we improved our defense just enough to be slightly above average?  With our current game plan of chasing opponents off the 3-point line, we would need to fortify the lane with more active and athletic (and disciplined) bigs.  That could perhaps be achieved through developing our current crop of players (if such development was emphasized…).  We would need to practice rotations and help defense significantly more to prevent easy attempts at the rim – something that is possible but not probable, given our coaching staff.

The alternative to minor changes?  Red fans often argue about whether or not blowing up the roster is a good move.  Fantasies of (purported) offensive wizards like Carmelo Anthony perhaps blind us of the problem that has plagued us for years now.  We are already good at scoring the ball.  Really, really good.  If we were to do something drastic (while keeping coaching the same), my vote would be to go after a group of players that are motivated to be dominant defensively without needing a coach to show them how.  Battier and Hayes are good examples of that mindset, but they lack the overall games to be franchise players, and of course are getting older.  I imagine players like Andre Iguodala, Dwight Howard, and Chris Paul (long shots…) are higher up on Morey’s list right now than ‘Melo.

Here’s a look at Budinger’s TS% and points per 48 minutes this season.  Points per 48 minutes is a good way of normalizing points per game for minutes, removing the statistical boost normally generated from increased playing time.

Click to Enlarge

Click to Enlarge

Let’s go through the major arguments in favor of the trade right now, before anyone blows a gasket:

1. Shane Battier is a winner.  Ignore the mainstream stats, because they are misleading.  He always finds ways to win.
2. He is an excellent person, and will always be a source of leadership in the locker room as well as on the court.
3. We had Yao Ming and Tracy McGrady in their primes.  We had to win now, not develop rookies.
4. We also got to dump Stromile Swift, for what it’s worth.

For the most part, all of those arguments were valid.  Shane has not disappointed, and has generally delivered exactly what we expected.  He was a part of the magical 22 game win streak and has always held himself and his teammates to the highest standards.  My biggest concern, however, is reason #3, which is in many ways a disastrous mindset.  I know, hindsight is 20/20, and it’s a lot easier to say win-now failed after your two superstars get irreparably injured.  However, how else can we form a basis for decision-making if not by learning from the past?

Also, before I continue, I want to clarify that I am not entirely enthralled by Rudy Gay.  His combination of flashy dunks and high per-game numbers make casual observer drool.  However, he is a volume scorer with mediocre scoring efficiency.  Here are some stats on Gay to prove my point, courtesy of HoopData.com:

The league average for usage this year is 18.42, true shooting percentage is 54.1%, and percent assisted is 60.0%.  He also has marginal shot selection, which contributes to his percentages.  Over his career, 58% of his shots have been beyond 10 feet, with 62% of those (37% overall) coming from 10-23 feet (inside the 3-point line).

On the other hand, Shane Battier has been more efficient and has much better advanced statistics.  As my “pseudo-control”, I decided to compare Battier’s first 5 years in the league (with the Grizzlies) to Gay’s first five years (also with the Grizzlies).

Let’s first circle back to the aforementioned shooting statistics.  Now scoring is one of Rudy Gay’s special gifts, right?  I think we can also agree that Battier is a pretty ugly scorer some times.  However, despite different usage, they have had similar efficiency**:

It gets interesting when you compare yet more advanced metrics:

Battier is more active on the court, contributing to a higher percentage of every statistic other than defensive rebounding, while turning the ball over less.   Judging by offensive and defensive ratings, Battier was clearly superior.  If those numbers don’t show you what Dawson and Morey saw five years ago, these will:

Win shares are an estimate of the number of wins contributed by a player as a result of his offensive, defensive, or combined contributions.  The WS/48 number represents a per-48 minute number of wins contributed, with the average sitting at approximately 0.1.   If there was any doubt that Battier is a winner, even when he was on the Grizzlies, I hope that this comparison puts that argument to rest. In a final attempt at empathizing with our management at the time of the trade, I will concede that we were very, very close to being a special team, and Shane Battier was perhaps the perfect role-player for us at the time.  We knew he had a limited shelf-life, but it would be worth it as long as we could make a few pushes for the title.

