On Kevin Garnett’s Passing and Broadening Our Definition of an Assist

Something about Wednesday night’s go-ahead basket got me thinking about the anatomy of an offensive play: Pierce’s sticky back pick was the one that initially freed up Jeff Green on his curling dash to the basket, but there was more to that KG pass than what met the eye:

And what about Jeff Green making the acrobatic catch, gathering himself and laying it in on the other side? For all of the debates about qualitative vs. quantitative measurement, basketball remains as much craftsmanship as it is artistry.

Now, much ink has been spilled over stats geekery and the difficulty in properly weighting the impact of any one player’s defense and how it correlates to a team’s ability to keep opponents starved for baskets. Brendan recently wrote about the fresh insights we can extract from a new set of interior defense analytics — using SportVu data as a complement to more traditional metrics.

But are the evaluation models that spit out numbers quantifying offensive impact really that much more developed than those available on defense?

A CASE FOR A MULTI-TOUCH ATTRIBUTION ASSIST MODEL IN THE NBA

A multi what, you say?? Basketball is not entirely different from the world of online marketing. For years, marketers have been scratching their heads wondering how they could possibly quantify all of their expensive marketing efforts (email marketing, social marketing, paid search, etc.) in a way that would commensurately assign credit for a consumer’s purchase — and allocate future advertising monies — to those touchpoints.

Say you received an email from Delta about cheap flights to Boston, liked the promotion on their FB fan page (bear with me here), tossed the offer onto your mental backburner and eventually went on to purchase the discounted flight by googling ”Delta cheap flight to Boston” a day later. The old model would only take into consideration that last action, i.e. the Google search preceding the purchase — a clearly inadequate view of the events incrementally nudging you all the way to the purchase.

In basketball, that’s the equivalent of giving the assist to the player who makes the pass right before the basket. Which is what we currently do according to the NBA’s statistics manual as long as the “player scoring the goal responds by demonstrating immediate reaction to the basket”.

What’s so wrong about a system that’s entirely weighted in favor of the last pass?

It turns out the answer is “a lot”, actually. Mainly, it’s an overly simplistic view that fails to capture the multiple actions in a single possession and some of the crucial interactions that precede that last, and for now, only assist that we keep track of. Let’s look at a few other things we might want to know about how a play unfolds:

1) The quality of the opportunity created by the assist: once the last pass is made, how hard was it for the player to finish off the play? Further complicating this subtlety is the fact that assists are subject to the whims of humans no more perfect than Marc Davis. Chilling thought. This is something we came across as Rondo’s assist streak was being alternately threatened and aided by any number of scorekeepers. HoopData recently published a study gauging the “lift” that teams benefit from just by virtue of playing at home. It was found that the difference in assist percentage from 2006-2012 between playing at home vs. playing away was on average a 4.9% increase in recorded assists, courtesy of generous scorekeepers. That means that some “assists” are not only of the Hail Mary variety but also of the dubious kind where the basket is less about the pass and more about the scorer’s creativity.

Two plays from the Golden State game that illustrate the stark contrast in the quality of KG’s “assists”: