Is Marbury a Loser?

Stephon Marbury has the skills, stats, and salary of a star. Nonetheless, he is perceived by many to be a loser. This greater perception of Marbury-As-Loser is likely formed in part by a constellation of subsidiary perceptions, such as the perception that Marbury is selfish (especially if you are a point guard purist), the perception that he has a poor attitude (especially if you consider wearing a towel on one’s head to be an indicator of poor attitude), and the perception that he is a poor teammate (especially if you’re into the tabloids). Probably the biggest factor in his losing rep, though, is just the fact that in his 10 seasons in the NBA, Marbury’s teams have finished in the lottery 6 times and have never won more than 45 games. In the 4 seasons where Marbury’s teams qualified for the playoffs, they failed to advance past the first round.

All else being equal, that history of futility at the team level could be construed as pretty damning. In fact, it comes off worse than just that. Jason Kidd and Steve Nash both managed to immediately elevate teams that faltered with Marbury just a season before, making it seem as if the team success was there for the taking all along, just waiting for a competent point guard to unleash it. Likewise, the fact that Marbury’s spotty team success has been distributed over four tours of duty in four different cities makes it seem as if the losing is a trend more readily attributable to the player than to his various teams.

However, closer inspection of Marbury’s career reveals numerous counterpoints to the above lines of reasoning. A thorough, season-by-season laundry list of objections one could raise to the traditional Marbury-As-Loser argument has recently been compiled by Dax-Devlon Ross. The Reader’s Digest version is that more often than not, Marbury’s teams have been either awful in terms of raw talent, or ravaged by injury, or both.

Points similar to those Ross enumerates have been raised in various Internet discussions on the Knicks ever since Marbury was traded to New York, but historically the skeptics have remained unconvinced. The bottom line, they insist, is that Marbury has failed to get it done. What is more, they claim, is that even those stats that do seem to reflect well on Marbury are misleading. Marbury’s 20 and 8 are nothing but numbers, empty stats that serve to promote the ego rather than team success. Sure, Marbury can ring up the scoreboard, but in the end his numbers do not translate into a tangible, on-court impact that really helps his teams win. Or so it is claimed.

What is nice is that these sorts of arguments needn’t be as indirect and unresolved as they sometimes seem fated to be. We don’t need to be satisfied with circumstantial evidence or received wisdom in this case.

How do we directly measure a player’s impact on his team’s success? The most straightforward measure is the player’s raw plus/minus statistics, which is a measure of the team’s point differential while a player is on the court vs. the team’s point differential while the player is off the court. But these plus/minus stats are not optimal for isolating the true impact of a given player, since they are subject to several influences beyond the player’s control. Consider, for instance, that you could hold a player’s impact on the court constant but change his plus/minus numbers drastically by changing the quality of his substitute, or by changing the quality of opposition he normally faces, or by changing the quality of teammates he normally plays with. For instance, TJ Ford would probably have a better plus/minus if his backup were Moochie Norris rather than Jose Calderon.

A more sophisticated measure of a player’s impact on his team’s success is adjusted plus/minus. The idea behind adjusted plus/minus is that we use statistical methods to remove the variation in a player’s plus/minus data that results from the other 9 players who happened to be on the court during his various court appearances. In essence, this removes the confounds alluded to above and gives us a pure measure of how much better (or worse) a player makes his team. (More on adjusted plus/minus methodology here and here.)

The major drawback to the adjusted plus/minus numbers is their scarcity. Unadjusted plus/minus numbers are only readily available starting from the 2002-03 season, which is presumably the season when the online game logs necessary for calculating plus/minus stats became available. And then there is the matter of calculating adjusted plus/minus from those rawer stats; thus far, no NBA stats site out there has made it a matter of course to fully integrate adjusted plus/minus numbers into its databases.

Fortunately, David Lewin recently crunched the adjusted plus/minus numbers for the 2004-05 and 2005-06 seasons in a series of articles for The results of the analysis would seem to turn the popular conception of Marbury on its head.

In the 2004-05 season, Marbury?s first full season in New York, the Knicks tallied a disappointing 33-49 record. Adding insult to injury, Marbury was roundly criticized after a torrid stretch of play in December inspired him to proclaim himself “the best point guard in the NBA.” The comment offended on two fronts. First, it was perceived as a politically incorrect kind of comment to make. (Things have apparently changed since the days of Muhammad Ali.) Second, it was regarded as a laughable claim at best. Sure, Marbury averaged 21.7 ppg and 8.1 apg, and even finished the season with a career second-best 21.9 PER? but those were empty numbers belonging to a loser. His team was no good, he didn?t make his teammates better on offense, and he didn?t play defense.