That being said, here is the part where I am going to lose you:  If I was the GM at the time, I would not have made this trade.  The short-term approach to winning is really what irks me, and while Battier is a remarkable person, we acquired him for the back half of his career.  Wait until he retires and hire him as a coach if you like his “presence.”  Actually, if you like defense so much, don’t fire Jeff Van Gundy.  As demonstrated above, Battier is an excellent player.   What’s not demonstrated above is how Gay may have faired the past five seasons if he had a few years to develop with the Rockets under some of the best coaches and players in the league.  Young players on bad teams develop bad habits, and Gay might forever be a different player because of his perceived role on that Grizzlies team, especially after the Gasol trade.  Then again, maybe he is getting better every year, and last summer proved that he can be an incredible role player on a winning team.  Oh yeah, and he’s still only 24 years old.

*The trade was July 12, 2006; Morey became GM May 10, 2007

**Courtesy of BasketballReference.com

The topic of interest today is the seeming disconnect between his strong pursuit of a “star” and his disbelief in the value of “clutch players.”  According to 82games.com, clutch is defined as “4th quarter or overtime, less than 5 minutes left, neither team ahead by more than 5 points.”  In the 2009-2010 regular season, 172 games, or 13.98% of all games played, were decided by 3 points or less.   That’s a pretty high number of games that come down to clutch situations.  Last season the Rockets were 5-5 in games decided by 3 points or less, and 20-20 in games decided by 4 to 9 points.  For a GM purportedly not interested in clutch players or statistics, it has to be a concern that the Rockets are already 2-4 this year in games decided by 3 points or less, and 4-5 in games decided by 4 to 9 points.

Circling back, we know that Morey has potentially made conflicting assertions.  If a star’s usage increases during clutch time, it seems that the need for a star is concurrently exacerbated during clutch time.  With such marginal clutch performances last year, followed by a downward trend thus far this year, I am starting to believe that Morey may have misled us in his apparent disregard for clutch-time statistics.  After all, actions speak louder than words, and his intentions this past off-season were in clear pursuit of a big-time star and legitimate go-to player in the clutch.  So, before we blindly go with the assumption that Morey actually does look at clutch statistics, let’s take a look at some of the evidence supporting this view.

I wanted to see if there is any difference in wins for a team leaning heavily on one player in the clutch versus a conglomerate of players.  In this mini-study, I chose one player from each team in the ’09-’10 season, courtesy of 82games.  The player chosen had the highest combination of games played, minutes, and FGAs per 48 minutes of their respective teams.  I’ll call each of these players their teams’ “clutch players”.  Last year it was Aaron Brooks for the Rockets.  Here is the complete list:

The “star” versus “committee” difference takes care of itself when you take a single player from each team, because if a player is sharing possessions with someone else in the clutch, his per-48 minute numbers will be lower than a player taking the lion’s share of possessions (ie. LeBron).  In other words, players with lower per-48 minute numbers are on teams with no defined go-to player or “star.”

As usual, I compared a number of different metrics with wins, and looked to see which were the most correlated.*   Here are some of the more interesting results**:

Here are my takeaways from this table:

1) Points scored are surprisingly the most correlated statistic, more so than any other metrics taking assists into account.

2) Having a single player use more FGAs in the clutch, and even more accurately, more possessions, is more important to winning than that player’s scoring efficiency.

3) Assist numbers are not very correlated to wins (r² of .038).  When your clutch player passes more as opposed to shooting, the correlation to winning decreases.  That would help explain why LeBron got so much flack several years ago when he passed to Donyell Marshall in the corner for a missed 3-pointer.

This evidence points towards the need for a go-to scorer in the clutch.  The type of player that, regardless of the results, you know decided your team’s fate in the waning minutes of the game.  Kevin Martin may be developing into that kind of player, but what about when Brooks is healthy again?  With Scola using possessions in the post as well, it seems like we are truly a “clutch by committee” team, which does not bode well for winning.  To the right is the list of the top clutch scorers per-48 minutes last year, and their teams’ wins.  Looks like good company to me.

For a more detailed, albeit ancient, examination of clutch stats, see this article.

*A couple of disclaimers here: Total team wins are used, while these stats are only from clutch games, which means that there are many wins that were not attributable to the clutch statistics (number of clutch games played for each player ranged from 20 to 47, with the average being 35.3). Also, these stats are not adjusted for pace, so a faster-paced team will have slightly inflated numbers.

** “Team points”, “created points”, and “team created points” are metrics I invented on the fly in an attempt to break down a player’s impact on the floor.  “Created points” removes points that a player scored from an assist by another player.  It is essentially points scored in isolation scenarios.  “Team Created Points” is created points plus an estimate of points created from a player’s assists.  It can be viewed as all team points that a player created (but didn’t necessarily finish).

