The Culture of Moving Dots

Here is a video of “The Culture of Moving Dots: Toward a History of Counting and of What Counts in Basketball,” a public presentation I gave last week at a workshop on “Doing Sport History in the Digital Present.” The workshop was sponsored by the North American Society for Sport History and the Georgia Tech Sport, Society, and Technology Program. A few people who couldn’t be there had asked if I could make it available.

The presentation was a distillation of a longer scholarly essay I wrote for the workshop which I expect will be published in the Journal of Sport History.  But as I did the research for that I really became so fascinated with the topic that it has become the seed of what I envision as my next book, a companion volume to my recently published book, Ball Don’t Lie! Myth, Genealogy, and Invention in the Cultures of Basketball that I’m calling, for the moment anyway, Numbers Don’t Lie! A History of Counting and What Counts in the Cultures of Basketball. It will situate the analytics movement in basketball in broader frameworks of statistical reasoning in sports, measurement and statistics in scientific culture in the west, the use of digital technologies in the age of Big Data, and, as usual, the cultural and political dimensions of hoops.

Because the project is in its initial stages, I’m especially eager to get constructive feedback on it.  So as always, but more than usual, leave me comments or shoot me an e-mail.

Towards a Techno-Scientific, Socio-Cultural, Tactico-Strategic History of Basketball Analytics

I know, I keep rebooting. In my last post on this topic, I referred to a larger (academic) research project on the rise of basketball analytics.  The first step in the project is a 5000-7000 word article for a workshop organized by and special issue of the Journal of Sport History dedicated to “Doing Sport History in the Digital Era.”

However, I’m also realizing that there’s enough material, and enough curiosity on my part, to make a book out of this.  Moreover, I discovered that there are no comprehensive histories of statistical thinking in basketball (or in sports, period) of the sort that exist for statistical thinking in general. So I think there’s a need; perhaps for a companion volume to Ball Don’t Lie! called Numbers Don’t Lie! The Quantification of Basketball. Who knows? Perhaps it’ll be volume 2 of a Hoops Quartet, I’m beginning to visualize.

As I learn more, I’m finding I’m more interested in understanding, describing, and offering interpretations of the various facets of the rise of basketball analytics and less interested in making judgments about it, as I did too hastily here.

To that end, today I formulated two basic questions guiding my thinking and research.

Screenshot 2016-02-06 13.21.22

That is, I have questions about the causes or conditions of possibility for the rise of analytics and questions about the effects of this rise.

Next I tried to turn these questions into a concept map, to which I added a branch for milestone events.

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I then started filling in some of the first conditions of possibility I could think off the top of my head, or that basketball people on Twitter suggested. There are in no particular order.

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To this, I added just a few obvious effects, as placeholders.

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Lastly, I begin to fill in some of the most obvious milestone events.

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When all these nodes in the concept map are expanded, it looks like this:

Screenshot 2016-02-06 16.45.39

I’m still working out how best to use this concept mapping platform, and welcome suggestions in that regard. But most of all, I’d like to draw on the varied, collective expertise of readers to help fill in facts, refine conceptual distinctions, and suggest sources and specific avenues of research.

 

 

The Culture of Moving Dots

Today I listened to a very well crafted, informative lecture by Rajiv Maheswaran on how basketball teams are using movement tracking devices and computing power to inform the decisions they make about roster composition, strategy and tactics.  Not only was the lecture itself admirable (something that, as a teacher, I care about a lot), but the human scientific intelligence and the technological power described in it leave me awestruck.  Moreover, the potential for the insights generated by this work to cut through certain persistent myths in basketball culture—myths that often harbor and purvey harmful social attitudes, especially about race—seems exciting to me.

Of course, as someone who has spent a lot of time analyzing the often irrational (if unconscious) attitudes embedded in the language and stories used to talk about basketball and basketball players from the game’s invention to the present day, the facts offered up by quantitative reasoning can be one useful instrument for countering these myths. And I can certainly see this presentation as a demonstration of the brilliant complexity of the physical and cognitive abilities of individual basketball players.  But still, quantitative reasoning and the technology and facts to which they lead remain just that—useful instruments—and ones whose utility depends, like that of any instrument, on the intentions of the user and the context of the use.  They are not, in my view any way, some sort of final horizon of human knowledge about basketball and its culture.  That’s why, despite these positive feelings, a reservation popped into my head almost from the outset, kept nagging at me throughout, and remained when I finished watching. 

