But what if he didn’t get any better? What if he just had the ball more? Let’s dig into the numbers to see what’s really going on.

Let’s start with his box score numbers. 28.8 Points per game, 5.3 assists, and 7.0 rebounds per game. Those seem like pretty monstrous box score numbers on their surface, and they are career highs for Brown. However, if we look at his efficiency, we can see it’s below league average. He’s posted a 98 True Shooting+ this season. (Two percent worse than league average) That’s not great for a primary option.

You might say, “Well, he’s taking more difficult shots with Tatum out.” We can look at his Shot Quality, and it is lower this season. But if we look at his Shot Making, we can see he’s basically performing at the same level he’s always been as a shot maker. (Shot making looks at actual vs expected Effective FG% based on shot quality)

What about his passing?

He is averaging a career high in assists. This is another case of just having the ball more. We can see that he’s always been a below-average passer relative to how often he gets to run the offense. The graph shows that he hasn’t improved as a passer, he just has more opportunities. 

“Well, he’s asked to do so much. He’s one of the top two-way players in the league, and an elite defender.” He did make that claim. If only we had a way to look into it with analytics. Oh, wait, we do.

Matchup Difficulty looks at how good the players are that you’re being asked to guard, and Guarded On-Ball% looks at how often you are guarding the player with the ball. We can see that Brown is guarding average players at a below-average rate.

His overall defensive impact metrics have been fine over his career, but nothing special. Here are his career D-LEBRON numbers.

By everything I can measure, Jaylen Brown has not improved this year. He just has the ball more. That he is in the MVP race is absurd. That is the power of the Boston Media machine. The same machine that convinced the public that Marcus Smart should win DPOY a few years ago. LEBRON and EPM WAR are metrics that estimate a player’s overall value over a season. They work by combining their impact per 100 possessions and their total minutes played. This produces their WAR, or Wins Above Replacement. I averaged the two stats together and compared Brown’s average WAR to the other MVP candidates.

SGA – 17.7 (1st)

Jokic – 15.73 (2nd)
Luka – 15.2 (3rd)

Wemby – 13.6 (4th)

Brown – 7.0 (26th)

Brown is not in the same stratosphere as the other MVP candidates. The point of the article isn’t to tell you Jaylen Brown is secretly a bad player, he’s not. But when we look into advanced analytics, he has not improved in a meaningful way. He’s the same player he’s been for years. A low-end All-Star who is very good, just not great. 

The post Did Jaylen Brown get better this year? appeared first on Swish Theory.

Cameron Boozer is simply one of the most versatile offensive hubs to ever play the sport of basketball.

Players Boozer’s size aren’t supposed to be this skilled – between his reliable handle, high-level playmaking vision, sublime shooting touch, and all-around scoring versatility, this 6’9″ 250lb bull gracefully drives through china shops without breaking a plate, consistently creating good looks for his team with quick-processing decision making, on-ball advantage creation, and off-ball play-finishing gravity stretching from downtown to the rim.

Fresh off an All-Time great one-and-done Duke season, Boozer has proven elite traits since his development path from Columbus High School that could add up to a sum-of-its-parts offensive engine at the NBA level:

• Outlier Outlet Passing
• Efficient Scoring Versatility
• Connective Hub Playmaking
• Special Rebounding Instincts
• Knockdown Perimeter Shooting
• Quick Processing Two-Way Feel

Now that March Madness ended in an exciting-before-disappointing run, there’s finally a crack in the Boozer Twins’ perfect armor.

Evaluators can still write a Christmas Carole with the list of accolades that the Boozer twins (Cameron, Cayden) have accomplished on their run to this point, two of the biggest winners to ever play the sport:

4 Florida State Titles
3 Nike EYBL Peach Jam Championships
2 Team USA Gold Medals
1 High School Natty

and the ACC champion regular season + tournament trophies.

After finishing the season, Cameron Boozer adds AP Player of the Year to that resume while becoming the first player in NCAA history to win NABC Freshman of the Year, Big Man of the Year, and Player of the Year.

Cameron Boozer is the clear best bet #1 pick in the 2026 NBA Draft class

Boozer is the clear top prospect in an all-time draft class not due to some immeasurable talent or high-flying bounce, but due to his consistent team-first feel and efficient scoring versatility in every basketball situation he finds himself in on the court.

Carlos Boozer calls his son, Cameron Boozer, a “modern-day version” of Tim Duncan, via Marc Spears:

“You look at what Tim Duncan did. I’m not comparing Cameron to Tim Duncan, but he was another guy that wasn’t [athletically] a Kevin Garnett or a Tracy McGrady or a Kobe Bryant or Shaquille O’Neal. But you know what he did? He won five championships in that era [against] those players — the Kobes and the Shaqs, because of his IQ, because of his skill set, and because his team would follow him… That is who Cameron is. He’s a modern-day version of that… So. if you want to win, you pick Cameron.” – Carlos Boozer

One popular comp for Boozer has been Kevin Love, and for good reason; while the mobility of these two players and play-styles on the ball are quite different, there are a handful of outlier elite attributes in outlet passing, rebounding, three-point shooting, post-up prowess and an impressively high BPM impact rating that make the stretch-four prospect comparisons easy to make. Love was an even better rebounder in college than Cam, but was slightly less efficient as a scorer and was 4 percentage points worse as a 3pt shooter. One big difference, though, is Boozer’s playmaking talent being on another level (25% AST/14% TOV%) compared to Love’s score-first style (14% AST%/15% TOV%)

Love was a big time prospect in his own right as a next-level scorer, shooter, rebounder, play-finisher and all-time outlet passer. Boozer’s ability to do those things similarly well while combining that scoring gravity with his handle, vision, and two-way feel takes his game to another level, allowing him to make quick decisions, create advantages for teammates and generate good shots for his team consistently, is what takes his potential superstardom to an even higher level of a scoring creator than Love.
One huge skill separating these two prospects here is Boozer’s handle, refined enough to help him self-create so many of these opportunities without needing a teammate to create the advantage first, which is uncommon for a big man. That handle, with the added team-focused playmaking, creates a floor-stretching downhill scoring creator with offensive engine gravity.

Another popular comparison brings up aesthetic similarities to the Magic’s Paolo Banchero and peak Pistons Blake Griffin in things like role malleability, scoring versatility, short-roll and postup playmaking, downhill play-finishing, and free-throw drawing as a powerful dunking 6’9”+ 250lb tank who can operate both ends of a pick-and-roll. As far as the hype machine bringing up names like Tim Duncan and Nikola Jokic, it’s for glimpses of similarities in fundamental footwork, strong screening, team-first connective play, and general understanding of the game as old-school offensive hubs, like Duncan sleepwalking to 20-10-3-3 statlines and Jokic splashing otherworldly tough shots and diming unthinkable passes from nearly any spot on the floor.

None of these are one-to-one comps; just all-time great prospects and players with comparable roles, playstyles, and archetypes who Boozer can build off to impact the game in similar ways to the stars who walked before him, like an artist mastering their craft by studying the classic works of old before mixing up what they learned into something new.

Any franchise painting on an empty canvas should give Boozer the paintbrush and get out of the way.


The Film

Just to highlight Boozer’s position and role malleability, let’s look at some Duke tape to see how an NBA team can utilize him in a variety of Pick-and-Roll situations, without even getting to the one-on-one creation card he can pull out of his sleeve.

Boozer running pick-and-rolls on the ball shows his ability to attack mismatches with drives and find teammates for good looks.

Boozer spaces the floor from deep in Pick-and-Pops, utilizing his shooting gravity to knock down C&S threes and attack closeouts with pump-fakes and driving touch finishes, creating a lethal shooting threat compared to the average screening roll-man.

Boozer’s finesse in the paint from a variety of angles and force at the rim when rolling hard offers a versatile play-finisher compared to the average screening roll-man, not to mention his ability to playmake out of the short-roll.

The Data
(as of 03.19.26)

Averaging 23 PPG – 10 REB – 4 AST / 2 TOV – 1.5 STL, Boozer seems to fill up the box score consistently whether you think he’s having a good game or not. In his time at Duke, he racked up 68 Stocks (BLK + STL) to 57 fouls, a good indicator for defensive instincts forcing turnovers without fouling.

Recorded 2 games with 15 REB, 2 games with 14 REB, 5 games with 13 REB, another 5 games with 12 REB; Boozer knows a thing or two about crashing the glass in case of emergency.

His best scoring outings were as follows: vs. Arkansas scoring 35 PTS on 1.4 PPP, vs. Indiana State with 35 PTS on 1.6 PPP, vs. Wake Forest with 32 PTS on 1.4 PPP, vs. Stanford with 30 PTS on 1.4 PPP, and vs. Florida with 29 PTS on 1.1 PPP.

Seemingly endless stat indicators hint at Boozers’ scoring versatility, shooting touch, rebounding instincts, and two-way feel being positives that will translate to winning at any level.

Synergy Playtypes:

Excellent or very good all-around scorer in most situations:

Excellent, Versatile Scoring Profile:

Boozer quite literally scored 1.0-1.5 PPP in every playtype other than off screens and handoffs, thriving in Post Ups (1.1 PPP), Spot Ups (1.3), Transition (1.4), ISO (1.0), Put Backs (1.4), and Cuts (1.5).

For comparison, AJ Dybantsa scored 0.88 PPP in ISO, in the 58th percentile, and 1.0 on Spot Ups, the 64th percentile, and 0.77 PPP as P&R Roll-Man, 14th percentile. Dybantsa thrived as P&R Ball-Handler, Transition, Post Ups, and Put Backs, but still scored less efficiently than Boozer in all those playtypes, except for his Put Back Rate.

Just to further highlight his scoring versatility, Boozer scored 1.3 PPP as the Roll-Man in P&R on 60 poss, and scored over 1.0 PPP on 63 poss as the P&R Ball-Handler. Breaking that up into pops vs rolls: 31 times he pick-and-popped for 1.3 PPP; 25 times he pick-and-rolled for 1.4 PPP; 4 times he slipped the pick for 1.5 PPP.

Are you picking up on the absurdly efficient scoring in nearly every playtype in nearly every situation on and off the ball?

Other than handoffs, off screen, and less scripted plays that don’t involve his patented putbacks, he’s rated in Top-20 percentile in all 8 other playtypes recorded by Synergy.

Offensive Engine Indicators – Team Shot Creation via Boozer’s Scoring + Playmaking in ISO, Postup, P&R Ball-Handler

Efficient shot creation including passes shows the decision making and execution ability of a primary ball-handler, which could be one of the sports’ few measures reflecting a player’s feel for the game.

Boozer scored 1.0 PPP on Drives for Duke; he preferred to drive left, averaging 1.1 PPP on 67 left-side drives compared to 0.9 PPP on right-side drives.

When including passes as a pick-and-roll ball-handler, Boozer’s shot creation for his team becomes even more efficient at 1.08 PPP on 128 possessions, staying at 1.1 PPP on another 72 possessions where the defense “commits” to him as a P&R ball-handler.

Compared to Dybantsa, AJ created 0.93 PPP on 356 possessions as P&R Ball-Handler including passes, a roughly 0.15 PPP worse than Boozer’s 1.08 PPP.

Cam’s ISO PPP, including passes to teammates, rises slightly above 1.0 in efficiency; Dybantsa’s rises to 0.9 PPP.

Boozer encourages defenses to double him in the post; when including passes on postups, Boozer creates 1.1 PPP on 241 poss (84th percentile); he creates just under 1.0 PPP on 121 postups where defense “commits”, and he creates 1.1 PPP on 91 postups where defense sends a hard “double” (85th).

Dybantsa does well out of the post, creating 1.2 PPP on 128 possessions for his team, a slightly better mark than Boozer on half the volume.

Boozer’s scoring creation indicators are so promising, he could take being a versatile efficient offensive hub to a full blown ‘offensive engine’ level for a franchise if his skillset is maximized for its quick processing efficient shot creation.

All in all, these efficiencies across every play type as both a scorer and team-first shot creator show how malleable Boozer’s game can be at any level, thanks to his efficient shooting versatility and high-feel decision-making.

Here’s one look at Boozer’s processing from Swish Theory’s Ben Pfeifer, who calls Boozer, “the best post skip passing prospect he’s ever scouted”:

Shooting Touch Indicators

42% C&S 3P% on 91 3PA
41% Pull-Up 3P% on 34 3PA
65% eFG% on 296 Shots At The Rim
61% eFG% on 255 Layups
94% eFG% on 35 Dunks
(9/12 on Hooks)

Overall Scoring & Creation

1.18 PPP
67% TS%
62% eFG%
1.7 AST/TO (133 AST)
26% AST% / 12% TOV%
62% 2P% on 338 2PA
42% 3P% on 125 3PA
78% FT% on 244 FTA

All-Time NCAA & ACC Ranks

1st in NCAA in BPM, Offensive BPM, Win Shares, Win Shares Per 40, Def Win Shares, Off Win Shares, and PER
1st in ACC in PTS | 2nd in NCAA in PTS
2nd in ACC in PPG | 9th in NCAA in PPG
1st in ACC in REB | 7th in NCAA in REB
1st in ACC in RPG | 13th in NCAA in RPG
2nd in ACC in Offensive RPG | 19th in NCAA in Offensive RPG
1st in ACC in Defensive RPG | 8th in NCAA in Defensive RPG
8th in ACC in AST
11th in ACC in AST
9th in ACC in STL
13th in ACC in STL / GM
4th in ACC in FG%
18th in ACC in FT%
12th in ACC in 2P%
3rd in ACC in eFG%
3rd in ACC in TS%
9th in ACC in AST%

BPM History

2nd-highest BPM ever (+20), up there with fellow Duke Blue Devil Zion Williamson for the most impactful collegiate season by impact rating.

Boozer joins Zach Edey and Steph Curry (2x) as the only members of the 30 USG% / 15+ BPM Club, via Chip Williams.

Cerebro Ratings & NCAA Data Viz

Cerebro Stat Glossary:
C-RAM (Overall Impact) | PSP (Scoring) | 3PE (3PT Shooting) | FGS (Playmaking) | ATR (Rebounding/Blocks) | DSI (Steals/Fouls)

What stands out most about Boozer compared to his peers in the conversation for the #1 pick is that Boozer combines the sum of his parts to project as a reliable half-court hub for an offense to consistently create good looks every night out for the next decade. Boozer’s ball skills, footwork, and mix of efficient scoring versatility, efficient team shot creation, playmaking execution, and team-first decision-making create a walking advantage creator who bends defenses and generates efficient points at will.

Freshman Boozer rated higher that Dybantsa and Peterson overall and in almost every aspect of the game that Cerebro tracks, other than Peterson’s lights-out 3pt shooting metric.

Boozer’s cumulative career ratings this far in all games recorded by Cerebro are elite as a scorer, rebounder, and defender, while ranking highest in every category except for being one point shy of Peterson’s defense and ranking a close 3rd in 3pt shooting. This highlights Cam’s elite traits and scoring efficiency, making winning plays like rebounding and playmaking, the ability to spread the floor from deep, and a special feel for touch passes and turnover-forcing defense, and shows how incredible his now-elite 3pt shooting development has come from his days at the grassroots level.

Individual perimeter defense and lack of quick first step burst could limit Boozer exploding past anyone or shutting down anyone on the perimeter, like most power forwards he’s more of an ultimate connective hub, but his instincts will help him force steals, his versatility will help him switch 3-5 to some degree, and he is effective in one-on-one offense in other ways by using his footwork, awareness, and skill to score and create advantages.

Efficient Shooting Line, High Usage, Low Turnovers

There is only one freshman since 2008 to hit Boozer’s marks in shooting percentages and shooting volume on twos, threes, and free throws at his usage.

According to barttorvik, Boozer is the only NCAA Freshman in their database with over 30% USG% who shot 61-39-78 on 10 2PA — 3 3PA — 7 FTA. For comparison, Dybantsa shot 57-33-77 on 13 2PA –– 4 3PA –– 9 FTA.

The chart below visualizes NCAA freshmen who meet a handful of stats attempting to show scoring efficiency and high-feel decision making, with the x-axis showing volume of shots at the rim horizontally, and turnover percentage vertically on y-axis.

Boozer has the most shots at the rim of all these prospects as a freshmen, and the 2nd-best turnover percentage while doing it, lagging behind one of the draft class’s other best decision-makers, Stanford Ebuka Okorie.

← Rewind to 2023: Scouting The Montverde Sunshine Classic


#12 Cam Boozer, 6’10” Forward, Columbus

A strong-shouldered forward with feathery shooting touch like his NBA All-Star dad, the 6’9″ Cam Boozer quickly become a household name in draft circles as a Top-3 2026 prospect, with this Montverde-Columbus marquee matchup featuring another potential Top-3 prospect (in 2025), Cooper Flagg, just to name two of many exciting prospects in this contest.

Cam Boozer and Donavan Freeman rate strongly here as both scorers and creators, in a similar range of output this weekend as Cooper Flagg and guards Rob Wright and Darius Acuff.

vs. Montverde
20 PTS
8 REB
5 AST / 8 TO
4 STL + 1 BLK
6/13 FG & 7/10 FT
(30 MIN)

A powerful yet graceful dancing bear 6’9″ forward who rocks rims on rolls through the paint, shows soft touch on the jump shot, looks ahead for outlet passes, and glides through defenses on off-ball cuts, Cam sure plays like a Boozer.

In the Montverde matchup, Boozer came out with more intensity in the second half, focusing on powering through people, showing sound handles on the ball, lookahead vision as a playmaker, and leaving huge impact as a rim-finishing play-finisher, even blocking a Flagg driving layup in help defense before finding his brother Cayden on the break off the turnover.

His outlet passes to jumpstart fast breaks were plentiful, even featuring a highlight coast-to-coast live-dribble behind-the-back dribble corner kick 3pt assist!

Boozer flashed all the developable dribble-pass-shoot ball-skills with strong finishing power and good off ball movement timing. This powerful 6’10” hammer who nails deep range jumpers projects to be an offensive force at the highest levels, excelling in similar areas to his NBA All-Star dad, while showing natural scoring creator tendencies for team-first shot creation.

Cam posted the 6th-highest overall impact rating in the event with 8.9 C-RAM, practically tying Cooper’s overall rating. Boozer was more effective as a scorer with a 79/100 PSP rating in the matchup, slightly more impactful defensively with an 87/100 DSI, while mostly matching Flagg in Floor General Skills and At The Rim effectiveness (75 FGS and 70 ATR)

Cam Boozer and Cooper Flagg sit atop future NBA Draft big boards for a reason; big wing/forward plus-defenders who can be relied on as halfcourt offensive creators, connectors, and play-finishers tend to be impactful winning basketball players.

The Good
Scoring at all three levels on and off the ball
Pick-and-pop, catch-and-shoot, relocation threes
Vertical gravity rim-running and well-timed paint-cutting
Drawing fouls with brute strength, sound footwork, solid handle
Clear vision, passing ability, grab-and-go playmaking chops looking ahead on fast breaks
Filling out the box score on both ends like a Shawn Marion or Aaron Gordon multi-faceted turnover-forcing play-finisher

The Bad
Losing control. Whether it be his own strength, the dribble, body and ball control at times – focused effort on spatial awareness, gaining the proprioception feeling of understanding one’s own body movements in space, could work wonders
First half lacked energy and focus compared to second half, but played opponent even from that point in a tough matchup

In football, a dancing bear tends to be a nickname for powerful defensive ends wh are surprisingly agile; large in their frame, yet quick on their feet.

Boozer is the strong, yet graceful dancing bear that any franchise dreams of building around.

A true modern day do-it-all power forward bending the floor on and off the ball, pummeling his way through defenders throwing elbows and shoulder swings, moving skinny through gaps with fundamental footwork fundamentals, finishing below the rim with an endless array of moves, rebounding everything in sight, forcing steals and processing team-first decisions from high to low.

Cameron Boozer remains the clear #1 2026 NBA Draft Pick for me through years of scouting due to him being one of the most impactful, efficient, effective, versatile shot-creating prospects to ever play the sport.

If anyone can be the tentpole that holds up an entire city in the circus that is the NBA, it’s the guy who always plays, always plays hard, always plays smart, always makes team-first decisions, and always generates good shots for his team.

While the basketball world eats up dunks, middy pull-ups, and fadeaways, one lucky team might just wind up landing one of the biggest winners the sport has ever seen, if only they buy low on the Dancing Bear Market.

The post Cameron Boozer, Duke’s Generational Dancing Bear appeared first on Swish Theory.

“Anyone who thinks you can have infinite growth in a finite environment is either a madman or an economist.”

Stubbornly insisting on a single approach can lead to blind alleys. Sometimes, looking at things from a different angle and changing perspectives can reveal unexpected details and help untangle contorted situations.

While I do not have a background in the more technical aspects of basketball, I compensate by putting to good use my expertise in other fields to better understand what I am watching. The pinnacle of interdisciplinary approaches, in my mind, is Evan Zaucha’s article, “The Art and Science of ‘Feel’ in Basketball”. Evan brings his neuroscience background to the forefront of his analysis to describe what the term ‘feel’ actually means in basketball terms.

Similarly, I intend to go beyond the traditional borders of basketball analysis, mapping my knowledge of ecology onto the basketball court.

Introducing the concept of density-dependent factors

A density-dependent factor is defined as “any force that affects the size of a population of living things in response to the density of the population.”

In nature, there are positive density-dependent processes, like diseases that would spread faster among individuals who live in close proximity, and there are negative density-dependent processes. In our case, we’ll take into account mostly the latter processes.

For example, the growth rate of mammal populations is generally influenced (negatively) by the density of the individuals.

Let’s take a look at how a deer population evolves. As population density increases, the amount of available food in the sample area will decline. As food declines, the body condition of individuals worsens. The birth rate is directly proportional to the animals’ body condition: when body condition is poor, the birth rate is low.

Ultimately, high density leads to scarce food supply and poor body condition, which in turn leads to a declining growth rate of the population. You can see already where this is headed.

Another variable that affects the process is the quality of the habitat, which can influence the rate at which growth declines. Habitats rich in resources can sustain higher individual densities for longer and slow the decline in growth rate; poor habitats will have declining growth rates.

(Credits @www.msudeer.msstate.edu)

This kind of process works for plants as well: just think about a very dense group of seedlings competing for the solar light.

NBA Ecosystem

An ecosystem can be broadly defined as a community of living organisms that interact with each other and their non-living environment. While I understand it doesn’t reflect what we commonly consider an ecosystem, the NBA itself can fall within this (broad, as I said) definition.

I’ve been meditating for years on the concept of the “NBA Ecosystem”: an interconnected set of biotic and abiotic components where we can identify rules and processes that we find every day in a coral reef or a boreal forest, for example. A reality that can be studied and analyzed through an ecological lens, alongside the traditional ways we analyze sports.

If we consider the entire National Basketball Association as a complex ecosystem, every team can represent a distinct habitat with its resources, population, and relative interactions. In this context of team-habitats within the NBA ecosystem, we can adopt an ecological approach to roster building, not focusing on the pieces themselves, but analyzing them in their connections with other biotic and abiotic components.

Density-dependent Growth and roster building

NBA teams can be assessed as peculiar habitats, and players as their populations, so we can try to apply the same models we generally use in ecological studies. I often think about similar ecological concepts when looking up this or that NBA roster or reading about a certain signing. And although they were modeled for a completely different field, I do think keeping in mind how these mechanisms work can help us understand certain NBA situations and players’ outcomes.

Density-dependent processes can be a useful tool for seeing rosters from a different angle, while adapting the notions we already have. First of all, rosters can have a max of 15 regular players plus three two-way contracts; the sheer number can’t be higher or lower, besides some rare exceptions. Then, what can be considered the “density”? It depends on the number of players occupying the same niche within the team dynamics. A 10-year vet and a rookie clearly don’t occupy the same niche nor have the same role with the team. In these years of rumination on the topic, I found density-dependent growth particularly fitting for the “population” of rookies and younger players who still need to develop their game.

While in the ecological studies, “growth” represents how the number of individuals in the sample area changes (generally expressed with a rate) in a roster where the number of individuals is pretty much fixed It takes on a more abstract meaning, representing the improvements of a player’s basketball ability.

The richness of resources in the context of a team/habitat is more labile from our point of view. It would take into account the number of minutes available, the quality and quantity of the staff. Three young players competing for minutes in a rebuilding team is a starkly different situation than three players competing for a similar share of minutes on a contending team with a set rotation consistently aiming for the best possible result.

This is an interesting excerpt of an article written by Tom Orsborn for the San Antonio Express-News about Spurs’ increased attention for film studies. The case was unusual, but it gives us a nice hint about something that otherwise would usually be inaccessible: even the potential hours available to study the tape can become resources young players are “competing” for.

In summary, if we consider it a functional parallel, an NBA team represents the habitat of the young players’ population, whose basketball skills’ evolutionary trajectory depends on the number of its individuals and the richness of opportunities, staff, and facilities. A fruitful habitat for maximizing these kinds of developmental resources is not guaranteed.

Brooklyn Nets, a concerning habitat?

The opening quote of this article could also replace “an economist” with “a Brooklyn Nets fan” (except for Lucas Kaplan and other rational Nets fans). The Nets represent a great example of what I’m trying to convey, and their moves during the last offseason were the spark that made me feel the urge to write about this topic.

The Nets’ roster at the beginning of the season (via spotrac.com)

With five rookies and a handful of other players who still need development competing for the same resources, the Brooklyn Nets could soon find themselves with a “declining growth rate” caused by the density within their habitat.

Looking up the Brooklyn Nets’ current per-game assists leaders represents a mystical experience: an apparent balance that hides a reality of shortcomings. All of them occupy a similar niche; all of them compete for playtime and reps; all of them will consume coaching staff resources. Considering also the fact that this season’s rookies are looking like players who need a consistent development path to impact, it is safe to assume not all of them will succeed and probably won’t have an ideal trajectory.

To me, the bigger issue is accumulating five first-round picks in a single draft: it implicitly punts the value of these picks as they are all competing for the same scant playing time/resources. Even more concerning is that all five of the selected players are fairly low-floor. A few of them will likely bust pretty hard. – The Case for Egor Demin by Avinash Chauhan

As Avi demonstrates, the concept of “overpopulation” that can limit the development of young players is something that already stuck in the back of our heads through empirical research and observations. The parallel with the density-dependent factors offers a more standardized explanation of the dynamic.

The byproduct of this messy ecological situation is evident. The team tried to find a balance, assigning players like Ben Saraf and Nolan Traore to the Long Island Nets, where they had to sail the insidious waters of the G League. Meanwhile, Egor Dëmin has his minutes and chances, but his season has been characterized by highs and lows (although it looks like he’s figuring out some things lately).

The release of Cam Thomas at the last trade deadline can be considered a symptom of the process. In a vacuum, it represents a potential waste of assets for the team, but on the other hand, it frees up resources.

Historic examples

The past offers us plenty of examples of the processes we’re examining if we look closely enough. Most rebuilding teams go through phases of overpopulation that are probably a natural consequence of trying to have and take as many draft chances as possible. The San Antonio Spurs during their 2022-2025 rebuild represent a great example I particularly care about.

The 2023-24 Spurs roster

Players like Dominick Barlow, Sidy Cissoko, Sandro Mamukelaishvili and even Blake Wesley or Jamaree Bouyea (who, to be fair, bounced around quite a bit before finally finding his niche this season) didn’t shine or had the chance to shine in this extremely young, extremely dense roster. And all of them are finding more success elsewhere.

Cissoko had some clearly likeable qualities as a prospect, but didn’t improve much from rookie to sophomore season, and the Spurs couldn’t find space in 2024-25 when they were already trying to put together wins. In this particular situation, the process was probably sped up by how quickly the team found their cornerstone (and it likely also applies for the Thunder at the time). When a team just drafted a young phenomenon and owns several future draft picks, the clock starts ticking early for those who are on the margins of the roster.

In a similar quickly developing, hyper-competitive environment, it becomes less likely for two-way players like Barlow and Bouyea to break into the rotation. Although there were probably some signs of Dom Barlow’s trajectory, especially considering how good he was at the G League level at a young age.

In the grand scheme of things, most of this stuff becomes irrelevant when your team gets the 7’4 lottery prize, but winning on the margins gives longer windows of opportunity. Look at it the other way around: how irrelevant was it for the Philadelphia 76ers finding their current starting power forward as a result of this process (Sixers? Process? Unintended pun)?

Acknowledging this process, it becomes easier to recognize buy-low, low-risk/high-reward occasions for teams disposing of plenty of resources. Besides the aforementioned Dom Barlow opportunity, Moussa Diabate going from an end-of-the-bench piece for a competitive team to growing into a high-level rotation piece for the Hornets is a notable example. In these cases, pre-draft evaluations and the G League sample are particularly relevant to identify the ideal candidates.

Another player that could become the most recent, valid argument in favor of this thesis is Ousmane Dieng. Since he left Oklahoma City, the French forward is showing things he didn’t have the chance to display consistently in the depth of the best team in the league.

The Houston Rockets from a few seasons ago are a slightly different but no less interesting case-study: players like Usman Garuba and Josh Christopher got devoured by the rebuild meat-grinder. Cam Whitmore is enduring a similar fate, though there seems to be some more attitudinal stuff going on with him. Could his issues be fixed by devoting more off-the-court attention to these issues in a less developmentally-dense environment?