He is a 6’4 small forward, though he often plays shooting guard.  We have Courtney Lee and Kevin Martin ahead of him in the depth chart, and there really is little chance of him breaking into meaningful minutes with our current roster, barring unforeseen injuries.  Is his increase in usage lately a sign that he will be a part of the Rockets’ future or a sign that we are trying to shop him?

Looking at accomplishments by 5 man units is one way to get an idea of a player’s contributions to winning.  According to 82games.com, here are the top 5 units so far this year:

There are a few interesting bullets from this information:

• The only difference between the number 1 unit and the number 2 unit is substituting Miller for Hayes.  There is a predictable jump in offense, but more striking is the huge improvement in defense.
• Brad Miller is in two of our top 3 lineups
• Our defense is atrocious in the one lineup featuring Yao

I know – this is limited data.  However, coaches pay attention to the relative performance of different 5-man units, especially with new players on a team and endless injuries.  I am not necessarily saying that these are our best lineups, but when trends do start to develop, unit success is a strong dictator of playing time.

The Rockets have started to look like a respectable team lately, but is it for the obvious reasons?  Here is Yao’s individual production on the court this year versus Brad Miller:

While their defense is comparable, it seems that Yao’s biggest hindrance thus far has been his offense.  Is this a pattern that will continue when he returns?

On the other end of the court, one aspect of being “undisciplined” defensively, somewhat synonymous with being “raw”, is the uninhibited impulse to block every shot.   When there aren’t any refs, the risk-reward relationship of attempting to block a shot shifts significantly in favor of going for the block.  Concurrently, the influence of pickup basketball rules changes a player’s perceived risk-reward relationship between driving to the rim and pulling up for a lower-percentage shot.  When the opportunity of free throw attempts is removed, a slight boost in FG% for shots around the rim versus, say, a 10-foot jump shot, does not justify the immense social risk of getting rejected.  My hypothesis is that, despite logic and best efforts of a coaching staff to keep players “disciplined” offensively, many players in the NBA cannot control their aversion to getting blocked, and therefore attempt lower-percentage shots.  These low-percentage shots include, in order of increasing egregiousness: raising the arc on a shot to clear the shot-blocker, shooting a fade-away, altering the shot/shooting form in mid-air, attempting a “floater” when there is a possible lane to the rim, and avoiding the drive all together and jacking up a long 2-pointer.

Opponent Shooting Percentage vs. Team Blocks

click to enlarge

The first step in my analysis was to see if there was a correlation between team block rate and opponent shooting percentage.  The idea is that if your team blocks a bunch of shots, opponents will not only miss those shots that were blocked, but will also have a large number of altered shots (assumed to be of greater difficulty and a lower shooting percentage).   Looking at regular-season data from 1999-2009 (databasebasketball.com), there appears to be a decent relationship, as displayed in the graph.   As you can see, as a team blocks more shots (block rate is blocks divided by opponent’s 2-point FGA), their opponents shoot at a lower percentage (ρ = -41.08%, rsq = 16.9%).

Opponent Shooting Location vs. Team Blocks

So we know that there is a relationship between opponents’ shooting and team shot blocking.  That was the first part of the theory.  The second part was that the FG% is lower because of an aversion to drive all the way to the basket.  The best way to measure that is to compare team shot blocking to opponent shooting locations.  I compared team block rates to two different location attempt percentages defined by hoopdata.com (2006-2009) – “at rim” and “<10 feet” (for example, the “at rim” location attempt percentage would be attempts at rim divided by all 2-point attempts; in other words, the percentage of 2-point attempts at the rim).    To my initial surprise, there was a slightly negative correlation between opponents’ at rim attempt percentage and team block rate (ρ = -12.38%, rsq = 1.5%).  It makes sense, as more chances to block shots will obviously result in more blocks; however the relationship is pretty weak.   I then compared the same team block rate to the “<10 feet” attempt percentage.  The results were even more unimpressive (ρ = -3.2%, rsq = .1%).

What does all that mean?  It means that, despite a team blocking shots at a high rate, opponents do not change their shot locations.  My theory that players will tend to stop short and pull up instead of go all the way to the rim when driving against strong shot blockers was incorrect.  They still will attempt those shots.