Marbury?s proclamation may still be regarded as non-PC, but in light of the adjusted plus/minus data, entertaining its truth value doesn?t seem quite so absurd. According to Lewin?s numbers, Marbury was 4th in the league in the 04-05 season in adjusted plus/minus at +12.4 points per 100 possessions, behind only Paul Pierce, Tim Duncan, and Elton Brand.

The simple conclusion to draw from this is that the Knicks’ struggles during the 04-05 season came in spite of, rather than because of, Marbury’s play. In fact, Marbury’s positive influence on the court was strong enough to rank among the league’s best. Therefore? in line with Ross?s arguments? if one were inclined to assign blame for the Knicks disappointing record that season, one would more properly distribute that blame among Marbury?s lackluster teammates, and possibly his coach.

The 2005-06 season is regarded as a down season for Marbury and his Knicks, as Larry Brown rode into town and… well, you know the rest. Marbury averaged career lows in points and assists per 40 minutes (17.9 and 7.0) and his 16.5 PER was his worst since his first two years in the league. His team stumbled to a bitterly disappointing 23-59 season. Marbury?s stock in adjusted plus/minus slipped as well, but he still posted a quite strong +7.57 points per 100 possessions. As with the prior season, Marbury was one of the few bright lights on an otherwise struggling team. It would be difficult to pin the losing aura of the 05-06 season on Marbury?s lapel since he was one of the few forces driving positive, winning play for the team.

Taking the weighted average of adjusted plus/minus over the 04-05 and 05-06 seasons, Lewin found Marbury to rank 8th in the league overall at +10.47 points per 100 possessions. By way of comparison, Nash (+8.47) and Kidd (+8.27) ranked 16th and 17th, respectively.

At this point, one can imagine the familiar response arising: those are just empty numbers; they don?t capture what the players are really doing on the court. But of course, adjusted plus/minus stats are designed exactly for the purpose of measuring a player?s net impact on his team?s success, rather than measuring milestones like points scored and assists recorded that may or may not contribute to a winning effort. It is logically possible for a player to average 20 ppg and 8 apg but still not help his team win. However, it is not possible for a player to rank exceptionally well on adjusted plus/minus but still not help his team win.

If one insists that Marbury is a sieve on defense, it must be the case that he is just that much better on offense. If one insists that Marbury is selfish and does not make his teammates better, it must be the case that Marbury?s style of play is nonetheless extremely effective at the team level, making the style critiques a moot point. If one insists that Marbury has still not been putting his teams over the top, one would seem to be criticizing Marbury for not being the best player in the league. In the end, it is not clear exactly how Marbury has helped his teams play better in recent seasons, but that he has helped them play better seems indisputable.

So, is Marbury a loser? Popular opinion may say yes, but at least in recent seasons, it turns out that popular opinion is wrong.

Of course, as with any other statistic, the adjusted plus/minus data do not come without caveats. A basic caveat is that the data may be rather noisy. Adjusting for the influence of surrounding players means you must measure the influence of surrounding players, and in some instances this may result in small sample sizes and hence the final numbers may come with rather large degrees of statistical variance.

One effect this has is to throw rank orderings into doubt. If two players are close in terms of their mean adjusted plus/minus, but both data points come with considerable statistical variation, then we may not have a lot of faith that the player who ranks higher is really higher in any statistically meaningful sense. Still, in the end, the actual averages that we get are our best guesses as to who should rank higher than whom.

It is also worth noting that in Lewin?s 05-06 analysis, the Detroit Pistons had strange adjusted plus/minus numbers, which Lewin argues was an anomaly due to their extremely rigid substitution patterns. Lewin does not think that this kind of substitution effect significantly skews the data for other teams. Still, it is worth noting that these sorts of problems may occur with the data.

These sorts of caveats do not seem to matter much to the general conclusion made here regarding Marbury, however. For instance, although Marbury was the point guard with the best adjusted plus/minus in 04-05, we probably cannot say with great confidence that his adjusted plus/minus (+12.4 points per 100 possessions) is really statistically distinguishable from Jason Kidd?s adjusted plus/minus from that same season (+11.15 points per 100 possessions). Therefore, one should not take away from this the ironclad conclusion that Marbury was in fact the best point guard in the 04-05 season. But if one is just asking the much more general question of whether Marbury really helps his teams win or not, then the sheer magnitude of his adjusted plus/minus numbers would make it very difficult for someone to argue that, in spite of the data, he is still a “loser.” Even factoring in statistical uncertainty, Marbury comes out looking roses on this analysis.

