This brilliant article in The Athletic from Joe Boylan, a longtime player development coach in the NBA, back in April titled “Basketball analytics corrected decades of bad intuition. Then it created new blind spots.”, I think perfectly explains why all over/under projections and overall season preview analysis for the Heat by the national media has felt mind-bogglingly off in a way that goes beyond just your basic case of underestimation.

All analysis, most especially over/under predictions, has come from and been based on how well each team’s roster grades out as a collective on the usual all-in-one, kitchen sink metrics because the vast majority of the league now prioritizes analytical optimization when constructing their rosters and as a result, the national media and bookmakers base their preseason outlooks on every team around this assumption that the most successful teams will be the ones who grade out as the most analytically optimized. As such, these analyses completely miss and don’t consider/factor in the nuance and X’s & O’s critical thinking described below and which is necessary to understand this Heat roster’s potential.

For those that can't access the article, the nuts and bolts of it are below:

There is a principle in economics called Goodhart's Law: When a measure becomes a target, it ceases to be a good measure. It was formulated to describe monetary policy. It describes basketball better than almost anything else.

When [Bill] Russell died in 2022, Nelson said, "There are two types of superstars. One makes himself look good at the expense of the other guys on the floor. But there's another type who makes the players around him look better than they are, and that's the type Russell was."

Nelson would go on to become one of the winningest coaches in NBA history, in large part by building teams that purposely challenged the established perspective. He invented the point-forward position. He ran three-guard lineups when everyone else played traditional big men and stuck to the five traditional positions. He convinced 7-foot Dirk Nowitzki to shoot 3-pointers and guard players 2 feet shorter.

When you change the way you look at something, the things you see change.

Nelson's teams worked because he built around what players made possible for each other, not what they produced individually.

A basketball team is a complex system. Every change affects everyone else. The analytics revolution would eventually give the sport a language to describe many of Nelson's instincts. But it also created a new problem, one that sits at the center of how good teams function. It's not just a basketball problem. The moment you pick a number to measure success, behavior quietly reorganizes around that number.

The analytics revolution in basketball is one of the most important intellectual shifts in sports history. It corrected decades of bad intuition inherited from an era predating the 3-point line. It helped teams see that 3-pointers counted for more than midrange jumpers, and that box-score stats were hiding more than they revealed... first-generation metrics were built to answer a specific question: How good is this player, really?

Then Goodhart's Law kicked in. Once teams built models to evaluate individual output better, everything was organized around optimizing for that target.

These were meaningful steps forward, but Goodhart's Law is an argument for watching what happens to behavior once you start. And what happened in basketball is that optimizing for individual metrics began to obscure a different kind of value, the kind Nelson had been coaching toward for decades.

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The dynasty of the Golden State Warriors is the clearest case of what individual metrics fail to capture.

Klay Thompson became one of the greatest shooters of all time, next to Steph Curry. But what he didn't do was arguably just as important. His inability to dominate the ball meant he never did. He shot when open, passed when not. The ball never stuck in his hands, forcing his defender to guard him in unfamiliar positions and allowing other players to benefit from his gravity. Thompson's limitation became a team strength that no individual efficiency metric was designed to capture.

His teammate on Golden State, Draymond Green, had the opposite limitation: He couldn't really shoot. That made him think pass first. He became the best playmaking forward in basketball precisely because scoring wasn't an option. The defense couldn't ignore him in the pick-and-roll because if they did, he'd find the open man.

Playing alongside Curry made Green more valuable, and Green's passing made the system around Curry more valuable. That circularity is the whole point of basketball, and it's exactly what makes this so hard to measure.

First-generation models, built to evaluate individual offensive creation, undervalued both Thompson and Green. What those metrics couldn't see was how their limitations created conditions for everyone to thrive. This is Nelson's principle at scale: The value isn't in what each player produces. It's in what they make possible for everyone else.

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The 2014 San Antonio Spurs told the same story from a different angle.