But what about the FG% thing?  I showed earlier that block rate has a decently strong relationship with opponents’ FG%.  I just showed that that relationship has little to do with shot location, so what else could it be?  Taking a further look at the breakdown in opponent’s FG% by location, you can see what is happening:

click to enlarge

To my best understanding, the biggest effect of strong team shot blocking is altering shots near the rim.  The closer an attempt is to the rim, the greater effect a team’s block rate has on opponent shooting.  For “at rim” attempts, we see the most drastic dip in FG% (ρ = -46.48%, rsq = 21.67%).  It seems that shot blockers also affect “<10 Feet” shots as well, but not as much (ρ = -32.99%, rsq = 10.88%).  Conventional wisdom preaches the benefits of shot blockers altering shots, but this is the clearest evidence actually supporting that claim.

Opponent Shooting Location vs. Best Shot Blocker (Elite Blocker Theory)

Despite my best efforts to encourage basketball viewership from a team perspective, it is widely more popular (and fun) to look at individual players.   After all, when you’re driving to the rim against the Magic, are you thinking about Orlando’s team block rate or are you thinking about Dwight Howard throwing your shot into the bleachers?   I scanned through the same four seasons, and found the leading shot blocker on each team each year (minimum 65 games), using blocks per game.  I chose blocks per game over block rate to place weight on minutes played.  After all, a player’s “presence” cannot be felt if he isn’t on the floor very much.  I then did the same comparison as the previous section.  Predictably, there is a similar lack of meaningful relationship between the best player’s blocks per game and opponent shot attempt location.  However, just like team block rate, there is a relationship worth considering for FG% at the rim (ρ = -35.99%, rsq = 12.95%) and FG% <10 feet (ρ = -19.46%, rsq = 3.79%):

click to enlarge

As you can see, having an elite shot blocker clearly affects opponents’ shooting, and can explain a large part of a team’s block rate, especially at the rim.   If you read my first post, you know how important shooting efficiency is to winning.   Good teams hold opponents to a low FG%, and good shot blockers hold opponents to a low FG%.  So, exactly how important is it that your team is good at blocking shots?

Block Rate to Wins

To keep this all in perspective, I compared block rate to wins from 1999-2009.   Compared to some of the more prominent categories discussed in past posts, blocks are not very significant.  However, there is a positive correlation, with an r-squared of 6.7%.   Here is a graph showing the relationship between wins and block rate:

click to enlarge

While blocking more shots may make a minor contribution to wins, it is directly related to one of the Rockets’ biggest weaknesses – opponent shooting. That weakness is further compounded by abysmal perimeter defense, allowing opposing wing players to penetrate with ease.

Through 11/17, opponents were shooting 63.7% at the rim against the Rockets, above the league average of 62.4%.   In case you were curious, Howard and the Magic are holding their opponents to 54% at the rim, the lowest rate in the league.

The bottom line is Jordan Hill needs more playing time.  All of this business about him being a liability offensively needs to stop.   He is shooting 70.8% on inside shots, with only 53% of them coming from assists (which means that he is creating about half of his own shots inside, and still shooting 71%; sounds pretty good to me).  As I mentioned last week, one of the biggest reasons he cannot stay on the floor is his poor court awareness and defensive rotations.  As soon as he can work out those kinks, I think he can provide the interior help that we have been lacking most of the season.

After a rough start, the Rockets may be showing signs of life, but we are still sitting at 3-6. The mentality of a Rockets follower this season is quickly shifting from “what are our current prospects?” to “what are our future prospects?” And the progression in the latter thought process immediately becomes “who are our prospects?” After all, having young prospects waiting to break out is a comforting feeling, especially during a season short on optimism.  Of the players I consider prospects on the Rockets, the biggest names right now are Jordan Hill, Chase Budinger, Patrick Patterson, Ish Smith, and Jermaine Taylor (and maybe Lowry and Lee, depending on your definition).   Here is a quick overview of these players*:

Budinger – As far as potential is concerned, his ceiling may be limited.  Last year, 85% of Budinger’s field goals were assisted.  So far this year, he is sitting at 75%. In a nutshell, he either cannot or will not create his own shots.  I believe it is the former, which limits him to a solid offensive role player at best in this league.   There have been many examples of athletic, unselfish shooters helping championship teams, such as Rick Fox, Bruce Bowen, and Trevor Ariza.  The difference is that Budinger has not been able to consistently translate his athleticism to the defensive end.  With a backcourt already short on defense, Chase’s minutes will continue to be limited unless he can prove to be a reliable defender.**

Patterson – He had a respectable summer league, but obviously limited data restrains any statistics-based analysis for him at the NBA-level.  I do think it is interesting that we used a lottery pick on an “NBA-ready” player, only to stash him away in the D-League.