It is obviously hard for us, as outside observers, to distinguish between those who simply weren’t good enough and who didn’t get enough chances to improve and have a better developmental trajectory in this case. However, those constitute interesting data points anyway.

Natural selection and density dependence

If you endured the reading of this piece to this point and followed NBA basketball in the last few years, you probably realize one of the weaknesses of this theory (or ramblings?).

Recent NBA history shows us that relying on sheer “natural selection” putting prospects in a highly competitive environment represents a functional strategy of long-term team building. Stockpiling as many prospects as possible and just find who is able to figure things out in the league seems to work decently enough.

Just think about the reigning NBA champions, the Oklahoma City Thunder.

Aleksej Pokusevski, Theo Maledon, Darius Bazley, and many others. Many players indeed busted, and many of their assets ended up in the meat grinder, but the selective pressure also allowed them to identify many pieces that are currently part of the clear-cut best team in the league.

However, the density-dependent processes remain important because not every team starts from the same foundations, with the same number of draft opportunities or resources. “Natural selection” operates within the density-dependent processes, and acknowledging them and how they work can help maximize the outcomes.

Wrapping it up

In high school, I studied Latin for 5 years, even though I attended a scientific high school. Many criticize its teaching because it’s a dead language and doesn’t have much value outside the academic world. However, Latin isn’t taught for its utility; it’s taught as a mental exercise to stimulate the identification of connections and instill a certain “forma mentis” in students.

I realized this article represents something similar. It doesn’t presume to solve team-building issues by adopting just a couple of ecological models. But this article humbly wanted to be a useful mental exercise, something that can stimulate the research of patterns and a transverse, interdisciplinary approach in a field that sometimes is a bit too vertical, fossilized in its knowledge.

The post Density-dependent Growth – an interdisciplinary look at roster building appeared first on Swish Theory.

If this issue were yet another symptom of our decaying online discourse, then there’d be no use in me writing this article or you reading this article. However, this same uncertainty around determining and quantifying player impact still persists at the highest levels of our sport, and it’s the reason why institutions, armed with premium datasets and hordes of full-time scouts, still get it wrong. Every year, draft boards fracture, bad contracts are given out like candy, and team-building philosophies collapse under any sort of playoff inspection.

Take the years-long debate over who should be the number one pick in this year’s upcoming NBA Draft out of Cameron Boozer, AJ Dybantsa, and Darryn Peterson. For some, Cameron Boozer is the drop-dead choice. A player who represents the Platonic ideal of prospect productivity, currently in the midst of one of the greatest freshman seasons of all time. At the same time, however, you have anonymous NBA scouts questioning whether he’s even a franchise cornerstone at the levels of his contemporaries.

What these issues and debates reveal is not confusion of talent or disagreement over players, but a deeper and more intrinsic struggle over what exactly player impact is, and how it should be determined. To me, at least, the issue stems from how we treat player impact. As if it were a single, unified concept that can be ranked from good to bad. So, before we ask the question of ‘who’s better than who’ or ‘who deserves what contract’, we need to first define: what exactly is player impact?

The Two Degrees of Impact

The framework I will try to explain in this article stems from a simple but too often overlooked truth about basketball, which is that not every action carries the same value. And over the course of a 48-minute game, hundreds and hundreds of actions will occur with varying levels of influence.

This is because basketball (and many other team sports) is, at its core, a stochastic sport. This means outcomes emerge from a web of probabilistic events rather than deterministic sequences, and small variations compound across possessions. As a result, actions cannot be treated as equal simply because they occur within the same possession or box score.

Every action that takes place on a basketball court is a probabilistic bet that seeks to tilt the game-state towards one direction; however, most mainstream analysis seeks to collapse all of these actions into narrow sets of outputs: points, rebounds, assists, etc. And in doing so we end up over/under valuing certain player archetypes that better suit our own personal biases.

Cumulative Impact

Following on from that jargon, we can now get into the weeds of the framework, and the first idea I need to introduce is that there are two levels of impact that a player can exert on a game, with the first being what I currently refer to as cumulative impact. Cumulative impact is the influence a player exerts on a game through actions whose value emerges from repetition and continuity. Cumulative players generate and preserve extra possessions, and while these actions do not produce high-value outcomes in isolation, they shape the conditions in which future possessions occur. Rather than deciding outcomes outright, these actions reduce the team’s reliance on low-probability solutions.

Basketball behaviours that indicate a player is cumulative, and some statistical indicators:

ability to extend and complete advantages

• assist rate 
• potential assists
• secondary assists 

ability to generate extra possessions

• offensive rebound rate
• steal rate
• offensive fouls drawn
• deflections

ability to preserve possession integrity

• turnovers per game 
• turnover percentage
• assist to turnover ratio

ability to impact possessions without direct ball involvement

• gravity rate
• opponent rim attempt frequency
• opponent fg% at rim
• defensive on/off

However, while cumulative impact explains how teams build and sustain momentum, it doesn’t explain how they convert that control into outcomes. You can control the chessboard for hours, accumulate pieces, dictate the pace of play, but at the end of the day, the game is still decided by checkmate.

Decisive Impact

This brings us to the second level of player impact, which is what I’m calling decisive impact. Decisive impact is the influence a player exerts on a game through high-difficulty and high-leverage actions that directly resolve possessions and sharply alter the game state. Where cumulative impact shapes the flow of a game, decisive impact collapses that flow into results. These moments disproportionately affect win probability and rely more on individual execution under pressure.

Here are some behaviours that indicate a player is decisive, and some usual statistical indicators:

ability to independently create/prevent advantages:

• pts/75
• ts added per 100
• shot usage
• FTA per 100
• block rate

ability to execute when time, space or structure is constrained:

• grenade percent
• grenade efg
• isolation efficiency
• clutch efficiency
• contested shot efficiency
• STOP%
• rSTOP%

The Four Quadrants of Player Impact

I’ve always been uncomfortable with binary thinking, and it’s probably why, growing up in school, I was always drawn more towards the humanities than STEM subjects. To me, very few meaningful things in life fit neatly into two categories, and player impact is no different.

In reality, we know that players vary in just how much cumulative or decisive impact they exert on games and that these dimensions are independent of each other. It’s why a player can be highly cumulative without being highly decisive, and why a player can be highly decisive without being highly cumulative.

Conceptually, I think this framework is best visualised as a fluid, four-quadrant model:

Low-Impact Players

These are the players whose presence does little to meaningfully alter either the structure or outcome of games. They neither accumulate influence through their repeated activity on the court, nor do they have the capability to resolve high-leverage possessions. This does not mean they lack basketball skill, but rather that their actions do not scale in either volume or difficulty. YOU SHOULD AVOID DEDICATING EXTERNAL RESOURCES TO THESE PLAYERS AT ALL COSTS.

Structural Players

Players in this quadrant are your textbook floor-raisers. The RAPM darlings. Rather than decide games outright, they shape how games are played through influencing a large volume of possessions. Their impact is rarely spectacular in isolation, but compounds over time as they increase the frequency of point-scoring opportunities. YOU SHOULD DEDICATE RESOURCES TO THESE PLAYERS PROVIDED YOU HAVE THE REQUIRED EVENT PLAYERS TO CAPITALISE ON THEIR IMPACT.

Event Players

Players in this quadrant are your archetypal ceiling raisers. They are those players whose value lies in their proficiency in high-difficulty situations. The Ball Don’t Stop alumni, if you will. And while their impact might not be felt continuously over a game, it will no doubt manifest itself in those high-leverage moments where only the strong survive. YOU SHOULD DEDICATE RESOURCES TO THESE PLAYERS PROVIDED YOU HAVE THE REQUIRED STRUCTURAL PLAYERS TO PROVIDE THEM AMPLE CHANCES FOR IMPACT.

Dual-Impact Players

This is the quadrant occupied by the true outliers of the sport, and those special hoopers who had/have the ability to both: increase the amount of and resolve their team’s scoring possessions. There is rarely a moment in a game where they are not either directly or indirectly involved in a possession. YOU SHOULD DEDICATE THE MAJORITY OF YOUR RESOURCES TOWARDS TRYING TO ATTAIN THESE PLAYERS.

Why the Most Valuable Players Tend to be Dual-Impact

An important, and perhaps the most important clarification that needs to be made before going further, is that within the same quadrant/archetype, players can vary enormously in quality. Not all structural players are equally valuable, nor are all event players, and this framework, when applied lazily, can flatten those distinctions. To me, what explains these gaps in quality are not the archetype itself, but the constraints under which players operate. Inherent physical and biomechanical limitations, as well as the external team environment, shape the range of total actions a player can perceive as viable. And while you can adapt your game around these constraints to become an effective player, these constraints will always exist and limit your ceiling.

A useful way of conceptualising this is through Plato’s Theory of the Forms. In Plato’s theory, the physical world contains imperfect instantiations of ideal Forms, abstract, complete expressions of concepts like justice or beauty. A drawn circle may resemble the Form of a circle, but it will never fully realise its perfection. Dual-Impact players represent the ideal Form of player impact: the fullest and most complete expression of game influence, where the physical capacity, technical skills, and cognitive processing all align. Structural and event players are merely imperfect (but still valuable) instantiations of that form, approximating along one or two of those dimensions, but not all. And it is this incompleteness that introduces fragility into their impact when conditions change.

Beyond any specific technical or physical traits, what truly separates dual-impact players from the rest of the field begins in the mind. At the highest levels of the sport, where technical skill-sets overlap and physical margins narrow, what separates players is not simply what actions they can execute or how they execute, but when and why they execute. Dual-impact players show a heightened sensitivity to the spatiotemporal structure of the game and understand that possessions are not isolated events, but linked sequences whose value compounds across time. This cognitive elasticity is what allows them to constantly shift their thinking from an individual to a team level, and the emergent result of this advantage is that their individual impact is less sensitive to their external environment.

Event and structural players, by contrast, are constrained by the cognitive tax of over-specialisation. Event players are forced to operate in high-leverage moments repeatedly, becoming over-reliant on situations that cannot be sustainably generated, and structural players become over-reliant on teammate continuity and control. In both cases, impact becomes brittle and increasingly sensitive to the external environment.

Basketball, ultimately, is a team sport, and any individual player’s impact only exists in relation to the environment it shapes. This is where the value of dual-impact players becomes overwhelming. Because they influence both the conditions under which possessions occur and the outcomes those possessions produce, they reduce the sensitivity of a team’s success to lineup construction. This is because it allows their GMs and coaches to allocate resources more efficiently, to surround them with lineups that lean towards offense or defense without sacrificing anything. This is why historically great teams like the OKC Thunder now or the Golden State Warriors in the past could field such defensively slanted teams around Stephen Curry or Shai Gilgeous Alexander, as the multiplicity of their skill-sets means they could make up for any gaps in offense or defense.

So…Why Do We Keep Getting It Wrong?

If dual-impact players represent the fullest expression of influence within a basketball game, then it raises an uncomfortable question: why are they so often misidentified and misunderstood? At a fundamental level, we do not evaluate impact directly, we evaluate signals of impact. Basketball, as both a sport and spectacle, privileges actions that are visible and narratively decisive. Event impact fits nicely into this perception, and a tough iso bucket or a chasedown block are immediately legible to both audiences and decision makers. As a result, event players are intuitively perceived as controlling games even when their impact is episodic rather than systemic. This perceptual bias is reinforced by the inherent structure of basketball discourse itself. Highlight clips, box score, scoring averages, and usage rates all reward possession-ending actions, and even most advanced metrics remain possession-local in nature. The consequence of this is that players who exert influence by shaping the conditions of future possessions (through indirect actions) struggle to announce their own value with the same clarity.

Due to this, event players are often easily mistaken for dual-impact players. Their ability to generate high-leverage outcomes under pressure is rightly valued, but when this capacity isn’t paired with the ability to frequently improve the frequency and quality of possessions, then its overall influence is too limited. Crucially, the inverse error also exists, just in fewer cases. Structural players are often overvalued in environments that reward stability and scale, where their ability to raise baseline efficiency can be mistaken for universal sufficiency. In this sense, both event and structural players are epistemically misleading, just in inverse ways. Event players are often overvalued due to the visibility of their impact, which makes it easy to narrativise, and structural players can be overvalued for those same opposite reasons.

There is also a further distortion that emerges online in spaces where we debate basketball, once this perceptual imbalance is recognised. Because event impact is more immediately legible and thus accessible to casual fans and mainstream media discourse, more analytically literate observers can start to define their analysis in opposition to it. Structural impact, requiring specialised language and a trained eye to identify, becomes not just a category of value but a signal of understanding itself. In this way, otherwise intelligent analysts can reproduce the same error as a casual observer, converging on a form of groupthink where what is hardest to narrate is assumed to be most important.

Implications for the Draft and Free Agency

Once player impact is understood as context-dependent rather than absolute, the implications for roster construction begin to clarify themselves a little more, especially when it comes to the draft and free agency. This is due to the fact that both of these mechanisms operate under different constraints and risk profiles, which change how different impact archetypes are valued.

Let’s start with the NBA Draft, which is by definition an exercise in projection under uncertainty. Teams that are rewarded with a lottery pick are generally weaker teams that lack organisational coherence and are years away from playing meaningful playoff basketball. In these developmental contexts, event impact is inherently fragile. High-leverage, possession-deciding actions only accrue value when a team is already capable of consistently generating competitive possessions. Without that foundation, event-oriented prospects are forced into roles that exaggerate their weaknesses and develop bad habits despite gaudy box score numbers or Twitter mixtapes. We also must acknowledge historical trends and how raw scoring output has lost a lot of its relative value due to the skyrocketing of league-wide offensive efficiency. Kobe Bryant’s 35.4 points per game in 2005-06 came in a league environment where the league average ORTG was 106.2, and teams averaged roughly 94-96 possessions per game. Luka Doncic’s 33 points per game this season, however, is occurring in an environment where league ORTG exceeds 115 with roughly 101 possessions per game. This means that as the entire league has become more efficient, the marginal value of raw volume scoring has declined. This makes structurally-inclined prospects, those who generate extra possessions and stabilise lineups, the more robust draft investments, even if their high-end outcomes don’t appear as high as the next prospect.

Free agency, however, operates under some slightly different logic. Established teams, those built around one or more dual-impact players, already possess the structural capacity to survive the regular season and get to the high-leverage environments of the playoffs. In those contexts, the marginal value of additional cumulative impact diminishes, while the value of decisive impact increases. It’s in these arenas where event-oriented players who struggle to justify primary roles can truly shine, as their ability to resolve possessions can meaningfully swing playoff games. When used in shorter stints or in tilted matchups, they can buoy the defects that come with their profiles over large sample sizes.

This asymmetry helps explain why certain player profiles appear to be ‘overdrafted’ or ‘underpaid’ early, only to resurface as valuable contributors later in their careers. (I’m looking at you, Aaron Gordon and Andrew Wiggins). The most shrewd organisations understand this distinction and resist the temptation to evaluate players as static entities.

However, there is a human element to these decisions that prevents teams from disavowing the historical mistakes of the past. Draft choices must be justified immediately, and event-heavy profiles must provide a form of narrative insurance. Their impact is legible, and their upside can be sold easily to owners and fans. “The talent was undeniable” is an excuse that allows front offices to skirt public scrutiny and keep their cushy, million-dollar jobs in NBA executive roles.

Taking a Wider Look

A framework is only as useful as its ability to scale, and the distinction between cumulative and decisive impact does not stop at the individual level. In basketball, where five players share the floor and possessions are both numerous and interconnected, team performance is best understood as the aggregation of individual impact profiles. For all the Xs and Os and schemes a coach wants to run, you can’t coach out a player’s built-in tendencies they’ve developed over years and years of reps.

At this point in the article, I think it’s clear that what makes dual-impact players so valuable is the fact that they don’t grow on trees. And so, a lot of what team-building becomes is being elite at aggregation and figuring out how to maximise interactions between incomplete skill-sets. Procure too many event players on one team, and you become over-reliant on situations you can’t sustainably generate. Your success as a team hinges on shot-making and individual brilliance, which causes you to become a high-variance team. However, if you acquire too many structural players and you become over-reliant on possession and territorial control, which causes you to become a low-variance team. We can observe that in both of these cases, stacking too many of one impact type on your team causes you to increase your margin of error, which matters all too much in a large sample size sport like basketball, where outcomes are decided across multiple games across a season.

This tension helps to explain why regular season and playoff basketball often reward different team profiles. This balance between cumulative and decisive impact begins to explain why certain teams consistently out/under perform expectations in specific competition formats. In large sample size formats such as the regular season, teams built with strong cumulative foundations tend to be rewarded for their efforts. Their advantages lie in reducing variance in possession quality. Over an 82-game season, those small, repeated gains compound, insulating them from the inevitable shooting slumps that derail more volatile teams. However, as formats compress, be it a playoff series or a single elimination cup game, the equilibrium begins to shift. Smaller samples magnify variance and reduce the value of pure accumulation. In those environments, teams with a greater share of decisive impact are better equipped to survive volatility, as they possess players capable of converting limited opportunities and swinging games on only a handful of possessions.

Ultimately, the same distinction that separates players at a micro level re-emerges at the macro level of teams, which is the cognitive difference. Teams built around event-heavy profiles demand a high level of mental bandwidth to constantly pull a rabbit out of the hat to win games, and, conversely, teams built around structural players demand a level of constant concentration and collective synchronisation over long stretches, to a point that isn’t humanly possible. What separates the best teams, much like the best players, is their elasticity and adaptability, and there is an equal cost of leaning too far into one identity, just in a different currency.

The post Structure and Event appeared first on Swish Theory.

Stanford Freshman Guard blends incredible skill, speed, and feel for the game

“I’m just playing to win and just help my team however I can to just get the win.” – Ebuka Okorie on his mindset

When you combine Ebuka Okorie’s quick first-step burst, stop-and-pop pull-up shooting, masterful ball control, effective flare handles, and one-of-a-kind finesse finishing at the rim, a lethal self-creating multi-level scoring threat is born.

Okorie speeds past any defender standing in front of him, threatening to pull up for a jumper at any time from anywhere on the court or get to the rim for a high degree-of-difficulty finish that he makes look routine.

Since I’ve started scouting potential NBA draft prospects in person, no player’s finishing at the rim has stood out as much as Okorie’s in-person, between his craftiness, creativity, and soft touch finishing. If Kyrie is the mountain top of masterful, crafty handle, creative small guard finishing around the rim, Okorie has started his climb, hoping to etch his own name, plant his own flag as one of the all-time finesse finishers.

In my 2024 Interview with Ebuka, I commended him for his feel for the game, asking him about his influences:

“I really like your decision-making out there, your patience, your jump shot. Are there any players you steal moves from or model your game after?” – RK

Ebuka says he studies two of the best guard finishers to ever play:

“Yeah, I just like watching top guards like Kyrie Irving and Steph Curry, obviously. I also like watching just any All-Star guards.”

There were two other point guards who came to mind when watching Okorie play two years ago for Brewster Academy, sharing aspects of Rajon Rondo’s and Dennis Schroder’s respective games – Schroder’s blend of first step burst, point guard instincts, and heavy shooting diet of pull-up shooting and finishing at the rim; Rondo’s next-level understanding of the game, his defensive instincts to force turnovers with the heads up awareness and then to make team-first passes up the floor pushing pace off them, and that special touch, spin, placement, and timing he’d put on passes to hit his teammates right where they wanted the ball in their shooting pockets to set them up best as play-finishers.

A high-volume pick-and-roll maestro self-creating ISO killer who threatens the pull-up shot, the finesse finish, and the clean dime every time down?

Ebuka Okorie is the most underrated Lottery Pick hiding in plain sight of the 2026 NBA Draft.

Quotes

Learning Basketball, a Swish Theory Podcast:


“Unbelievable handle, exceptional burst, can shoot… high-variance upside bet… absurd scorer.” – Ben Pfeifer, Swish Theory


“He can finish any shot you can think of at the rim.” – Ryan Kaminski, Swish Theory


Stanford HC Kyle Smith on Okorie’s draft status:

“My pitch has been – if you want to be in the place where you are leading a team and getting the most minutes to develop what you want to be as a pro, and essentially, we’re pros now, they’re getting paid. So I think Stanford’s the best option.

But… Look, you’re leading a team, you’re 19. But now, if someone in the NBA says, hey, we’re gonna take you at 12 and you’re our starting point guard, well, that’s something to consider.”

NCAA Moments, Impact & Efficiency

(all data as of 3.11.26)

Okorie walked onto Stanford’s campus as a four-star as the 12th-rated point guard in the country. (On3, 247)

Ebuka’s +10.3 C-RAM ranks in the Top-10 among top 2026 Draft Prospects, via Cerebro Sports.

Okorie’s all-around game at Stanford is rated highly by Cerebro – as a defender (86 DSI, 1.6 STL/gm), floor general (69 FGS, 3.6 AST / 1.8 TOV), 3pt shooter (80 3PE, 2 3PM on 36% 3P%), and scorer. (87 DSI, 23 PPG on 46% FG%)

Combining his high school stats with his freshman college stats for a total of 81 college+high school level games tracked by Cerebro, Okorie shot 53% 2P% on 534 2PA, 35.6% 3P% on 396 3PA, 83.5% FT% on 315 FTA, scoring 58.6% TS% overall.

Ranking 5th in the country in scoring and 2nd among freshmen (23.1 PPG), even ahead of Cameron Boozer, Ebuka Okorie is more than just a crafty point guard; he’s a certified walking bucket. Okorie’s seven 30-point games are tied for the most by any freshman in ACC history (Marvin Bagley) and fourth among any player all-time in the conference’s history. On top of being selected to the All-ACC 1st Team & All-ACC Rookie Team, Okorie’s scoring average is on pace to pass RJ Barrett for the top mark in ACC history by any freshman ever, while being the nation’s co-leader in games with 25+ PTS scored. (14g)

Okorie’s handle is simply electric, with few able to accelerate, stop on a dime, change directions, and throw in dribble combo moves along the way as smoothly as Ebuka makes it look.

The scoring has been incredible, and what’s even more impressive is his rapid development, consistently improving as the season goes on. Starting the season with 4 20pt games, dropping 3 30pt games soon after, then dropping the hammer with a 36 PT – 9 AST statement game vs UNC to put this Stanford team on the national radar.

Cracking the 40pt mark in a blowout over Georgia Tech, Ebuka reached that total with only 3 3PM, showing his scoring abilities within the arc (9/15 2P) and ability to maneuver his body smartly to draw the foul. (13/13 FTA). Squeezing in another 30pt game against Pitt, once again Ebuka showed off his smooth scoring abilities inside the arc (8/13 2P) and at the free throw line (9/9 FT); the game before, against California, the 6’2″ guard pulled down 13 rebounds.

Dropping 33 PTS on 71% eFG% vs NC State, Okorie showed off the double-edged sword of floor-bending gravity as a pull-up three pick-and-roll artist – rising and firing for off the dribble jumpers as he navigates picks and gets to his spots, splashing three dagger off-the-dribble threes, countering off the threat of the shot with the explosive drive by splitting the defenders in a quick Horns set attacking the gap and driving through the paint for an open lay-in.

Okorie’s ability to operate a multitude of pick-and-rolls at a high level, stretching the floor on ball to open driving lanes to attack, draw fouls, or kick is one foundation of how he can be relied on likely quickly at the NBA level to create advantages for himself and teammates in the most popular action in the league.

Ebuka Okorie’s 2025-26 Stanford Cardinal Synergy Efficiency Stats

In every overall basketball situation, Synergy rates Ebuka Okorie as “very good” or “excellent”; Okorie rates especially high overall (1.09 PPP), half court (1.05 PPP), Sidelines Out Of Bounds Sets (1.24 PPP), After Time Out sets (1.2 PPP), against a Press (1.15 PPP). Okorie can give you buckets in practically any situation, however you want to get scored on, whether you guard him man-to-man (1.03 PPP) or with zone. (1.35 PPP). Okorie’s half-court play types are highly efficient, especially in his highest volume play of running pick-and-rolls (1.05 PPP, 90th percentile), along with his third-highest volume play of running ISOs (1.11 PPP, 87th percentile). He also scores a very good rate in transition (1.24 PPP) and on Spot Ups (1.07 PPP).

Ebuka’s offensive repertoire is vast: he can initiate offense with and without ball-screens, score off picks and off the dribble, and threaten the defense off the ball from deep with closeout-attack drives to counter. This all makes him a versatile scoring guard off the bat.

When including passes, Okorie’s volume of pick-and-rolls increases by twice the volume (415 poss) while dipping in overall efficiency, but still efficient overall offense at 0.97 PPP. Okorie is a trap-killer in pick-and-roll, averaging 1.38 PPP in such situations, making defenses pay huge in the 16 times they’ve tried this season, rating 92nd percentile; when the ‘defense commits’, however, that drops to 0.83 PPP. (229 poss).

Including passes on ISOs, Okorie’s efficiency stays equally as impressive at 1.11 PPP, with about thirty extra possessions; so, whether Okorie passed or shot out of ISO, the advantages he created in 1-on-1 led to an extremely efficient look for his team.

What stands out overall is Okorie’s range of good-to-great efficiency in such a variety of playtypes and situations. That much versatile scoring efficiency is one example of good feel decision-making, reading and reacting to defenses to make the best play for your team, and the individual advantage-creation and scoring ability to execute consistently.

Okorie’s Shooting Touch & Athleticism Indicators are all promising to translate to the next level:

50% FG% on 30 Runners (FLOATA)
35% 3P% on 101 Pull-Up 3PA
36% 3P% on 67 C&S 3PA
51% FG% on 221 Layups
100% FG% on 9 Dunks
84% FT% on 214 FTA

Measuring Two-Way Feel and understanding of how to play the game is not fully quantifable.

Two stats that show the results of Okorie’s decisions: 1) as a safe decision-making passer with a 102 AST/50 TO Assist-to-Turnover ratio, and 2) as a sound defender racking up 45 STL + 9 BLK / 38 PF Stocks-per-Foul ratio. Creating advantages and creating scoring opportunities that lead to good looks for yourself and your teammates, and doing so without turning the ball over, shows good decision-making process as a primary on-ball decision-making creator. Forcing turnovers without fouling via well-timed digs, jumping passing lanes, timing up help-side blocks, and deterring drives with active hands are examples of a high-feel defender.

In the highest-rated class in NCAA Freshman BPM history, Ebuka Okorie ranks 9th in BPM among freshmen. Change those barttorvik filters to the entire NCAA in 2026, and Okorie ranks 36th. Change them again to Only Freshman from Any NCAA Season back to 2008, and Okorie rates T-45th with Kon Knueppel, Derrick Rose, DeMarcus Cousins, Zhaire Smith, and Collin Murray-Boyles. For reference on the magnitude of this draft class, the average draft features ~2 players with a >10 BPM, via Jeremias Engelmann; the 2026 draft is on course to feature 6 players with BPMs over +12 BPM, and by my count, roughly 25+ potential draft prospects with over a +9.0 BPM; the depth of talent in this class is utterly insane.

Here is some statistical company for three marks Okorie reached:

As of March 11, 2026, 31 freshman since 2008 have scored at a 54.5% TS% rate, assisted 19.5% of their team’s passes when on the floor, and forced 1.95% of their team’s steals while on the floor, with an over 7.0 BPM rating, visualized below. Only top prospects and star offensive players rank higher than Okorie in overall BPM impact in this group: Cameron Boozer, Cooper Flagg, Kingston Flemings, James Harden, Lonzo Ball, Reed Sheppard, D’Angelo Russell, Trae Young, Ben Simmons. These minimums attempt to show all-around scoring efficiency and decision-making among high-impact two-way college freshmen since 2008, when Bartorvik’s available data begins* (*close 2PA, shots at the rim, are not recorded until 2010).

Ebuka Okorie’s Historical Stats via Barttorvik

To highlight Ebuka Okorie’s incredible advantage creation, efficient team scoring, and sound decision making, the chart below shows how Okorie is record-low in TOV% among high volume creators and has created as many shots at the rim for himself as any big name prospect besides Boozer since 2008.

How is a 6’2″ Guard not only getting past his defender, penetrating the paint, and getting to the rim, but also finishing this efficiently while doing so?

Ebuka Okorie’s Historical Stats via Barttorvik

Another interesting query highlights Okorie’s ability to get to the rim by limiting this list to filter for freshmen who have taken 200+ close shots at the rim, shrinking the group to five-star downhill prospects:

Cameron Boozer, Cooper Flagg, Trae Young, De’Aaron Fox, Ben Simmons…and Ebuka Okorie.

Not only do I see Okorie as a special finisher at the rim based on his crafty layup skills in person, but he’s also next-level elite at creating the advantages necessary to get to the rim. at a high rate as a small guard on insanely high usage, touches, and shot volume while maintaining scoring and shooting efficiency, and posting the lowest turnover percentage of any of the players on any of these lists.

When you combine his quick processing and quick movements with his total control of the ball, his body, and the situation, plus his scoring touch from every level, Okorie flashes real potential as a primary decision-making offensive engine scoring creator – a scoring point guard a team can put the ball in the hands of and rely on to create a good look for the team every time down the floor, because he can score and create efficiently out of nearly any situation and playtype.

Good things happen with the ball in Ebuka Okorie’s hands. Statistically, he has the best turnover rate for a high-volume scorer and passer of any freshman since 2010. Okorie is the only freshman since 2008 to post 20+% AST% with below 13% TOV%, let alone rate 3% better than the next closest assist rate at 2nd (Cam Boozer), via Barttorvik.

Among the 460 freshman since 2008 with 20% Assist and 2% Steal rates, Okorie’s 10.2% TOV% ranks 1st and his +9.5 BPM rank 12th all time. Expanding to every college player since 2008, Okorie ranks 7th in TOV% among the 382 who met these minimums of TS% ≥ 54.5; Assist % ≥ 19.5; Steal % ≥ 1.95; Box +/- ≥ 7.1. Okorie handling his insane on-ball usage and shot volume, maintaining scoring efficiency across the board, and ranking all-time great in the turnover ranks for high-volume creators is an incredible feat showing his primary decision-maker capabilities.

Excerpt from my 2024 Sunshine Classic Scouting Report on Swish Theory

Ebuka Okorie popped out with decision-making, passing chops, and tough shotmaking at the rim and on pull-up jumpers, with decisive feel and defensive instincts leading to routine winning plays.

Ebuka Okorie’s crafty finishing at the rim, decision making feel running the show, splashy pull-up 3pt range, anticipation jumping passing lanes for steals and timing up blocks for turnovers deserves to be highlighted.

Dante Allen, Ebuka Okorie, CJ Ingram stood out the most in the tournament statistically by their overall impact and defense, with the Montverde duo also rating highly in rebounding/rim-protecting measures; all three were the standout prospects in overall impact (C-RAM), each registering over 10+ C-RAM respectively.

Ebuka Okorie rated 2nd in overall impact (over 10+ C-RAM) and very highly on the defensive end, rating 4th of all players. (97 DSI).

Ebuka was just as impressive on the offensive end, rating 2nd as a scorer (88 PSP) and 2nd at passer (79 FGS) at the 2024 Sunshine Classic, via Cerebro Sports.

Okorie slotted in as the 12th best 3pt shooter (72 3PE)

Okorie (and Dante Allen) again stand out on this chart as offensive engines, rating among the best as scorers, playmakers, and 3pt shooters, showing they could be the most reliable scoring creators from the 2024 Sunshine Classic.

#2 Ebuka Okorie (Stanford)
6’2″ Guard 2025

Incredible decision-making feel
Crafty finisher around the rim
Real two-way impact forcing turnovers
Clean Pull-Up and C&S 3pt jumper rhythm shooter
Great vision executing half-court offense, finding open teammates
Willing passer giving up good shots for better shots
Defensive instincts timing up steals and blocks

19 PTS – 3 AST – 1 REB – 2 BLK – 8/11 FG (26 MIN)
vs. LuHi

Crafty finish up-and-under hanging in the air at the rim
Soft touch finger roll high off the glass
Good body control, deceleration
Tough contested finish at the rim with soft touch
Nice block timing
Crafty finishes all around the rim all game long
Up-and-under reverse
Beats buzzer through contact for tough finish at the rim with defender draped all over him and no foul called

15 PTS – 6 AST – 3 REB – 4 STL – 3/7 3P – 5/10 FG (29 MIN)
vs. Orangeville

Good anticipation on Steal
Smooth stroke pull-up triple
Patient decision making, good feel and decision to shoot of the handoff
Unselfish pass from good to shot to great shot in open corner shooter
Smooth C&S 3 off screen, playcall seems to be named “leg”
Nice decision dumpoff pass

2024 Interview with Ebuka Okorie

For one last peek in Okorie’s mindset as a player, person, and teammate, here’s the remainder of our interview:


RK – I really liked the patient decision-making, your ability to read the floor. How would you describe your mindset when you’re in the game?

Ebuka – ”I’m just playing to win and just help my team however I can to just get the win.”


RK – You’re off to Stanford. What led to that decision?

Ebuka – “It’s a really good school in terms of academics and obviously basketball, so I just felt like it was the best fit for me.”


RK – What kind of skills are you trying to develop and add to your game over the coming years?

Ebuka – “I’m just trying to develop all parts of my game. Getting stronger, quicker, just like all parts of my game, just still working hard.”

Q. How would you all describe yourselves as teammates off the floor?

Ebuka – “Yeah, I’d say like we’re just around each other all the time, and our chemistry just keeps going up every single time, every day.”

RK – One last question. Your teammate, Dwayne Aristode, wasn’t able to make this trip; he’s dealing with an injury. How would you describe him as a teammate and a person?

Ebuka – “Yeah, obviously he’s a great player. He’s also a great teammate, like he’ll pick us up like if we’re having a bad practice or something, he’s always here for us.”

What ultimately stands out most about Okorie’s game is not just his outlier super power ability to get to the rim or any spot he wants, its his complete game – his crafty handle, sound anticipation, defensive instincts, dangerously quick first step burst, masterful start-stop body control, efficient scoring versatility, clear playmaking vision, sublime shooting, smooth finishing touch, and earned confidence – combined with one other super power – his impressive decision making on the basketball court, putting all these pieces of the puzzle together.

A team-first decision-maker with the ability to get to any spot and make any shot at any time, with or without the help of a screen, who can beat you with speed and touch to stretch the floor in both directions at once, is one versatile offensive weapon.

A 6’2″ high-volume shot creator with record-high impact, record-high rim attempts, and record-low turnovers who creates advantage at wills and shots consistently for his team, Okorie’s overall scoring versatility, pick-and-roll mastery, mean pull-up jumper, and knack for attacking the rack makes him one of the most efficient shot creators of any draft prospect.

A truly masterful point guard who can force turnovers on defense and do it all on offense; not just dribble, pass, shoot as a base skill-set, but massive potential on the ball with his ability to penetrate the paint and create good looks for his team consistently with ease off his lightning-quick first step burst, total start stop body control, flashy handle ball control, mean pull-up jumper and cerebral feel for the game.

Ebuka Okorie is the 2026 NBA Draft Lottery Pick hiding in plain sight.

The post Ebuka Okorie: A Lottery Pick Hiding in Plain Sight appeared first on Swish Theory.

As I go through this intense process, I normally have one or two players who stand out to me. Not because I like or dislike them, but because I find them to be particularly testing for my process. This year, it is fair to say that Amari Allen from Alabama fits the bill.

Allen has some serious fans within the Draft-sphere. Per Jon Chepkevich who just released his annual ‘consensus board‘, Allen ranks 24th. That may not seem overly high, but there are some high placements in there. In the model of our very own Wafe, Allen comes in in 6th place. One of my favourite Twitter follows, JPR from The Center Hub, has him ranked 8th. Any player will have fans at well above consensus, but I believe it’s fair to call Allen polarising.

The high-end sell of Amari Allen is that he is an ambidextrous player who can pass, drive, and shoot, and processes well. While watching his film, I found myself sitting somewhere in the middle. I see a player with tools, but who needs to sharpen some of them to make an impact in the NBA. I wouldn’t call the value theoretical, as he is objectively a good player, but I ran into some issues on the film despite the statistical profile seeming well-rounded.

I will go much deeper throughout the piece, but I want to give a basic outline up front. I largely believe he has capabilities as a pass, drive, and shoot player, but the driving is underdeveloped right now. I also believe the defense is solid positionally, which explains why he has solid numbers for both blocks and steals, but I don’t see him as a major disruptor on that end, even if I believe his physical tools are quite enticing. Largely, the driving is where I hope to see development and why I ultimately want him to return.

Amari Allen’s Role

There’s a good argument to be made that Nate Oats is the best offensive mind in the entirety of basketball. Others may have more exotic schemes, but in terms of putting things into practice and getting the best out of his players, Oats is probably the best I’ve seen. It sometimes means we deem Bama players as having more of a ceiling than they show, largely because he puts them in such an optimised role.

Allen’s role is largely what I’d call a perimeter attacker. He isn’t the lead creator, and there aren’t necessarily pet sets for him, but his job is to drive off the catch, attack closeouts, and be a rim finisher. It’s a good use of his shooting ability and his above-average court mapping. Below is a good visual of his role from the excellent Hoop Explorer site.

As you can see, he’s attacking, kicking the ball out, and working in transition. Oats rarely asks him to take dribble jumpers and he almost never gets to showcase any kind of in-between game, because a Nate Oats offense drastically cuts down on those shots and disincentivises them.

Part of his role is also being a secondary Pick-And-Roll ball handler, which I deem to be an area for improvement. Per Synergy, he is in the 62nd percentile for frequency of all PNR plays (including passes), but in the 44th percentile for efficiency. This number drops to 15th percentile when the ‘defense commits’, which essentially just means when they play man to man defense and commit to guarding both the roller and the ball-handler, with traps and hedges being calculated separately.

So, Allen is being asked to drive quite often, with Oats asking him to do it from a lot of different scenarios that involve both with and without ball screens. This is good for a film student because it means we get to see the full picture, which isn’t a luxury with other players who can often play for coaches or in situations that suppress certain things we need to see. The question is, what does the film tell me?

Amari Allen’s Driving and Finishing

Let’s start with the raw driving before we get into the nitty-gritty of Pick-And-Roll play.

Allen’s driving is largely a bit of a rollercoaster. He’s strong and has flashed some incredibly impressive moves when he gets inside the arc. Where it can be adventurous is before we reach that point, as he can sometimes struggle to generate separation.

Just to give a note for the reader, I do not start clipping stuff until I have formed my overall take. I watch everything, form an opinion, then pick clips that back up my opinions. Watching film to anchor biases or to look for the truth you want is bad process.

Below is a play from the game against Auburn.

Allen pump-fakes to get Pettiford in the air, but struggles to gain any kind of separation while driving left, and ends up throwing up a pass that was never on. He doesn’t seem to be comfortable going to any kind of decel move, which is a problem as he doesn’t often separate at the top of the drive.

Generally speaking, he struggled against physicality at the point of attack, but was better against it around the basket. Here’s another example from a game against Clemson.

Allen drives from the slot, first trying to go left but going right after getting nowhere. He seems to generally prefer going to the right on film. He gets decent territory inside the paint, but never really compromises the defender at any point, and after trying a move, he ends up throwing up a wild shot that gets blocked.

Allen is strong, which means he can sometimes generate position as a driver. It’s just quite often not the most convincing endeavour. The play below against Kentucky illustrates this further.

Allen attempts to drive, but generates little separation, which means Jaland Lowe can just poke the ball out from behind him because he’s able to both stop the drive and not be overly worried about Allen going to a second move in the half-court.

A notable part of Amari Allen’s profile compared to others I’ve watched is that he attempts to be ambidextrous. This is likely good for his long-term development, even if it nukes his efficiency in the short-term. The reason I’m bringing this up is that, while a lot of the struggles come from driving left, I feel they are notable when going right, and I would not say he’s a standstill separator or anything like that.

Here’s an example of another problem when driving left that relates to a few things.

Allen gets a good (possibly illegal) flat ball screen and powers past his man, but, even though there is almost no rim protection, takes his attempt very wide to the left and ends up completely missing. While he struggles separating at the top of the drive, it feels as if the handle when he gets into these areas can be quite inconsistent, though it does show up more when he drives to the left.

On the topic of his ambidextrous nature, I hand-tracked all of his layups on the year. He is shooting 61 percent on right-handed layups (33/54), and 45 percent on left-handed layups (11/24). There are occasions when he’s able to get the ball to his right-hand even while driving to the left, but if it’s a left-handed attempt, he is much less comfortable on the whole.

Where it gets more murky is that a lot of his best finishes are in transition. Per CBB Analytics, Allen is shooting just 44 percent on two-pointers in the Half-Court which is 23rd percentile across D1 Basketball.

Though he isn’t much of a separator with his dribble moves or with a first step, I do believe it’s notable and important that he’s able to be strong against other wings. He can, however, struggle more against big guys such as on this rep against Thomas Haugh.

Where the driving becomes interesting is that there are some seriously impressive flashes. Flashes are a buzzword that can definitely rile some draft scouts, particularly on the spreadsheet side of Twitter. I largely agree with these critiques, however, I’m not going to completely ignore some very good stuff with his drives due to his age and his room for improvement. Below is my favourite drive from his tape so far.

Allen sizes up his cross-match in transition and completely shreds him. He gets low (which is something I look for when I’m analysing handle), then shows agility to get back into the lane. Compare that to the lefty layup against Mississippi State, and it’s night and day.

This one against Clemson is also impressive. He gets the switch on a PNR, and his screener largely doesn’t give him much to work with. He then power steps and crosses back into a Eurostep and finishes off the glass. If he gets into the paint with some kind of force behind him, he does have some very capable east-west moves. The question I keep circling back to is how often will he reach these areas.

This one against Arkansas is also great. He really seems to get a lot of force when driving into the paint, so it gives him more power whenever he goes to his East-West moves.

Let’s, however, compare what this looks like when going to his left.

Bama throws him the ball at the elbow on the out-of-bounds play, essentially giving him an Isolation. He sends his man darting backwards, but he doesn’t quite have the same comfort when he is on his left. One factor I may want to consider here is that Nate Oats doesn’t like his players taking any kind of mid-range shot. When watching this play, I wonder if Allen would have felt more comfortable with a turnaround jumper after sending Tyler Nickel flying. Instead, we get a tough left-handed miss.

The driving is largely an area where Allen needs work, but there are some tools there that make me think he may put it together. It’s probably the main reason I hope he returns. He’s strong, I’d just like to see more efficiency on the drives and possibly some way of separating that isn’t just pure strength.

On the topic of driving, it makes sense to dive into his finishing. I noted earlier that his desire to be ambidextrous slightly nerfs his overall percentages. But it would be fair to say that his finishing profile is quite average overall. It’s above average at a push, but the main reason for it is that he doesn’t possess the handle to make things easier on himself at the rim. As mentioned previously, he’s shooting 45 percent on 2s in the Half-Court.

One thing I do appreciate about Allen is that he gets good hangtime on his layup attempts. There appears to be more difficulty with self-created ones, but I feel this is a notable factor in projecting future improvement. Here’s a good play below.

Alabama runs the Noah LaRoche ‘Wheel’ Pattern in early offense. Allen sinks to the corner, attacks the closeout, and finishes strong through the rim protector. In these tilted or short-manned floor situations, I feel the finishing shows up a little better. While we should expect this, I still believe it to be notable. Below is another example.

This one comes in early offense, but Allen drives past his man with a crossover and gets good hang time before finishing off the glass. He’s athletic and capable of finishing through contact. Something I will note is that I’m often not a fan of indexing on ‘flashes’. An experienced scout once told me, to my shock, that ‘Jonathan Isaac Movement Shooting Flashes exist’. However, there are enough of these from Allen for me not to be completely out on him as a finisher, though the first level of driving needs work. Here are a few more.

They run Elbow Chicago, and he dives to the rim after screening and finishes through contact. Again, a play did the early legwork for him, but he still managed to finish the play for Alabama.

Here is a play against one of the very best.

After some early offense broke down, Bama swung the ball back to Allen at the top of the key. He gets a clear lane, and, even though that’s a relevant factor, I still find it impressive that he goes right through Ruben Chinyelu for the easy finish.

Something I will also add to this is that Amari Allen was seriously drawing fouls at the start of the year, which makes sense when you consider his hang time and the physicality he sometimes shows. This has declined in recent games. Amari Allen missed the final 2 games of February with an injury. Since then, per BartTorvik, his FTR is down to 29.1, which is a drastic drop off from the 45.2 he was rocking previously. You could argue that the off-ball strength-based finishing and foul drawing are the best part of his scoring profile, so this is something to monitor. He’s only attempted one free throw in his last three games.

Something I do see as a pattern is that his better flashes seem to come when Bama are spaced out in five-out. Being in five-out does not automatically equate to spacing, but it does appear he is more comfortable as a driver and finisher when things are already tilted for him.

Allen isn’t a guy I project to be a high-volume driver as of now; there isn’t enough evidence of separation on the film. I, however, see enough to believe he could be a decent play finisher on offense. It’s just a question of how good the numbers get.

The reason I bring this up is that I believe Amari Allen’s best half-court reps came as a PNR Roll man. It wasn’t something they leaned into all that often, but when they do, it is very effective and showcases some of his talents. Firstly, he just shows good feel for when to dive or roll, which matters. Not all screeners are equal no matter their dimensions.

Here’s a simple look at it. Bama goes to a guard screening action, and Allen makes the simple read to the corner.

They went to it in a game against Texas, as well.

They run ‘Ram’ action, and Allen hangs in the air before making the dump off pass to the big man for an easy finish.

While this action often led to Allen getting potential assists, there were times when he was strong finishing through contact on these play-types, too, such as below.

Bama runs ‘Ram Exit’ with a smallball lineup. Allen gets the ball on the roll, gets met with size, but steps through him and scores the layup.

Allen has also hit threes out of these play types too, showing good feel for when to move, and he has decent shooting numbers and good shooting mechanics on the whole.

Ultimately, where I find myself gravitating towards with Amari Allen is envisioning him as a diverse play finisher. The NBA is changing a lot. The days of standstill high PNR are over. Will Hardy and Quin Snyder popularised ‘5 slot’, which involves putting your center on the wing, something Duke has now made their core half-court offense. What this effectively means is that bigs are doing perimeter stuff, and there is more room for wings and even guards to be play finishers.

Teams would not specifically run plays for Allen unless he was picked very high, but I feel that a team who has guard or wing screens as part of their Half-Court offense, such as Charlotte, Boston, or Indiana, might benefit from such a player. I try and see a path for any player I scout, and I feel this is the best possible path I currently see for him. If he returns, this may change. The idea of Allen joining a guard-screening heavy team and working inside off-the-ball is the best path I see on offense as of now. Effectively, for a team running a modern 5-out offense, can he be a shooter and screener who finishes inside?

Where that sell gets more complex is that his current numbers, while not bad, are not truly elite. There are logical reasons to talk yourself into them improving, but to what extent is the great question you must answer if you’re going to buy into my idea of him being a play finisher.

Amari Allen’s Processing

My biggest hesitancy with regards to projecting Allen into a larger offensive role is that his processing on offense is quite inconsistent. I take Synergy percentiles with a pinch of salt largely because they can be mistracked and only include actions where the player ended up shooting or turning the ball over, when there are realistically more than those outcomes.

However, one that really stood out to me was that Amari Allen is in the 14th percentile as a PNR Ball Handler when the ‘defense commits’. From watching every one of these clips, I concluded that it means when the handler and the roller are both accounted for by one defender. This particular playlist does include plays where he passes, so it’s not entirely on him, and Alabama doesn’t really have the most athletic center room.

He can often make very scripted reads that lead to turnovers.

Alabama runs Ram 77 Empty Exit, a nasty play that is almost guaranteed to lead to a good shot.

Allen doesn’t show much comfort despite basically having every option available to him. He has the opportunity to shoot himself, hit the roll man, or even make a quick dump-off pass to the three-point shooter. He instead stares down the roll man, and Krivas gets the steal. This admittedly is a very good Arizona team, but it was incredibly obvious where Allen wanted to go with the ball.

Here’s a similar example below against Mississippi State.

They run a PNR with a wide ball screen on the weak side, admittedly one that isn’t perfectly set, but it’s enough to occupy everyone. Allen gets into the lane but misses his window to Taylor Bol Bowen, which allows the defense time to recover. He also goes for a jump pass, but there wasn’t anything on the weak side to sell, so it just telegraphed where he wanted to go.

Let’s watch below:

For anyone who read my Javon Small piece last year, you’ll note that I quoted Jake Rosen, who said that a good way to spot a faulty processor is to watch how often they stare down the first reads as opposed to reacting to what they’re seeing. Here’s a good example. Bama runs a simple high PNR. The corner man tags aggressively, which gives Allen a clear window to skip to the corner. Instead, he missed it, and ended up picking up his dribble and turning it over. Sometimes you only get one window. Elite creators can open more windows, but most can’t.

Allen’s handle isn’t outright bad, but there are times it can slow his processing a little. Think of it like sometimes you think of things before your body can actually execute them. This play is a good example.

Allen misses Bol Bowen on the roll, then misses him again when he tries to go left. He ends up getting stuck in no man’s land and tries to hit a backdoor cut to a player who is out of bounds. Sure, the off-ball Bama players don’t cover themselves in glory, but he also can dribble himself into these spots sometimes where it becomes a lot more difficult. If you miss windows, it’s sometimes hard to get them re-opened.

Sometimes the problems are caused by the fact that because Allen doesn’t consistently separate at the top of his drives, the reads are murkier, as defenders will play closer to their off-ball assignments if they know their teammate has it. But he does also just miss reads and sometimes struggles to move through possessions in PNR. I do not project him to be much of a PNR threat as of now, he’s better in more ancillary play-types.

I am not meaning to hold Amari Allen to the standard of a primary. I more just want to challenge the notion of someone being a ‘pass, drive and shoot’ player as I feel it’s an overused description of players. He’s capable of driving, I just don’t quite know how good the processing is, and it’s notably at its worst in PNR situations. This largely matters if someone is going to be a drive-heavy player, which many project Allen as.

Defense

To say Alabama has struggled defensively would be quite the understatement. They lack rim deterrence and have taken some big scorelines this season. Despite this, Amari Allen has been relatively solid. He’s above 2 percent for block and steal rates, which is a good summary about how I feel about him as a defender currently. I don’t believe he’s elite, but he is very positionally solid. I would feel comfortable saying I’ve barely seen him get beaten off-ball. On a team with the defensive lows Alabama can have, this is notable.

Allen is positionally sound, and his best plays have come as a nail helper or as a low-man, such as below:

Clemson runs Delay Chicago: a staple yet very effective play. Allen keeps his eye on the driving guard despite his man clearing for 3, and when he crosses over, Allen instantly shifts to come up with an incredible block. He gets good verticality generally and doesn’t seem to have much trouble with his timing. Below is possibly my favourite defensive play of the cycle.

Amari Allen is initially the low man and flies out to contest Meleek Thomas. Thomas sidesteps him, but in basically the same motion, Allen jumps from a standstill and blocks Thomas’ shot with his right hand. The verticality is genuinely very impressive. He strikes me as the type of defender who would really thrive in a Tom Thibodeau-style defensive scheme where he’s being aggressive at the nail and then jumping out to shooters on the weak side.

As a scheme-driven defender, I think he can be a really good player for an NBA team. He’s strong and genuinely did well in quite a tough defensive context. The steal and block numbers being decent rather than elite kind of match up to what I’ve watched on film. He’s positionally sound and doesn’t chase stuff, and gets his actions by doing his job.

The only real issue I found with him defensively is that he’s a little bit worse at the point of action than you’d want. He can be caught off guard by screens quite often; it’s a definite pattern.

Auburn runs an angled Spain PNR to an empty side. It’s a difficult play to stop, but just focus on Allen here. He’s completely blindsided by the screen because he’s not playing with his head on a swivel. The reason I can be lenient on defense is that I do believe it’s a team sport, and that’s often misunderstood in individual analysis. But Allen did have plenty of plays like this where he was so hyper-focused on his man that a screen completely blindsided him. Most modern NBA Defenses don’t want to give up any kind of middle penetration, so it’s an issue to iron out, even if it is really the only issue I have with his defense.

Here’s a similar example against Auburn.

Auburn runs a pick-and-roll from the slot. Allen is guarding Pettiford, which isn’t an easy task for anyone, but particularly wings, as Pettiford is so crafty at the top of his drives. Allen again doesn’t have much awareness of the fact that he is about to be screened, which gives Pettiford an easy route downhill. Once you have a 4-on-3 with someone of Pettiford’s craft on the ball, it is largely over. Bama does well to delay him, but eventually the player guarded by the nail helper scores an easy one at the rim.

Overall, don’t take this as nitpicking. I just want to create a full picture. Allen is a good defender. I don’t know if I see an All-NBA type ceiling, but I’d expect him to be comfortably above average. He’s strong, has good instincts, and has good timing, which meshes well with his ability to get vertical very quickly. The point-of-action defense is a concern I have, but it might not be something that’s tested all that often. As a helper, he will be NBA-level from day one.

Concluding Thoughts

Overall, Amari Allen is probably the most interesting player I’ve watched so far. When you browse Draft Twitter or even places like Reddit and Discord, you’ll find a lot of takes and quick-fire slogans about players. I mentioned some, such as ‘pass drive and shoot wing’ and ‘ambidextrous slasher’, which I saw. There is some truth in these, but I always aspire to go deeper with my analysis where I can.

My ultimate take is that I have concerns about what the offensive role looks like at the next level, from an upside perspective. As of now, the top of his drives are quite underdeveloped, even if there are some nice east-west flashes. I will, however, note that NBA offense isn’t 4 people taking turns to drive from standstill positions. But it’s fair to question the offensive role when the shooting and rim numbers are only ‘good,’ and he’s yet to show a tonne in the half-court outside of ‘flashes’. Being a top-end creator, even as a third option, does require some form of standout skill, and I don’t know what Allen’s is yet.

He will likely be good at the ancillary stuff as he can rebound, hit spot-up threes, and has good feel as a screener. Guard screening is definitely becoming more viable and important with the rise of 5-slot and inverted offenses in the modern NBA, but it’s also fair to say the floor for being good offensively seems to get higher every year.

What I keep coming back to long-term is that his profile is well-rounded, and that seems to matter. I’m nowhere near the Bart Querier of someone such as Avi or Finn, but I will post this one that I checked was ethical.

He can do a lot of things quite well. It’s not unreasonable to believe that he may sharpen one of these tools. Nate Oats believes he has another level to show as an offensive player. But as of now I don’t quite know what the standout trait or standout skill is. If he declares, the day-one uses to a team would be his defense and his rebounding with a bit of spot-up shooting mixed in. I just worry about him as a ‘pre-draft’ candidate, given the driving has quite a way to go.

When scouting, I often come up with a few hypotheticals for the player I’m scouting, ones I deem to be important to the overall process. Revisiting my earlier point about him possibly being a play finisher, this is the hypothetical I keep coming back to.

• Is any of the shooting profile good enough to really be a play finisher at the next level?

The shooting is solid, the layup percentage is alright, and he may have an in-between game when not playing for Nate Oats. But none are truly elite right now. I’d say the banker for serious improvement comes down to his driving game developing quite significantly, which is why I’m hoping he returns to Alabama. I just don’t know how much hope I’d put on this. I also think it’s fair to say that even if the first steps become more crisp, the handle might limit him, as he does need to pick up his dribble quite often. He is powerful, but the 2-point scoring issues go all the way back to his AAU Days. I’m likely of the opinion that the efficiency isn’t there right now for me to draft him at consensus if he declares this year.

Overall, I’d say Allen is a high-floor player who, if he declares, I’d rank somewhere between 22 and 28. I don’t have a board yet, but I think the defense could be quite impactful, and he does have room to grow. But the thing I keep coming back to is, where do you get with the offense. I can’t be out on him as the metrics are good, and his good games are also impressive. If he returns, he’s someone I’m watching for next season.

The post Understanding Amari Allen appeared first on Swish Theory.

*takes a deep breath*

Hundreds, if not thousands, of data points factor into every prospect evaluation, many of which we don’t consciously consider. These data points converge into a cohesive story that informs a prospect’s placement on our boards. Scouting, in a nutshell, is the practice of surmising the story that a prospect’s film, stats, measurements, surrounding context, etc., are telling you.

If that sounds daunting, that’s because it is. That’s why simplifying evaluations, when appropriate, is critical for my process. One does so using heuristics — rules of thumb that simplify complex decisions or judgments. Put differently, heuristics use a few data points about a prospect to form a reasonably complete evaluation.

Now, there are pitfalls aplenty when relying too heavily on heuristics. Read Thinking Fast and Slow by Daniel Kahneman if you want proof. But, there’s a reason we evolved heuristics as humans: they can be helpful! It’s no different for scouting NBA Draft prospects. I’ll show you what I mean.

Consider this former college basketball player.

Would you draft him based on the presented information? I wouldn’t, and I’m guessing you wouldn’t either. If I asked why you came to that conclusion, you’d cite the poor production and efficiency over a large sample of games. Without reviewing any film or advanced numbers, I think we’d all feel comfortable with that decision. Guess what, we’d be correct. Those statistics belong to none other than LaVar Ball when he played college basketball in the 1980s.

Without heuristics, you’d have to dive deep into Lavar’s film before definitively concluding that the NBA was not in his future. You would have to conduct similar thorough assessments for every draft-eligible player regardless of their minutes played, production, or anything else. Obviously, no one has ever operated in this way (this is why I’m always skeptical of self-proclaimed eye-test-only scouts). We can comfortably eliminate most players from draft consideration, like we just did with Ball without thinking twice, thanks to heuristics.

The Lavar Ball example demonstrates at a basic level how heuristics can apply in scouting. In this case, bad career production = bad prospect. Done. Case closed. However, we have to be more discerning when discussing prospects with actual NBA chances. That said, some evaluations are much easier than others…bringing us to Yaxel Lendeborg.

Lendeborg is a forward for Michigan by way of UAB and JUCO before that. He attended the draft combine last year, where he actually generated some first-round hype before deciding to return to school. At the combine, he measured at 6’8 1/4” without shoes and 234 pounds, with a 7’4 wingspan and 9’0 standing reach.

With that, time for pro-Lendeborg heuristic number one, courtesy of Chuck from Chucking Darts:

Wings with 7’2+ wingspans don’t grow on trees (I’m still shocked by how small this list is), and the hit rate is spectacular. So, great physical tools: check!

Now, pro-Lendeborg heuristic number two: incredible all-around production.