At a linguistic and conceptual level, as I’ve expressed elsewhere on this blog, I’m concerned with the abstracting tendencies in basketball culture that lead us to see players as something other than human beings like ourselves.  So I get worried when Maheswaran boasts that in sports, through the “instrumenting of stadiums,” “we’re turning our athletes into moving dots.”

moving dots

we’re turning our athletes into moving dots.

There better be, in my view, some extremely compelling reason, some significant value delivered that outweighs for me the ethical cost of viewing (let alone “turning”) athletes—or any human being, for that matter—into a moving dots.  After all, psychologists have told us that seeing other people as moving dots, say on a radar screen, seems to make it easier to kill them.

But Maheswaran’s work seems driven by an assumption that the ability to track and quantify human movement is a desirable thing.  He asserts this more or less directly a few times in the course of his lecture, apparently to remind his audience of the practical value of the scientific research involved.  

So, he introduces his work with the relatively simple rhetorical assertion of value:

And wouldn’t it be great if we could understand all this movement? If we could find patterns and meaning and insight in it.

Then, after a detailed and informative explanation of how machines deliver NBA franchises information about shot selection and shooting ability, he explains that

it’s really important to know if the 47 [meaning the 47% shooter] that you’re considering giving 100 million dollars to is a good shooter who takes bad shots or a bad shooter who takes good shots.

Finally, in concluding he offers a touching glimpse of the personal value we might derive from non-sporting applications of this technology:

Perhaps, instead of identifying pick-and-rolls, a machine can identify the moment and let me know when my daughter takes her first steps. Which could literally be happening any second now.

Studying-Gothic-4

Think very carefully about this: are you prepared to live with what what you create?

Finally, he lands on a firmly optimistic and time honored Enlightenment era affirmation of the blissful marriage of science and progress in the quality of human lives:

Perhaps we can learn to better use our buildings, better plan our cities. I believe that with the development of the science of moving dots, we will move better, we will move smarter, we will move forward.

To some degree, I am with him on most of this.  However, I must say it’s no more important to me to know if the player that an NBA owner is considering giving $100 million to is a good shooter who takes bad shots or a bad shooter who takes good shots than it is to know whether my friend Johnny is moving his body in the most productive way during his shift as a stocker at the local Walmart. Beyond this, with regard to his final assertion, a great deal depends for me on what he means by better and smarter and even forward.

I am no scientist, but I am also no Luddite.  I recognize and depend upon the value of quantitative and scientific reasoning and its many technological applications countless times in the course of my daily life.  For example, at this very moment, I tap my fingers on a wireless computer keyboard that sends signals to my CPU that in turn transforms those movements into letters and words appearing on my screen in the post composition screen of a page on the internet. I may not understand the process in detail, but I know enough to know that my own work depends, directly or indirectly, on the work of people like Maheswaran.  And so I want to be clear that I am not adopting some sort of polarizing anti-technology stance whereby I’d advocate a world law banning the use of quantitative reasoning, science or technology in sport or elsewhere.

I am, however, advocating for a place at the table where decisions concerning the development and use of such instruments get made.  

I don’t mean a place for me personally (though I can think of worse candidates), but for people like me (but smarter and better informed—in other words, I can also think of better candidates) who have devoted much of their lives to studying the history of the relationship between human technologies and human values.  People, I mean, willing to attend to the annoying complexity of concepts like better, smarter, and forward.

Our technological power, as Maheswaran so ably demonstrates, is growing in leaps and bounds and the demonstrations, like his lecture, we have of it—themselves reliant upon new technologies—grow increasingly enticing and compelling to more and more people. Meanwhile, despite a shrinking budgets for higher education around the country, corporations and university administrators continue to prioritize spending for the development of facilities, faculty and resources in science, technology, engineering and math.