Smith – His scoring efficiency is terrible (31.7 FG%, 35.4 eFG%).  Generally hand size and arm length are negatively correlated with outside shooting and positively correlated with inside scoring (think Rondo vs. Stojakovic), but Smith seems to be both a poor shooter (39.7 eFG% on jump shots) and ineffective around the rim (14.3% on inside shots).  On the other hand, Smith has shown the potential to be an elite passer.  With 18 assists on the year and only one passing turnover (ratio of 18.0), he is among the top passers in the league.  Compared to Chris Paul (17.3), Rajon Rondo (5.4), Jason Kidd (4.2), and Steve Nash (2.7), there is a lot to like and it will be interesting to see if he can stay in the rotation when Brooks comes back.

Taylor – This is a sad story, as he really hasn’t had an extended opportunity to shine (minus one 3-game stretch last March when he averaged 14.3 points in about 30 minutes/game).  Jermaine has the potential to fit the off-the-bench spark mold of Von Wafer, but after almost getting dumped for Dampier, his future as a Rocket is in jeopardy.

Hill – I saved the best for last.  Jordan Hill was selected 8^th overall in the 2009 draft, ahead of budding stars DeMar DeRozan, Brandon Jennings, Jrue Holiday, Ty Lawson, and Darren Collison. With his size, athleticism, and quizzical flashes of brightness, he has perhaps the most potential of these listed players. However, Hill is still learning the game and has some major areas in need of improvement.

Let’s talk offense first.  Hill is the best offensive rebounder on the team, with an ORR of 9.7.  That doesn’t say much, however, as that number is good for 29^th in the league among qualified power forwards.  He has a 45.8 FG% this year, which is poor for a post player.  Looking a little deeper, his shooting percentage from inside is excellent (70.0%), but only 42% of his attempts are inside.  The rest (58%) are jump shots, and he is shooting a shameful 28.6 FG% in that category.  This is about the clearest indication of poor shot selection that you will ever see.  Given his age and basketball experience (he picked up the sport in the 9^th grade), his poor shot selection is most likely a combination of a) the offensive system putting him in bad locations on the floor, and b) the coaching staff encouraging him to expand his game and perhaps complement Yao more effectively.  Either way, for now the coaching staff is responsible for working to make things simple for Hill on offense and putting him in position to play to his strengths.  Jordan, please stick to the dunks and hook shots.

As for defensive rebounding, Hill is considerably less productive than Scola with a DRR of 15.2 (48^th among PF) versus Scola’s 24.0 (12^th among PF).   For Hill’s size and athleticism, this is a cause for concern.  Why is he rebounding at such a low rate?   You could argue that he is being drawn away from the basket to contest shots, but that doesn’t seem to stop Dwight Howard.  You could argue that our defensive rotations leave him away from the rim during shot attempts, but that doesn’t stop Scola.  If there is an easy explanation, I haven’t found it yet.  Generally the propensity to get “50/50 balls” is largely a product of intangible attributes such as hustle, will, and intensity. This may be something to pay attention to in the future, as a player devoid of those attributes ultimately has a limited upside.

On a positive note, Hill’s most positive contribution on the court has been shot blocking.  The 6-10 forward is averaging 4.75 blocks per 48 minutes.  That’s good for 5^th in the league among qualified players, better than Dwight Howard (4.41), Josh Smith (4.35), and Tim Duncan (3.30).  I’ll dive deeper into blocks another time, but his defensive presence cannot be understated.  One of his biggest weaknesses defensively is his awareness on defensive rotations.  He is mentally slow on the court, which is probably a product of his late start in basketball.  If he can get those rotations down, his minutes will increase significantly.  Overall, in terms of current value-add and potential for growth, Hill is the Rockets’ best prospect.  There is little doubt he has the physical abilities to be an impact player, so his ceiling will only be limited by his work ethic and focus.

Looking at this list, I am feeling, at best, mildly optimistic about our young crop of players.  The odds of any of them emerging as stars on in this league are minimal.  The best chance of developing a star in the next few years is probably via our draft picks (assuming they are not traded), but 2011 will be a weak draft class, and there is always the potential for both the Rockets and Knicks to have non-lottery picks.