Analytics models loved Lendeborg last year at UAB to the point where he cracked the top 20 on some people’s boards. Going into this season, scouts rightfully asked how Lendeborg’s numbers would look at the Big Ten level. Well…pretty amazing, as it turns out.

There are no weaknesses here. Lendeborg’s efficiency from every spot on the floor is comically high. He takes care of the ball, generates steals and blocks, and his assist-to-turnover ratio keeps improving year-to-year. If his current ~20 BPM holds, this would be one of the greatest statistical NCAA seasons we’ve ever seen.

Now, pro-Lendeborg heuristic number three: his archetype. A dribble, pass, shoot, defend wing.

Had Lendeborg stayed in the 2025 Draft, downsizing to play the three in the NBA would have been more of a projection, as he was a 4/5 hybrid at UAB. Thankfully, Michigan deploys Lendeborg at the three, with Aday Mara and Morez Johnson Jr. acting as the two bigs in Dusty May’s system. As such, we’re getting a look at Lendeborg in his likely role at the next level, and it looks great.

Lendeborg has served as the perfect wing connector for Michigan on both ends of the floor. Offensively, the ball never sticks to him. Lendeborg’s court mapping is outstanding. He knows everyone’s location on the floor, and he uses that information to make quick decisions. But, what makes Lendeborg so good is that his skill level allows him to properly act on the quick decisions he makes. He’s a triple threat with the ball in his hands. He can use his handle to generate optimal shots for himself or improve passing angles. When he passes the ball, he can find open teammates through tight windows and give them easy looks. If no driving lanes or teammates are open, Lendeborg can rise up and shoot over defenders, even with a hand in his face. Put simply, good luck preventing Lendeborg from optimizing an offensive possession for his team.

Defensively, it’s the same story. Lendeborg can get down in a stance and harass multiple positions on the ball. He’s big enough to be a problem for interior players, too. Additionally, his length proves super functional on rotations, help-side blocks, and recoveries contesting shots at the rim. His verticality without fouling has become a real asset defensively, and I expect it to translate to the NBA. I can’t recall a time when Lendeborg has made a faulty gamble defensively or been out of position. He’s simply an incredible basketball player.

Unfortunately, there is one hair in the soup for Lendeborg: his birth certificate. With a September 2002 birthday, Lendeborg will be a 24-year-old rookie next year. Important heuristic number four: old prospect = less room for development. I don’t want to entirely eliminate the possibility of star upside for Lendeborg, considering his development curve and complete skillset. But, history says we shouldn’t count on it.

Let’s succinctly combine the four heuristics. Yaxel Lendeborg:

• Has an ideal physical profile (6’8, 230 lbs, 7’4 wingspan)
• Has an otherworldly statistical profile
• Has a complete skill set: dribble, pass, shoot, can make the right decisions quickly, and defend
• Will be old for a rookie at 24, likely capping his development trajectory

From these four premises, I’m concluding the following:

• Yaxel Lendeborg is a probable high-end playoff starter in the NBA. But, his age likely limits further upside scenarios.

Using a few heuristics, we have told a reasonably complete story about Yaxel Lendeborg. With so much time until the draft and more information yet to be revealed, I rarely draw formal conclusions about prospects in December. Cases like Lendeborg are the rare exception.

I view Lendeborg as a lottery-level prospect. I feel confident in my evaluation of the player, but the work with Lendeborg is far from over. I still have to contextualize Lendeborg within this draft class. How many players will I rank ahead of Lendeborg? It’s too early to say. But a reasonably complete evaluation of Lendeborg, aided by heuristics, will now serve as scaffolding as the rest of my board takes shape.

The post Yaxel Lendeborg and the Importance of Heuristics appeared first on Swish Theory.

The consensus preseason top three of Darryn Peterson, Cam Boozer, and AJ Dybantsa seemed untouchable, and I broke that mold. The upside case for Wilson is obvious. He’s one of the better defensive prospects I’ve ever seen, with offensive upside to boot. I may still write an article making that case in more detail.

But, it turns out I’m not the only one who feels this strongly about Wilson:

Nathan, if you’re reading this, thanks for stealing my thunder…

In all seriousness, the Caleb Wilson train has left the station, and I don’t have as much to add as I thought I did. The No Ceilings crew did a great job making the Caleb Wilson case here. As a result, the masses have caught on, and Wilson is knocking on the door of a lot people’s top three.

Now, that leaves an obvious and intriguing question at hand. If Caleb Wilson enters the top three, who out of Boozer, Peterson, and Dybantsa do you take out? I have my answer on that, which I’ll save for another time. But, I’ve been shocked to find that many Twitter folks who are high on Wilson feel that way at the expense of…

Cam Boozer???

I can’t believe some of the takes I’m seeing. So, in the rest of this article, I’m going to try recalibrating the conversation around Cam Boozer.

I’ll start here: Cam Boozer has been the best player in college basketball this year.

Anyone who’s watched Boozer’s start to the season would tell you that there have been some hiccups here and there. He couldn’t buy a shot in his first half of college basketball, and his rim finishing has taken a noticeable hit against Duke’s tougher competition. There’s been a small adjustment for Boozer physically after dominating high school and AAU ball sweat-free — totally fair considering he’s 18 years old.

And yet, he’s been the best player in college basketball.

Let’s start with some numbers. Box Plus-Minus agrees with my assessment of Boozer’s play.

And in Evan Miyakawa’s model, Boozer is practically lapping the field:

Now, Sports Reference:

It’s highly unlikely these stats hold, but if they did, we’d be looking at the greatest NCAA prospect of the 21st century. I mean, look at those numbers! 42 points, 20 rebounds, and 8 assists per 100, strong free throw rate, excellent shooting indicators, 4.0 AST:TO ratio, and sublime steal and block rates. Oh, and by the way, all from a 6’10, 250-pound player who will turn 19 a week before the draft.

You don’t have to watch a second of film on Boozer to contextualize the caliber of prospect he is. With a BPM hovering around 20 through seven games, I think it’s safe to say that Boozer will finish the year with a BPM > 12. Here’s the list of freshmen on Bart Torvik’s database to accomplish this feat:

Assuming Boozer joins this list, that’s incredible company to keep. All-in-one metrics are far from perfect, but I tend to believe them when they point me to a high-level prospect like this.

When you turn on the film, the eye test backs the incredible impact metrics. I already covered Boozer’s exceptional feel for the game over the summer. I’ll link that article here. Boozer is a possession optimization machine. His court-mapping and split-second decision-making allow him to effortlessly pick apart defenses at every turn.

Boozer’s brain is second to none in this class, but Boozer separates himself from other high-feel prospects with his functional strength and scoring ability. Whenever Boozer decides that asserting his will as a scorer is the way to optimize a possession, he can get to his spots at will. Here are two examples from the Texas game.

Boozer skeptics point to athletic limitations as a cause for concern. I honestly don’t get it. Boozer is among the best functional athletes in the entire draft class. He’s currently sitting at 42.4 PTS per 100 on 65% true shooting largely as a result of strength-based scoring.

Put simply, I care about substance over style. Those looking for raw athleticism in this draft class should look at Michigan State’s Coen Carr. Carr’s vertical leap and power combination at 6’6, 220 is difficult to comprehend. Yet, he only boasts a 56.5 eFG% compared to Cam Boozer’s 60.4%. I’ll leave it to you to decide whose physicality is more compelling.

My point here: when evaluating a prospect’s physical ability, evaluate functional athleticism. Did Nikola Jokic need run/jump athleticism to hit high-end outcomes? How about Luka Doncic? Karl-Anthony Towns? Alperen Sengun? All these guys are athletic in their own way, but more importantly, they just get stuff done on the basketball court. Believe it when a prospect tells you they can produce at a high level and check your aesthetic biases at the door. As Brad Pitt (portraying Billy Beane) says in the film Moneyball, “He gets on base a lot. Do I care if it’s a walk or a hit?”

To close, I want to reference a tweet from my Swish Theory colleague Avinash:

Avi has lead the charge in emphasizing prospects for whom high-level cognition and physicality converge. You could argue that the meta in the NBA right now is acquiring players at all five positions who hit competency thresholds in both categories. Avi’s query has a spectacular hit rate for finding such players.

Cam Boozer comfortably hits these thresholds right now. So, by the way, does Caleb Wilson. Both are incredible prospects littered with green flags. Put Wilson in your top three, by all means. He’s there for me! But, doing so at Boozer’s expense would be a dire mistake.

No one shown in Avi’s query also had Boozer’s scoring and rebounding ability as a prospect. This is a combination of physicality, smarts, production, and youth rarely seen at the college level, if ever. I’ll say it again, he’s the best player in college basketball at 18 years old. We’re talking about a slam-dunk, can’t miss, mega-star prospect that should be top two on everyone’s board.

He’s number one on mine.

The post I Can’t Believe I Need to Say This: Cameron Boozer is Insanely Good appeared first on Swish Theory.

One mold that has always fascinated me is big players with exceptional “feel for the game.” There is something intrinsically valuable about combining a point guard’s cognition with a forward’s physical profile.

Whether it was Bobby Jones in the 1980s, Robert Horry in the 1990s, or Boris Diaw in the 2000s, this type of player has reliably contributed to winning basketball. With cognitive load relative to position on the rise, we’re seeing more and more players of this mold enter the league. The next one entering the league may just be hiding in plain sight in the 2026 draft class: 6’10” Iowa forward Álvaro Folgueiras.

The most compelling argument I can make for Alvaro Folgueiras as a bona fide NBA-level prospect is via this query. We are looking for tall underclassmen ( 6`8 and above) who displayed an outlier level of feel (quantified via AST%, STL% and partly OREB%) alongside a baseline of (vertical) athleticism (quantified via BLK% and partly OREB%) 

Alvaro stands among five players who are currently returning top-8 value in their respective draft classes, including the No. 1 and No. 3 prospects on last year’s Swish Theory board, as well as Ethan Happ, who led the BBL in PER in 2022 and the ACB in 2024, and is likely a positive NBA contributor hiding in plain sight. What makes Folgueiras so fascinating within this group is that his anthropometrics align with the non-shooting “big wing” segment of the query, while his shooting indicators match those of the smaller players on the list.

This combination creates a strong case for Folgueiras as a lottery prospect in the upcoming draft: He shares statistical indicators with the highest cognition wings the league has seen in the last few years, while being bigger than the prospects who shot the ball as well as him and having the best shooting indicators amongst all the players with comparable measurements.

Let’s explore, in the following segments, to what degree this heuristic actually holds up in reality and whether Folgueiras could truly be a top-level NBA prospect in the 2026 draft.

Offense:

Alvaro is one of the most “Haliburtonified” prospects I’ve seen in recent memory (shoutout to Mike Gribanov for the term). His decision-making is exceptionally quick, whether he’s initiating transition, connecting the offense from the perimeter, or finding cutters as a hub. He can make virtually every read in the book and thread interior passes through tight windows.

What especially stands out is his spatial awareness, as he almost never over- or underthrows passes. Posting a 21.9 AST% and a 1.4 assist-to-turnover ratio at his size is incredibly impressive, even after adjusting for his level of competition.

Folgueiras could also end up one of the better “big” shooters we’ve seen in recent years. He posted a 50 3PAR for Spain across his FIBA career, and he’s maintained a 40 3PAR and 76.5 FT% in college despite playing for one of the lowest-volume shooting teams in the country.

His willingness to shoot over contests and off of different platforms is pretty special for a long, 6`10 player.

So far, Folgueiras sounds like an ideal modern forward as someone who connects offense from the perimeter and provides reliable spacing.

So, what’s the holdup?

Alvaro’s scoring process and interior scoring profile aren’t consistent with those of typical NBA wings. To illustrate this point, let’s circle back to the base query of this article.

Within this group of players, Alvaro ranks last in 2pt ASTD%, second to last in rim: non-rim ratio and dunk rate, and third to last in pull-up jumper frequency. Being heavily rim-reliant while not finishing those attempts with dunks is already a major hurdle at the next level, where opposing frontcourts get longer and more athletic. When you combine that with a highly assisted shot diet and a negligible volume of pull-up jumpers, it raises serious concerns about whether Alvaro can realistically be utilized as a wing, an essential part of his projection, given that his underwhelming verticality, sub-70% rim FG%, and modest 5 BLK% are likely to prevent him from earning meaningful minutes at the 5.

His pull-up frequency is particularly concerning when compared to the true “wings” on this list. His edge in terms of touch becomes far less meaningful if he cannot successfully leverage it into counters in the middle of the floor.

There are two potential counterarguments to this  First, Folgueiras may have ended up with a big-adjacent scoring profile simply because he was forced into that role at RMU. As the tallest player on the roster, he frequently received PnR roll-man and post-up reps that he likely wouldn’t have been given on a different team, which may have skewed his shot diet. However, this explanation loses weight when we compare these indicators to his freshman season and his FIBA sample, where similar patterns persist.

Something even more important to consider in this context is Folgueiras’s drive frequency. He drove on roughly 15% of his possessions, a strong mark for his role and an encouraging indicator of his potential as a closeout attacker. While his lack of bend and high-end handle (which contributes to a staggering 23.9 TO%) and his discomfort with midrange counters are still very apparent on film, I’m encouraged by both the frequency and the efficiency of these drives. He posted a 64 TS% on them, which is a legitimately strong number.

Defense

Alvaro offers a solid baseline as an NBA defender, with some potential upside as a genuine game-changer. He posted 20+ DREB% across multiple samples, signaling strong positional rebounding. When contextualized with his excellent anthropometrics and impressive stock rates, this forms a solid foundation for retaining defensive value at the next level.

However, he is somewhat vulnerable against quicker players on the perimeter and occasionally struggles with proper foot alignment. Folgueiras’s lack of horizontal athleticism, particularly his limited ground coverage, shows up on tape. Combined with his issues in vertical contests, this makes it difficult to project him as a reliable weakside rim protector.

Even so, Folgueiras compensates with sharp positioning and strong overall cognition, routinely disrupting actions and getting his hands on the ball.

Folgueiras has consistently posted strong steal rates throughout his career, though his BLK% has fluctuated. This will be something worth monitoring at Iowa, especially since he will take on fewer center duties there (similar to his role with Spain in last year’s U20 EuroBasket, where he recorded just a 1.8 STL% and 2.4 BLK% while carrying an increased offensive load!). 

I remain confident that Alvaro can return positive defensive value in the future. He should be able to meaningfully influence opponent turnover percentage and limit opposing offensive rebounds as he develops. The key question is whether his cognition and disruptive hands can compensate for potential issues defending in space. In my view, the answer is yes.

One best-case scenario is Alvaro replicating Kyle Anderson’s defensive impact—trading some of Anderson’s elite cognition (career 3.2 STL% for prospect Anderson vs. 2.4% for Folguerias is noticeable) for a higher SR. 

Conclusion

I believe Folgueiras’s eventual placement on my final draft board will come down to two factors: What will his role and production look like at Iowa? And will he measure as well as he is rumored to?

