For the decade and a half that I've been a basketball fan, there's been a wide perception of basketball players being either selfish or selfless. There's been a distinct categorization of those players that "would do anything to win" and those players that play well "just for the stats." I'm sure you can think of numerous examples off the top of your head... Zach Randolph, Ricky Davis, Jason Williams all come to mind as examples of the former.
In baseball, the number of people that believe in "selfish" or "unselfish" baseball plays is dwindling. You can only claim Player A hit 50 "selfish" home runs so many times before acknowledging that, hey, Player A hit 50 home runs.
But in basketball, the perception of doing it for stats' sake versus doing it for winning still clings on tightly. Part of that is simply the nature of baseball versus basketball- baseball is an individual sport masquerading as a team sport. Basketball is so much of a team sport that we're still struggling to come up with defensive metrics, despite insane amounts of technology at our disposal.
I'm sure many of you have seen Michael Lewis' article by now: The No-Stats All-Star in the New York Times. It's a story revolving around Shane Battier, how the Houston Rockets keep advanced defensive metrics to measure his value, and how he's ridiculously undervalued by traditional box score statistics. The essential claim of the article is this: basketball is an inherently selfish sport. More than that, statistics make players selfish. Players pursue the accumulation of individual statistics at the expense of the team good.
Daryl Morey, GM of the Rockets, goes as far as to say, "someone created the box score and he should be shot."
This is where I think the story misses a little bit. The concept of stat-seeking at the expense of the team is somewhat overblown. True, a box score fails to inform us of many, many aspects of a game. Who guarded whom? Who took the charges? Who spaced the floor? But our analysis of box scores has advanced to the point where we can speak with great accuracy on the offensive efficiencies of each player.
As this whole series has and will continue to harp on, that's the key: efficiency.
Padding points, rebounds, assists, etc. can be a simple task. Padding advanced stats- stats that actually matter- is much more difficult. Think of it this way. How does a player pad his points total? By taking more shots. If a player starts bricking a ton of shots just to score a few more points, his points total will obviously go up. It'd be at the expense of effective field goal percentage, true shooting percentage, etc. If a player started missing close range shots to collect more rebounds, it'd show up as a decrease in efficiency. If a player ran up and down the court just to collect assists, it'd show up in an increased turnover rate and potentially even a lower assist rate if too many extra possessions were used.
Being among the scoring leaders simply requires opportunity (being on a bad team, getting numerous shot attempts, whatever). Being among the PER leaders or the WinScore leaders requires efficiency. Two very different things. The combination of opportunity with efficiency is the hallmark of an elite player. Standing alone, opportunity or efficiency mean nothing.
Again, it's not like it's impossible to pad stats. Advanced statistics are by no means perfect. Far from it.
A player can still go for the "home run" assist at the expense of a crisp, non-assist pass. A player can still try and steal rebounds from his teammates. A player can still try and play only offense at the expense of defense. It's just that when you consider stat-seeking from an advanced statistics perspective, it's highly, highly overstated. Even the much maligned defensive stats have evolved to the point where, through sites like Basketball Prospectus and Basketball Value, we can catch a case of "dogging" it on defense pretty easily.
So next time you hear someone say, "he's a statistical monster, but it never translates to wins," you can smirk a little bit. Because, odds are, he ain't that statistically monstrous.