It may be premature to say that we are rebuilding.  But if we’re not rebuilding, then we’re trying to win now, right?  After 9 games, it sure doesn’t feel that way.   A trade to land another star would cement a “win now” approach, but every day we hold on to those picks, we move a little bit closer towards ”rebuilding” with up to three mid-first round selections in the next two drafts.  At some point, management will have to commit to a direction for this team’s future.  Until that happens, Rockets fans may be in for an insufferable period of prolonged mediocrity.

*Stats updated through Saturday; taken primarily from ESPN.com and 82games.com.  The holdup was 82games, so I didn’t update anything else to keep it consistent.  Hill’s ORR fell to 8.4, DRR rose to 15.8, and BLKP48MIN fell to 4.10 after 16 minutes of action Sunday night.

**After a few more weeks, there will be enough data to start looking more closely at Budinger’s ’10-’11 defensive and other advanced statistics, but for now, take my word for it.

1) Attempt more shots:  This is for a couple reasons.  First, if your team is used to a fast pace and the opponent is not, the opponent generally will make more mistakes (more turnovers).  You dictate the speed of the game.  Second, due to lots of quick, long-range shots before defenses are set, there are more opportunities for offensive rebounds.  Think about it –  if the offensive rebound rate off of three’s is higher than the rate off of two’s, then shooting more three’s will increase the number of possessions for your team.

2) Shoot lots of 3-pointers:  Long range shooters must pull the trigger when open.  The eFG% of 3-pointers is better than any other type of field goal attempt other than those close to the rim (dunks, layups, hook shots, etc.).  Also, three’s are easy and take little effort, allowing for more energy on defense and crashing the boards.

3) Take the first available shot:  Maintain the fast tempo by taking quick shots.  These are not always great looks, but remember – your team will have more attempts.

Historically, there have been very few pure run and gun teams.  I remember back when I played, one team in our conference, Emory and Henry, experimented with it for a few years.  Here is an example of one of their box scores.  They would full-court press the entire game, and subbed 5-man units every 4 minutes to keep the guys fresh.  They would shoot primarily three’s, and through steals and offensive rebounds would attempt about 30% more field goals than their opponents every game.  I couldn’t understand why this formula wouldn’t win every single time (they won some games, but could never win against the good teams).

There are zero teams in the NBA with that drastic of a commitment to the run and gun approach.  I think a major reason is that, as the opponents’ skill level increases, the effect of full-court pressure becomes less beneficial, and is often detrimental to a team’s success.  It takes a lot of energy to run a full-court press, a cost that may be too high for the slim rewards yielded against NBA-caliber back courts (against lesser opponents and in lower levels of play, however, it is still very effective).  In the NBA today, teams instead like to embrace the offense part (push the ball up the court, take quick shots), but not the defense part (force turnovers by pressing).  They instead hope that the other team will take quick shots as well, but at a lower percentage.  If you don’t already have some teams in mind, think of the Suns, the Warriors, and the Knicks.  I don’t think the Rockets fall into this run and gun category, even though a few aspects of our team are eerily close.

Run and gun does not win for 1.5 reasons (1.5 because reason #1 is significantly more important):

1) Free throw differential.  This is the single most important reason why run and gun does not work.  If you are camping out on the 3-point line, you are not drawing contact and getting to the free throw line.  Free throws are the second highest percentage shot in basketball (behind dunks which, coincidentally, are also pretty rare when attempting lots of 3’s), so less free throw attempts means that your team has a lower TS%.  Using the same general equation that I presented last time, I investigated the relationship between two different ratios:  free throw attempt differential and three point attempt differential, and their impact on wins.  I used data for all teams in the NBA from 2002 to 2009 (not selection bias – Excel could only handle 255 rows for regressions…), courtesy of databasebasketball.com.  Just as a quick overview, free throw attempts differential is a team’s weight of free throws per offensive possession divided by the opponents’ weight of free throws per (opponents’) offensive possession.  The formula looks like this:  ((.44*o_fta) / o_pos) / ((.44 * d_fta) / d_pos).  Three point attempts differential is the exact same thing, but insert 3-point attempts as the numerator (instead of .44*fta).  These first two charts show the relationship of attempts differentials to wins.  Note that these ratios are not impacted by shooting efficiency (FT% or 3PT%), and are only indicative of attempts.