One final point of interest is that Marbury?s overall strong play may be a recent development. Dan Rosenbaum conducted an adjusted plus/minus analysis on the 02-03 and 03-04 seasons for Although Rosenbaum?s methodology differs somewhat from Lewin?s, in Rosenbaum?s analysis Marbury comes out looking like an average, break-even player during the 02-03 and 03-04 seasons. It is unlikely that such a drastic difference can be chalked up to the relatively minor methodological differences employed in the two studies. Therefore, it may be the case that one or more of the traditional critiques of Marbury (e.g. gives everything back on defense) were in fact legitimate at one point, despite being false in more recent years. It is hard to make any strong conclusions regarding this, though, given the absence of consistent methodologies across seasons and the paucity of data before the 02-03 season.

Early Results Suggest Improvement

Although the season is still young, perhaps enough games have passed (11 of 82, or 13.4%) for us to get a handle on some of the emerging trends for the Knicks? ongoing 06-07 campaign, and in particular to see how things compare to last season?s trainwreck. Some have suspected (or outright accused) Larry Brown of deliberately veering the 05-06 Titaknicks headlong into disaster, and so it bears investigating how the undoubtedly earnest bailing efforts of captain Isiah are proceeding thus far, with essentially the same cast and crew as the last go-around.

The Quick
Preseason proclamations from Thomas indicated that the Knicks would resort to a more up-tempo style this season, under the hood of a seemingly complicated hybrid offense dubbed ?The Quick.? At least as regards overall pace, such claims have thus far been more shtick than quick. The Knicks? pace factor is indeed slightly higher?91.8 possessions per game this season, versus 90.8 last season. However, this slight uptick in pace is more readily attributable to faster league-wide play than anything the Knicks are doing in particular. (Remember, pace is a function of both how fast you play and how fast your opponent plays.) Both last season and so far this season, New York is playing at almost exactly the league average pace (90.6 poss/g in 05-06, 91.8 poss/g in 06-07). A drop in offensive rebounding prowess (see below) may also be contributing to the Knicks? slightly faster pace thus far.

The Knicks are playing quicker on the level of individual possessions as well, taking 42% of their shots within the first 10 seconds of the shot clock, compared to 35% under Larry Brown?s more deliberate offensive attack. It?s difficult to judge this increase relative to league-wide trends, however, as does not provide stats for league-wide shot clock usage.

Offensive efficiency
Last season the Knicks ranked 25th in offensive efficiency, posting a paltry 103.7 points per 100 possessions. At times it seemed as if every possession was a mortal struggle to score (even the ones not involving Malik Rose). Subjectively, the Knicks? offense seems more free-flowing this season (though too often dominated by one-on-one play), and the numbers back up this impression, as the Knicks currently stand at 107.1 points per 100 possessions, good for 13th in the league.

A closer look at the four factors shows that last season, NY was excellent at offensive rebounding (4th in oreb%) and getting to the line (1st in FT/FGA), but that these considerable strengths were completely overshadowed by below average shooting (22nd in eFG%) and unspeakably awful ballhandling (30th in TO per 100 possessions at 19.5, a full 1.4 more TO/100poss than 29th placed Boston). This season, without Brown?s constant harping about playing the right way, New York is no longer great at offensive rebounding (16th) or getting to the charity stripe (11th), and has only slightly improved its shooting (48.8 eFG%, good for 14th in the league, vs. 48.1 eFG% last season). Nonetheless, the offense has been significantly better due primarily to significantly better ball handling?so far, the Knicks have shaved off 2.3 TO per 100 possessions from their 19.5 mark last season, making them an average ballhandling club rather than a rock-bottom one.

Defensive efficiency
Brown?s regime was supposed to have marked an infusion of defensive-minded play, but the Knicks struggled on D, giving up 111.3 points per 100 possessions (26th overall). They were below average at all of the defensive 4 factors except for their merely average defensive rebounding prowess. Isiah?s Knicks are actually stingier defenders thus far than Larry?s Knicks, surrendering 107.9 points per 100 possessions (22nd). The improvement in D appears to be driven entirely by opponent eFG%, where the Knicks currently give up 48.6% (15th) rather than 51.1% (22nd); the numbers for the remaining 3 defensive factors are comparable to last season?s, with average defensive rebounding and below-average performance in terms of forcing turnovers and keeping opponents off of the free throw line.

On balance, this year?s Knicks are thus far an impressive 3.4 points per 100 possessions better on both ends of the court than last year?s squad, making their net efficiency (-0.8 points per 100 possessions) resemble that of a .500 team. Perhaps a team performing within the vicinity of .500 ball is nothing to get excited about, but it’s nonetheless a steep improvement over a team contending for the #1 lottery pick (like last year?s team, which posted a hair-raising net efficiency of -7.6 points per 100 possessions).

So although all is not roses in MSG?s hallowed boobird halls just yet, the early results point to a team that might be mildly, rather than wildly, disappointing over the course of the full season. Of course, there is still ample room for the team to breathtakingly overshoot or undershoot these tentatively drawn out early trends.