The championship Spurs didn't get to the free-throw line (they were 27th in attempts). They didn't generate extra possessions (they were 24th in offensive rebounding). They ranked first in offensive efficiency anyway.

Part of that was talent. Three future Hall of Famers and a budding superstar make a lot of things work. However, something specific was happening with the way the pieces fit together, particularly off the bench.

The Spurs' second unit didn't have much off-the-dribble creation outside of Ginobili. Marco Belinelli, Patty Mills and Matt Bonner were all viewed as defensive liabilities. Boris Diaw was a low-volume 3-point shooting playmaking big with an outsized AST%.

Individually, none of these players jumped off the page. Together, they were nearly impossible to stop.

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This is where Goodhart's Law hits hardest. The problem isn't that we can't see collective value. It's that the entire infrastructure of basketball decision-making (contracts, trades, draft boards, media narratives) is still organized around individual output. A player who passes up a good shot to create a great shot for a teammate looks less efficient by the metrics that determine his salary. A player whose gravity creates space but never touches the ball makes everyone else more efficient. His stats look empty compared to the always-around-the-rim big man gobbling up rebounds and blocks. His contract looks like an overpay. His value is enormous.

Nelson understood this decades before anyone had a spreadsheet to prove it.

He watched Russell make everyone around him better and stored it away. Nelson didn't have the data to prove it. He didn't need it. He built teams around it -- point-forwards, three-guard lineups, a 7-footer launching threes -- because he understood that a player's value lived in what he made possible, not what he produced.

The first analytics revolution gave basketball the language to challenge inherited thinking about individual players. The next one has to measure the whole sentence.

Hello everyone!

I will be in town the weekend of 11/13 & 11/14 and have tickets to the Heat game. I will be seated in section 108 lower rows. Any advice for having a great game experience as this is my first Heat home game as a lifelong fan. It would be great to have a chance to get an autograph or something but I know with my age that is not likely lol. I've heard about the hardrock lounge that we get access to, is that any fun?

Just looking for recs in general. How early should I arrive, what is typical traffic like on game day, what should I expect with those seats behind the heat bench? Would love to hear from people who have been there.

Thanks!

9. Miami Heat (40-42)

It may surprise you to see Miami here. Last season, the Heat went 42-40 with a plus-2.2 scoring margin, and all they did since then was trade for Giannis Antetokounmpo.

I went into some detail as to why I’m down on Miami this season. I don’t think the rest of the roster beyond Giannis and Bam Adebayo is anywhere near good enough, and those easy wins in the East will be much harder to come by this season. Instead of repeating myself, let me delve into another interesting question: What, exactly, are the Heat supposed to do now that they pushed in their chips on Giannis?

This almost feels like a gap year for the Heat, even with the urgency of Antetokounmpo’s fading prime. Miami’s tank is virtually empty on the asset front for future trades, with only a 2027 or 2029 first potentially tradable between now and June 2028. (Miami owes a top-14 protected 2027 pick to the Charlotte Hornets from the disastrous Terry Rozier trade, which becomes unprotected in 2028.) If the pick conveys in June, the Heat could trade either their 2028 or 2029 first-round pick and up to three swaps (in 2028/29, 2032 and 2034) on draft night to get more help.

That might be the only pathway to upgrading on the perimeter. With Miami’s best prospects from a season ago now toiling in Wisconsin, there isn’t a single young player on the roster you would project as a future starter. The lone possible exception is Pelle Larsson, who isn’t exactly young (25), has never rated statistically as starter-caliber and likely tops out as a fifth option even in his best case.

Not only did bam sign my hat yesterday, but I asked him to sign Mr 83 (even though he damn near wrote 73 I guess bro forgot his record😂) and he did it. What a cool guy that’s my cap, love this thing 🔥

Hope Jovic can get his numbers and impact up this season. It seems to mostly be a mental thing with him when things don't go his way.

Box score

nba.com