So what does this data show us?  Both charts essentially confirm the idea that attempting a greater number of high-percentage shots will increase the likelihood of winning.  However, as I previously mentioned, players do not get fouled very often when they attempt 3-pointers.  A key differentiator between run and gun teams and, more generally, “fast-break” or “up-tempo” teams (think Showtime), is that run and gun focuses more heavily on attempting 3-pointers in any situation, rather than exhausting other options first (ie. getting to the rim and getting a layup or drawing contact).  The best teams, it seems, find a way to attempt a high number of 3-pointers and get to the foul line more than their opponents.  Daryl Morey obviously knows this, which would explain why he went after Kevin Martin (think of Martin’s two biggest strengths – drawing fouls and shooting 3-pointers).  The propensity to draw fouls and shoot a high percentage at the charity stripe is a key differentiator between the Rockets and typical run and gun teams.  Also, considering the Rockets’ commitment to lumbering centers Yao and Brad Miller, the openness to sign a shoot-last point guard like Ish Smith, and the lack of follow-through in trading for volume-shooter Carmelo Anthony, many signs point to our Rockets preferring a more dynamic scoring attack.  I will further discuss the implications of this realization with regards to the Rockets after reason #1.5:

1.5) eFG% is misleading for end-of-game shots.  Being a run and gun team with a reliance on high eFG% 3-point shooting does not help much in crunch time in a close game.  I don’t need to pull out any fancy stats here.  Even though Aaron Brooks had a 59.7 eFG% from three last season, the odds of him making a three-pointer on any given attempt were still 39.8% (his 3-point shooting %).  This is the intuition side of me, but good teams make clutch shots.  If your team relies on 3-point shooting (Rockets), and you need a clutch shot at the end of a game (against New Orleans or San Antonio), the odds of you making that particular shot are lower than a 2-point attempt (given the higher possibility of drawing a foul).  I don’t want this to appear like a contradiction from my last post.  I stand firm that 3-pointers are a crucial ingredient to winning, but an overreliance on them allows for greater variance.  Variance is fine during the course of a season or even a full game, but when your team has one shot at the end of a game, variance is the enemy.

Implications for the Rockets:

No, by most definitions the Rockets are not a run and gun team.  However, after digesting this information and thinking about our team, I am of the opinion that we are not optimizing our personnel.  Last year, the Rockets had a free throw attempts differential of 1.038 and a three point attempts differential of 1.35.  While our team’s FT% has been consistently above the league average the past three seasons (this year included), we are not getting to the free throw line enough.  Having excellent free throw shooters is a major competitive advantage that we are not exploiting.*

Despite not getting to the line very often last season, we allowed our opponents to get to the line even less.  Last season 9.88% of our possessions ended on free throw attempts, while our opponents ended 9.52% of possessions on free throw attempts (compared to a league average of 10.38% from 2002-2009).  Our defense, and more specifically our ability to not foul our opponents, covered up our inferior offensive free throw attempt rates.  Before Sunday’s game**, sitting at 0-5, we had attempted 2.8 less free throws per game than our opponents.  As we have witnessed the steady dilution of Jeff Van Gundy’s defensive impression on the Rockets since his departure, this may be the final straw.  Remove a defense-first coach, add an offense-first backcourt, and throw in a bunch of young, undisciplined defenders, and you have maximum exposure to some of the Rockets’ biggest flaws.

With Rick Adelman as coach and with our current roster, I do not see us magically becoming more disciplined defensively.  It’s just not going to happen.  Our best chance of reversing this trend is to attack the basket – a lot.  No more 19-foot jumpers.  We need to finish our drives, go all the way to the rim and get blocked, get fouled, or make a close shot.  The referees may be to blame for a call here and there, but over the course of a season there are no excuses.  The Rockets are currently built to outscore opponents, but if we shy away from one of our biggest competitive advantages on offense –  the highest-percentage shot in basketball outside of dunks – how can we be expected to overcome our defensive ineptitudes?  I implore you to join me in a collective cringe every time the Rockets settle for a long 2-pointer, appreciate aggressiveness, and by all means, learn to love free throws.

*In 2008, when the Rockets won 52 games, our FT attempts and 3-point attempts differentials were 1.098 and 1.273, respectively.  That slight boost in FT attempts over opponents (combined with some other factors) was enough to propel us into solid seeding in the playoffs.  The results of the Minnesota game Sunday were more of a confirmation than ever that the free throw attempts differential is especially important for the Rockets.  In that game, we attempted 47 free throws (shooting 83%), while Minnesota attempted 33 free throws (68%).