“[Understanding] depends on things themselves…but also, crucially, on our bodies, our skills, our situations, and our interests. We achieve the world’s presence and we do so dynamically, and actively.” –Alva Noë, The Entanglement
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You may remember a controversy around the third hole at the 2023 Masters. It’s a short four with two options: bang driver up near the green and pitch up the hill or lay back with an iron and approach the green with a full wedge. The choice, effectively, is a shorter pitch or the added spin of a fuller swing.
A former player in the commentating booth advocated for the layup when the pin was up front. The front shelves, his school suggests, are just too small to hold consistently without spin and too elevated to allow the steep descent of a high lob. Laying back and hitting a full wedge is the only way to come in high and soft enough to hold the tricky green.
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The statisticians disagreed. Any way you slice the data, there simply is no greater correlation to lower scores than proximity to the hole. By the expected-value calculations, a fifty-yard wedge is always easier than the same hundred-yard wedge, full stop. Anyone who laid up (or suggested that one should) didn’t understand the simple patterns that underlie scoring.
Back in 2003, a decade before Mark Broadie’s seminal paper invented modern golf statistics as we know them—even a year before ShotLink recorded its first shot—Tiger Woods came to the third tee wanting to hit his patented long-iron stinger. His caddie, Steve Williams, had “no question in [his] mind” that Tiger should hit driver to get closer to the green. Tiger eventually conceded to his caddie and hit driver. He hit it terribly. He refused to say a word to Williams for another six holes, and Williams considers the dispute the biggest on-course conflict he had with Woods.
Twenty years later, Tiger returned to the third tee at Augusta National. Those twenty years saw more data collected than could fit in your local library in 2003—data that (if you listen to the experts) suggest unilaterally that hitting driver is the objectively correct play on the third hole. Yet Tiger hit iron.
This contradiction requires one of two things to be true. Either Tiger has overlooked one of the most obvious and valuable pieces of golf strategy in history, or has stubbornly carried an unhelpful memory for twenty years, and is either way undeserving of his image as the smartest and most ruthlessly competitive golfer in history. That, or the statistical analysis isn’t quite as conclusive as the statisticians will tell you.
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Consider a story about a lump of clay. On some indeterminate Monday, this lump of clay sits on a table. On Tuesday, a skilled sculptor shapes the clay into a beautiful statue. It sits on the table through Wednesday and is admired by many for its beauty and effect. The sculptor squashes the statue beyond recognition on Thursday. On Friday, the lump of clay sits on the table.
This simple story illustrates a substantial claim: that two ordinary objects can exist in the same place at the same time. No tricks, no obscure physics or linguistic gimmicks, no smoke or mirrors. The lump doesn’t cease to exist when the statue comes to be, though the statue wasn’t there before it was sculpted. There’s no trick: on Wednesday, the same stuff truly does make up two unique things.
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It’s easy to see why the data revolution appears to be the Eye Test’s death knell.
Our modern lives are inseparable from our procession through data, leaving more data in our wake. This statement is banal to make and hacky to expound upon, both of which only affirm that data [gestures wildly] characterize our age.
Golf has been a game of numbers since the gutta-percha revolution, never mind silicon—a game of yards and inches, of carry numbers and elevation adjustments, of green speeds and wind directions, of handicap indexes, cut lines, and winning scores. After all, despite the incomprehensible complexity that keeps us hooked, golf boils down to nothing more than strokes on a scorecard.
This numerical nature makes golf the perfect target for statistical analysis. Simply, because golf is scored by strokes and strokes alone, any metric that measures progress to the hole in units of strokes thus measures golf’s essence. Strokes Gained statistics behave exactly this way; this is what makes them so valuable. With our oceans of ShotLink data (as well as even larger amateur datasets), we can predict an average expected number of strokes to hole out from any position on the course. By adding and subtracting these expectations from each other—for instance, from a shot’s start point to its end point—we can quantify how many strokes were gained or lost with each swing.
Statistical advances such as these have illuminated other sports with greater clarity than ever before. Whereas reading “0-3, 3Ks'' in a box score leaves you only with a rudimentary—even anecdotal—understanding of what happened last night, you can watch baseball today and know exactly why your fastball-hunting glove-first centerfielder hitting below the Mendoza line isn’t touching this guy’s .090xwOBA wipeout splitter.
But with golf, the further claim is that these statistics don’t just tell better stories; they tell the whole story. Golf success is measured by numbers of strokes; Strokes Gained measures in units of strokes; therefore, Strokes Gained measures golf QED. For a game of such nuance, the ruthlessly uncomplicated way of determining who wins and who loses is nothing more than the score you shoot. As such, at the end of the day, it’s all just a game of strokes.
That modern statistics measure golf so fundamentally has upshots that reverberate all the way up golf’s intellectual ecosystem. For instance, golf strategy—once the subject of fierce books- and decades-long debate—turns out to reduce to a few simple commandments: advance the ball as far as you can toward the hole, avoid penalty strokes at all costs, and just get it on the putting surface (and definitely don’t short-side yourself if you miss). The exceptions to these rules are few, if any—for nearly any subjective assessment of two lies, there’s a data scientist to inform you of its statistical insignificance. Considering approach angles, hitting it below the pin, or getting lags to the hole to give it a chance, these all have been debunked as fallacies that the evidence simply does not support.
With modern statistics measuring so close to the game’s essence, less and less is up for discussion. Subjective debate withers in the face of objective answers. More and more, the guy arguing against the numbers at the 19th hole finds himself in an indefensible minority. Golf moves ever closer to being a computationally solved game, like tic-tac-toe or connect-4, where subjective assessments are trivial in the face of settled objective fact. The Eye Test no longer passes as evidence.
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Responses to the statue and clay story—attempts to reconcile a compelling train of logic with the intuitive sense that “something’s up”—come in abundant flavors, none without aftertaste. One of the most common is to deny statues. This is nihilism, the deeply skeptical position that nothing exists beyond mere collections of particles and that any words (“statue” or “lump” or “sculptor”) are nothing more than tools of reference, “useful façon de parler.” While the particles might take on new shapes, nothing changes besides our own psychological interpretations—judgements that are illusory and detached from the real, cold, hard truth that there are no statues. Aesthetics and human value judgments are bunk. We live on a floating rock, nothing actually matters, at some point, the sun will explode, etc. etc. It’s all just stuff—stuff that’s subject to our mushy, illusory human interpretations, but really just mere lumps of stuff nonetheless.
As difficult as this position appears to escape, it has a fatal flaw: if it’s all just lumps and nothing more, than what explains the sculptor? Or whoever believes the “just stuff” theory? Or whoever’s reading about it? Are these really best understood as mere stuff?
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Returning to the third hole at the 2023 Masters, it’s easy to see why the statisticians are so confident that driver objectively is the correct play. This is the upshot of expected-value-based predictive statistics: they very quickly become prescriptive statistics.
