Curiosity only kills the Big Cat if he can't escape Schrodinger's delivery.

J.J. Barea's Marvelous "What If?" Machine

If I formulated a non sequitur for every time a conversation about Kareem Abdul-Jabbar veered abruptly into a revolution of sports gambling and a love affair with questions, I’d have spent the weekend in Las Vegas.

Toward the end of our zig-zagged discourse, my foil launched into a soliloquy lauding Google and their corporate philosophy of curiosity. He emphasized that the most important consideration one can make when trying to innovate or improve is “What if?” If you’re willing to ask that question (and questions of its type), you stand a much better chance of pulling yourself out of the box – or your head out of your ass, if so necessary. Focus on the wrong questions (“Is it possible?”; “How difficult will this be?”) or assume to know too much – a curse often caused by a reliance on tradition and what once worked – and you’re doomed to, at best, a Schrödinger’s Cat-like existence*, neither moving forward nor having the decency to get out of the way and end the suspense.

*After enduring a season of sedentary joy, the kind where one can smile from the couch at the beauty of Steve Nash but never find motivation to leap from one’s seat; of feeling boxed in by the empty potential of a race for the eighth seed; of watching players good enough for the Spurs – but not the Suns! – slide to 13 in the draft, I hereby declare a .500 winning percentage “the Schrödinger Line.”

It’s a conversation on vacation that ensured my preparation for this evisceration of quantification by Jonah Lehrer, specifically this runaway train of thought:

But sabermetrics comes with an important drawback. Because it translates sports into a list of statistics, the tool can also lead coaches and executives to neglect those variables that can’t be quantified. They become so obsessed with the power of base runs that they undervalue the importance of not being an asshole, or having playoff experience, or listening to the coach. Such variables are the sporting equivalent of a nice dashboard. They can’t be quantified, but they still count.

Well, why not? Why can’t they be quantified? More importantly, what if they could be?

Instead of approaching the issue as sports fans, it’s more effective to slip on our behavioral theory caps. How would we go about quantifying the importance of a nice dashboard, to use Lehrer’s analogy?

The first step would be to define the system – just what is a nice dashboard? We would set up experiments, controlling across different groups, to evaluate people’s preferences. In an ideal world, we’d have these evaluations for every conceivable type of car – every color, every year – and as large of a sample size as possible.

With our definition of a nice dashboard set, we could conduct a second experiment to determine the difference in actual price paid between different dashboards, again controlling for all of the variables. Finally, the entire process would be repeated for every single aspect of the car, in order to come up with an analysis of what consumers consider when buying a car and how crucial each of those factors is to their bottom-line.

…okay, that’s an incredibly daunting task. It seems almost impossible. But with enough computer power, enough refining of variables, definitions, and methods, and enough time, it’s certainly possible.

When we talk about doing the same thing with human beings playing an exceedingly precise game at speeds that require repeated viewings to properly analyze, it becomes even easier – to throw one’s hands up and declare the job the work of gods, that is. As Lehrer says, “the qualities that often determine wins and losses” in the NBA “can’t be found on the back of a trading card.” Had he stopped there, we’d be on the same page. However, he continues with “…or translated into a short list of clever equations.”

Well, why not?* What if we had the tools to properly measure the exact location of each player on the court and their movements? What if we translated that information, through analysis of large samples, into their impact on shooting percentages, the reduction (or increase) in passing lanes they defend, or an on-going list of clever equations that isn’t very short if we ask the right questions and view the game the right way?

*Is there an echo in here?

What if we had a large enough sample size to gauge the impact of a point guard with whom teammates love playing (hi, Steve Nash!), or a guy who keeps the locker room light, or any of the innumerable intangibles?

I’m thinking here of a Philip Roth metaphor. When asked by David Remnick, in a 2000 New Yorker profile, how he felt about a cramped literary interpretation of one of his novels, Roth busted out a sports analogy. He imagined going to a baseball game with a little boy for the very first time. The kid doesn’t understand what’s happening on the field, and so his dad tells him to watch the scoreboard, to keep track of all the changing numbers. When the boy gets home someone asks him if he had fun at the game:

“It was great!” he says. “The scoreboard changed thirty-two times and Daddy said last game it changed only fourteen times and the home team last time changed more times than the other team. It was really great! We had hot dogs and we stood up at one point to stretch and we went home.”

If that little kid were around today, he’d be obsessed with sabermetrics. He’d almost certainly win his fantasy league, but he’d miss the point of the game. Sure, he wouldn’t have squandered center field on Rowand, but he also wouldn’t have started Barea or bet on the Mavs. His car would have way too much horsepower and shitty seats.

Lehrer’s attempt to paint “sabermetricians” and this spectre of a child with the same brush seems like an artist grabbing his tool by the bristles. We’re in the same boat, Bob Ross. We both want to find the true value of J.J. Barea and what he does on the basketball court. I’m simply not content with statements like, “his speed and energy were virtues even when he missed his layups (and he missed a lot of layups), and that when he made those driving floaters their value exceeded the point score.” That may very well be true. If it is, then I want to figure out just how much value* Barea adds with his play.

*Two notes on value. One, value in basketball means points. Anyone who argues otherwise is misinformed or a dolt. Two, defensive value – that is, the negative impact on points scored – is severely underrated by people who attack “stat heads.” Most people who favor advanced statistics are aware of the limitations of current defensive metrics, and many (including myself) seem hopeful that optical tracking can help shore up these deficiencies and provide us with a more precise definition of defensive value.

Some factors, be they large or small, may be out of our reach. I don’t know. And it’s assured that attempts to quantify “intangibles” will be fraught with peril and often end in flames. (What, you don’t automatically light all of your bad ideas on fire?) I refuse to let the potential – the certainty, really – of failure deter me from better understanding the game I love, however, and I know that I’ll discover a thousand different things I’d otherwise never known by approaching the game this way.

To argue that it’s definitively impossible to define certain actions and characteristics – to say that it’s something that we just can’t account for because you make faulty assumptions or ask the wrong questions – strikes me as a lack of creativity and a willingness to gloss over difficulty. Add some color to your palette with a dash of curiosity. And if you’re going to ask the athletes you watch to do everything they can to reach their full potential and best play the game, try to do the same yourself and understand it as well as you can. Even if you ask some questions that don’t make sense, you’ll be amazed at what you discover.

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