But this expansion has often come at the expense of investments in the humanities disciplines that have been the traditional home (in universities, at any rate) of critical conversation about the ethical costs and benefits of the developments we find so enthralling.  0When we contemplate, individually or collectively, using a new tool (which is how I see the technological application of scientific research), we must ask ourselves, informed by historical knowledge and by a deep interest in the causal web that extends around the globe, into the earth itself, and forward into the future, what we stand to gain and to lose by its use.  As you might imagine, the conversation that follows that initial query is likely to be complicated and messy and, dare I say it, inefficient.  But it is no less—and perhaps more—urgent that we have it on that account.

We need, in other words, to think very carefully and to talk about what we’ll gain and lose by moving “forward” into a “better” and “smarter” world in which we may all transform one another into moving dots.

In Praise of Inefficiency and the Incalculable

Much has been written in recent days about the Cleveland Cavaliers improbable victories over the Golden State Warriors in Games 2 and 3 of the NBA Finals.  The Warriors, the NBA’s best team during this year’s regular season and, according to several advanced metrics, one of the most dominating and efficient teams ever, were supposed to steamroll the Cavs, especially given injuries to Kevin Love and Kyrie Irving, two of Cleveland’s big three stars.  And yet, as we’ve seen and then read about, this is not the case.  Observers have noted a number of reasons for this.  Cleveland has slowed the pace of games by running down the shot clock, aggressively pursuing offensive rebounds (which prevents Golden State’s big men from releasing on fast breaks), and pressuring the ball in the back court.  Golden State has thrived on playing a fast paced game and they’ve clearly been confounded by Cleveland’s tactics.  Of course, a big factor in Cleveland’s ability to set the pace has been the play of LeBron James.  Here, we read how James, whose career has been marked by efficient scoring and unselfishness, has reluctantly adapted to the conditions of this series by controlling the ball more on offense and putting up many  more shots than usual.  The story, to boil it down to oversimple terms, is that, contrary to predictions based on statistical analysis of the regular season (and even the longer career trajectories of key participants), inefficiency is beating efficiency.

I find this heartening for many reasons, but I want here to focus on just one. Read more

Bill Simmons is Wrong! (But also…) On Russell and Chamberlain’s Supporting Casts

I just can’t let this go. My distaste for Bill Simmons’ smug pseudo-argumentation has led me on a four-day journey down a rabbit hole of advanced statistics and I feel compelled to share my report of the trip. Read more

The Genesis of The Corner Three

14zonesIn an original and stimulating post yesterday, Curtis Harris at Pro Hoops History speculated on the idea of genre in basketball.  Specifically, he was prompted by former English professor turned director of the Stanford “Literary Lab” Franco Moretti’s book Graphs, Maps, Trees to think about particular basketball “genres” as emergent phenomena of what might be called the basketball system.  Moretti’s groundbreaking and controversial (among literary scholars) work rewrites literary history by looking at it from the point of view of quantitative history (“graphs”), geography (“maps”), and evolutionary theory (“trees”).  Or, as the books summary tells us, Moretti wants literary scholars to stop “reading books and start counting, graphing, and mapping them instead.”  Another way of putting this would be to say that Moretti sees world literature as a complex system and wants to apply advanced statistical methods to understand how it changes over time and space.

Curtis draws upon the parallels between emerging, rising, falling, and disappearing literary forms and plays or ways of playing in basketball and concludes with the following

Could the same thing happen in the NBA and with basketball?

It doesn’t seem that far-fetched that new events, technologies, fads, and social forces could force out one way (genre, if you will) of playing in favor of something new. Few people take hook shots these days. No one does two-handed set shots anymore. Corner three-pointers didn’t exist back in 1945. Without doing the full research now, my gut feeling is that basketball genres do exist.  Now to only figure out what events cause the genre changes. Read more

Where Anything Happens: The Dreams of Moneyball and the Beauty in the Unreasonable

Moneyball tells the apparently simple story of how a failed ex-major leaguer finds redemption and the underfunded team of which he was the general manager finds success by surfing the implacable wave of advanced statistical methods.

As such, it’s an underdog story that’s easy to follow.  Both the general manager, Billy Beane, and his team, the Oakland Athletics, are easy to identify with and support.   Most of us struggle, like the A’s, to make our lives without the privilege of vast wealth or superior natural talent.   Read more