Coach McCollum built a slow, pick-and-roll–heavy offense around point-guard maestro Bennett Stirtz at Drake, and he has carried that system over to Iowa. So far, Iowa ranks in the 93rd percentile in PnR frequency, 100th percentile in cut frequency, and 12th in team assist rate—figures that closely mirror the stylistic profile of his Drake team. In a context that centralizes advantage creation to this degree while boosting assisted-two volume through cuts and PnR roll-man possessions, it is highly unlikely that we will see a meaningful shift in Folguerias’s overall scoring profile.

McCollum retained his two highest-frequency rollers, meaning Alvaro will likely replace some of his old post-up and rollman possessions with spot-ups. It will be important for Folguerias to continue showing confidence as a shooter in these situations, while also maintaining a reasonable drive frequency to help offset his otherwise shaky offensive projection. So far, he has done exactly that—scoring 1.7 PPP on spot-ups and opening the season with a 16:0 AST/TOV ratio through his first five games. Another encouraging sign: Folgueiras has recorded 5 dunks on 12 total rim attempts, compared to just 12 on 167 as a sophomore.

The more pressing question, however, is how well he will measure. If he comes in closer to 6’9″ in shoes with a wingspan under 7’3″, I will struggle to view him as a lottery-level prospect. Without elite positional size and given his middling athleticism and ball skills, Alvaro’s entire projection could begin to unravel. But if he measures at 6’10” in shoes with a 7’4″–7’5″ wingspan and a solid BMI, he may possess one of the most favorable cognition-plus-size intersections we’ve seen in years, paired with what could be an elite jumper.

A pillar of my evaluation process is identifying historically favorable skill intersections. For decades, big players with exceptional feel for the game have consistently provided positive on-court value in the NBA, and  Alvaro Folgueiras appears to be next in line.

The post Prospect Preview: Alvaro Folgueiras appeared first on Swish Theory.

For this piece, I’m talking to Swish Theory’s Avinash Chauhan, who makes an optimistic claim about Texas wing Dailyn Swain. You can find Avinash’s Swish Theory work here, additional basketball musings at his Substack here, and follow him on Twitter here.

Avinash’s claim: Dailyn Swain is a top-20 level talent in the 2026 NBA draft.

Question #1:

The list of drafted players Swain’s height with a <15 three-point attempt rate (3PA/FGA) is littered with misses. Opponents leave him wide open. Do you think his outside shot is absolutely cooked (career 11-54 from three, 27-74 from midrange) or is there some hope?

Avinash:

How could it not be cooked? Swain is an astonishing 3 for 23 on open catch-and-shoot 3s. I would advise against expecting strong 3P development across his career, and I remain quite high on Swain despite this cognizance. He does not need to shoot to be a productive NBA player.

But is there hope? There will always be hope with a profile as contradictory as Swain’s.

Swain shoots extremely well from the FT line (career 81.6% FT across 152 attempts). While FT proficiency is usually a sign of future shooting goodness, it can’t be that easy.

See, Swain is in this weird zone, shooting enough threes to not be a complete non-shooter, but shooting a relatively low number of threes overall and bricking them.

To showcase this, let’s focus on the three main indicators of shooting upside: FT%, 3P%, and 3Pr.

High FT% + High 3PR + High 3P%: elite elite shooter

• Ex. Steph Curry, Sam Hauser

High FT% + High 3PR + Low 3P%: still an elite shooter, likely lots of OTD 3s

• Ex. Austin Reaves, Franz Wagner

High FT% + Low 3PR + High 3P%: usually a rim-heavy guard that can still end up shooting

• Ex. Shai Gilgeous-Alexander, Jalen Williams

High FT% + Low 3PR + Low 3P%: ???

This is an extraordinarily rare intersection: just 7 NBA-appearing college players since 2008 have shot worse than 40% 3P with less than 4 3PA/100 while still shooting 80% from the line. What’s even more interesting is that just 3 of these players had a true career sample: it’s really just Delon Wright, Hansbrough, and Mike Muscala that met this intersection over multiple seasons, and only Mike Muscala did it over more than 2 seasons. Swain appears poised to join him.

What makes this even more baffling is that Swain has been shooting 80% from the line all the way back to his AAU days. In 37 AAU games over 16U and 17U Nike EYCL seasons, Swain shot 83/107 (77%) from the line. That means Swain has been shooting ~80% FT since 2021.

75% FT, < 30% 3P, < 2 3PA/game. From my AAU database with ~2000 player-seasons, just 5 players met these criteria. Despite every one of the NCAA players here having lower career FT% in NCAA compared Swain, they at least doubled his 3Pr.

Some other notes:
Swain has shot 13/33 (39%) on dribble jumper 2s across 2 NCAA seasons. He shot 7/25 (28%) on dribble jumpers in AAU. At least there’s touch improvement somewhere, and there’s a bit of asymmetric reward to risk. It’s the type of shot someone with a 14% PnR BH scoring frequency could really use (this is a superb rate for a wing-sized player).

And Swain narrowly missed this query with a number of impressive developmental stories, sporting an assist percentage just 1% off the 12% threshold.

So we have 100 games of Swain’s low 3P make + high FT% tomfoolery across AAU+NCAA, and he has at least 30+ games left in his college career. This is uncharted territory, and your guess is just as good as mine for whether he ever meaningfully shoots. For what it’s worth, the only person close to this sort of volume (Muscala) shot 37% 3P on 8.2 3PA/100 for his NBA career, but it took him 6 NBA seasons to actually hit that rate across a season.

And, Swain kinda ended the season with some momentum. He went 3/5 from 3P in his final game vs Illinois in the first round of March Madness. It was actually his best college game ever (27 points, 27 BPM, 33% USG, 6 assists+steals : 0 TOs). Positive momentum for the win?

Maybe. For those keeping track, that also means he was 1/9 from 3 during that month, excluding the Illinois game. Still, his 3PA/100 was doubled relative to his career average across that final month.

To summarize: Swain’s profile holds an unparalleled long-term integration of FT% goodness x 3P badness, nice dribble jumper proficiency, high levels of cognition typically associated with strong development, and positive momentum. And he’s super young for class. This year, I expect some 3P shooting improvement for the first time in years.

But he’s missed so many 3s for so long that it’s still more likely than not that he does not end up shooting well. There’s hope, but he doesn’t really need it. He should be a solid NBA contributor regardless.

Question #2:

A big part of the appeal for Swain is his being a wing ballhandler. This premise makes his fans excited about his transition game and utility as a pick-and-roll operator. However, his turnover rates for both pick and roll when pressured and when used as a transition ballhandler are a very high 30% for each.

Avinash:

A big part of Swain’s appeal is indeed his wing ball-handling upside. He clocks in at an impressive career 15% assist rate on just 17% usage. However, his career 16% TO rate is unimpressive relative to this lower usage. What gives?

The unifying theme of Swain’s turnovers is errant passes. This is important to me, as most other wings that I’ve watched have turnover issues more concerned with scoring process or poor dribbling technique.

More specifically, Swain is trying to get rim assists at a pretty high clip, which is actually a feature of the Xavier offense: they ranked in the 4th and 1st percentiles in spot-up frequency in 2025 and 2024, respectively. There are some gimme assists that he fails, like bouncing off his foot, but his biggest issue is just forcing passes into very tight windows, as well as poor pass accuracy on the move.

In defense of Swain, he didn’t quite have the safety valves that others may have. First, Xavier probably had the worst “center” rotation out of any reasonably good high major team. Their center was Zach Freemantle, a 6’9 225 lb power forward with a mediocre wingspan. Forcing the ball to a guy with such a limited catch radius is just not ideal, but he just didn’t have those other safety valves. Beyond their uber-low spotup frequency, Xavier didn’t run many cuts either (13th percentile in 2025, 7th percentile in 2024), meaning that many of Swain’s passes out of PnR had to be post entries.

As a side note, Swain probably should be used more on cuts. He has the body and intuition for it, along with 1.3 PPP last year. Unfortunately, Xavier’s primary perimeter PnR was 6’2 Dayvion McKnight, who shot 49% at the rim and less than 3 3PA/100. His abhorrent 0.702 PPP on PnR BH, and the departure of the four Xavier players with higher assist rates than Swain in 2024, were major reasons why Swain’s PnR BH frequency doubled from 2024 to 2025.

So, Swain’s TO rate when defense commits is concerning, but it was a bad enough context that we can hopefully expect strong improvements with his feel and another year under his belt. It is something to monitor.

Swain’s turnover rate in transition is less defensible. The most obvious culprit again seems to be errant passing. He’s more pass-heavy in transition than I expected, considering a massive 30% of his scores came in transition. He’s just moving too quickly and isn’t able to make dynamic, accurate kick-ahead reads.

Ultimately, Swain has clear turnover issues, but not something I would consider truly pivotal: I’d be more concerned if more of these were bad scoring TOs rather than bad pass TOs (see below: his drive TO rate). His career 1.7 A:TO and 3% steal rate indicate strong enough cognition that we can partially cope that this is an issue of poor technique rather than processing. I expect more turnovers with increased usage, but hopefully he trims the rate somewhat.

Question #3:

Additionally, his 1.4 drives per game lags the second-year drive rate of Herb Jones (1.8 per game), Kyle Filipowski (2.9), or Mikal Bridges (1.7), among prospects with relatively similar production profiles. What kind of ball-handling burden/complexity is Swain really capable of when faced with tougher comp?

Avinash:

Yes, to activate higher-end outcomes worthy of meaningful draft capital, Swain needs to demonstrate creation capacity. His career 17% usage + 55% minutes share after two seasons lags a bit behind these names mentioned. While it remains to be seen how well he scales up, his playtype rates, rather than per-game numbers, is probably more instructive.

Let’s compare his playtype numbers to the names mentioned, plus three more I added. I used Bart’s Career Player Comp feature to generate this query that ranked the most similar careers to Swain, and added an NBA filter and height filter. I chose the top 3: OPJ, Cody Martin, and Dalen Terry.

Swain’s 13.4% drive frequency isn’t as pressing in this paradigm, but it still notably lags behind Filipowski and Herb.

However, Swain crushes the field in drive efficiency, with over 0.9 points per drive possession. He does this with the lowest drive turnover rate, while still drawing a healthy number of fouls per drive. This micro turnover rate is an interesting antidote to his turnover concerns.

However, since there is typically no double-counting between drive possessions and PnR BH possessions (a drive does not involve a screen), I like to account for these PnR BH “quasi-drives”.

Immediately, Swain’s massive PnR BH frequency stands out. Part of why Swain’s drive frequency was so low is that he scored on PnR BH possessions at a high rate.

It’s not just higher PnR BH frequency relative to the field. Swain’s scoring approach out of PnR BH playtypes was far better than any other player here. If we ignore Filipowski’s inflated stats out of a 1.3% PnR BH frequency, Swain paces the group in PnR BH frequency, PPP, AND free throw rate. His TO rate ranks 3rd out of 6.

To recap, Swain is the most efficient on drives and PnR BH reps among these players…while ranking close to the top in TO rate and FT rate. His drive+PnR BH aggregate frequency trails just Herbert Jones and his query-worst aggregate PPP.

To be fair, none of these guys were really creating like that in the NBA. But Swain’s production transcends this comparison. And he’s the youngest here, while weighing at least 10 more pounds than anyone besides Filipowski. With potentially the best wingspan. There’s just no argument to me: Swain has by far the best creation upside of the group.

Increased ball handling burden is inevitable, and while improving handling control and complexity are not something I can easily project, there’s just too much here for me not to expect continued improvement.

You can’t get better datapoints than size/age-adjusted creation efficiency (not that it needs to be adjusted) and strong cognition. While you raised exceptional points that cannot meaningfully be refuted until we see it manifested, this is my best cope.

Question #4:

That all sounds great, and I am struggling to poke holes in Swain’s fairly complete game otherwise. But I do struggle to see what kind of role Swain would fit into immediately that both keeps his development curve sharply sloped and the friction with NBA lineups low (absent a major shooting leap). How does he fit in right away?

Avinash:

Swain is largely theoretical in impact right now. He possesses a slew of important traits, from his FT touch to his cognition to his impressive ballhandling at size…but he hasn’t been particularly impactful.

A net offensive rating impact of -0.8 when Swain is on compared to Xavier’s baseline is very underwhelming for a decent offense. Swain has a positive FTR influence, and his positive TO influence is an improvement from last year. We can attribute this to his scaling up (higher PnR and driving responsibility) while maintaining A:TO.

The lack of on/off impact is emblematic of a more pressing issue with Swain: there just isn’t a whole lot of “guarantees.”

He’s promising in a lot of areas, but not truly adept at anything in relation to halfcourt offense. You’d think a player with his athleticism and transition prowess would be able to be more effective at the rim, but Swain shot a pedestrian 64% at the rim on a majority-assisted rim diet. While there’s some sliver of ball handling upside, there’s also a chance Swain isn’t able to convert self-created rim attempts at a respectable rate.

Swain is what I’d call a “trait-maxxed” player: he checks lots of boxes that indicate high upside. He’s super young, he will measure and test exceptionally well, and he blends cognition, physicality, and touch in a way that typically translate to NBA goodness. But he simply hasn’t quite done anything worthy of NBA status … yet.

Without improved shooting volume, the projection is somewhat difficult but not impossible. Something like an athletic finisher with defensive impact, something in the realm of Ausar or Josh Minott. He could carry over his 98th percentile transition frequency to the league and do his best Christian Braun impression, though that is somewhat dependent on the context. This may not sound too compelling, but my thesis is that Swain’s ancillary production is too good to fail. It’s quite similar to my case for the aforementioned Josh Minott, who also faced questions about his NBA role, but is making it work given his cognitive and physical strengths.

To answer the other half of your question: based on historical trends, I believe that trait-maxxing is the most important predictor of development over expectation. Massive arms and feel, for instance, has been Sam Presti’s method to draft success. This is why I believe his development curve will be sloped upwards regardless of role, for the time being: he’s entering the critical period of development (age 20/junior year) where the big-time leaps occur.

Can he access super high-end outcomes without being able to shoot at reasonable volume? Probably not. But the guy is an S-tier athlete with huge dimensions, can run creation playtypes at efficiency, and he’s an elite stocker with strong passing and rebounding. There is a small (and improbable) chance that Swain could check every single meaningful “trait” box and parlay that into stardom, particularly if he shoots (and as I outlined before, higher volume shooting isn’t as unlikely as you may think).

In an expected value paradigm (probability x value), a miscellany of small probability x high upside avenues can aggregate towards a sneaky-high expected value. It is difficult for me to project the specifics of Swain’s development curve, but I feel that his expected value is somewhere in the tier of a real deal NBA player. Let’s see if ancillary production and trait-maxxing can manifest in legitimate impact.

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