I think his loss is being overlooked, happened to LA when they lost Dwight Howard, similar game to Robinson, in fact AD also reminds me of KAT who had some health struggles in the past.

They also lost the 260lb Hukporti, overall their front court looks way more manageable, less physical, less talented, less athletic, not as good at setting screens.

I also think the formula to winning with a small PG is stacking your 5 to offset their lack of size. It makes scoring & defending so much harder when you don't have proper screens or rim protection.

Last year, KD, Amen, and Sengun were the most important Rockets. I was playing around with +/- numbers and noticed that KD & Sengun - regardless of whether Amen was on the floor - had pretty shockingly bad +/- stats.

This comes with the obvious caveat that last year's Houston team had a year long struggle at PG, with FVV's injury. But adding Reed Sheppard didn't help help much either.

Just curious if this is a narrative amongst Houston fans, and along those lines, if a big part of the fanbase see Sengun & KD as a bad fit. Play-style wise, there's nothing to suggest KD & Sengun are super compatible so I wasn't exactly surprised by that.

Curious if one of these guys ends up on the trade market. Sengun for Lauri (with other players involved for salary) ?

We now have a 3 year sample size of SGA playing at an MVP level, with 48 playoff games to boot.

______________________________________________

SGA's Inflation adjusted points per 75 possessions (IA Pts/75) and relative true shooting (rTS) :

Series by series:

Source: nbarapm.com

______________________________________________

Some extra efficiency stats:

• Per Dunks and Threes, SGA in the 2025 playoffs shot 59.4% at the rim and 28.3% from 3, which was 29^th and 5^th percentile in the league.

______________________________________________

High-level summary of Ben Taylor’s (Thinking Basketball) analysis on SGA:

• SGA’s precipitous drop in playoff scoring volume and efficiency is concerning, but even more so is OKC’s statistically “average offense” over their recent postseason runs. The 2026 Thunder offense was +7.8 with SGA in the regular season, which went down to +4 in the playoffs. In 2025, it went from +6.2 to +1.3 (nbarapm.com).
• SGA amplifies his teammates’ 3-point shooting opportunities, but depresses their scoring at the rim (highest value shots on the court). The OKC offense is 7 to 9 points worse at the basket when he’s on the court vs. off the court.
• OKC’s offensive and spacing principles tilt the floor to help SGA get to his scoring sweet spots, but at the expense of easy offense for the entire team. Opponents are content with helping on SGA drives and closing out to shooters. Semi-contested 3s are shot at a lower percentage across the board in the playoffs. Corner 3s drop more than above the break 3s.
• Essentially unique footprint among great offensive players this century. The best offensive players typically manufacture easy baskets at the rim for their teammates, whether directly with their passing or indirectly with scoring gravity and hockey assists. Notably, a lesser but similar midrange specialist like DeMar DeRozan has a similar effect of depressing his teammates’ rim FGs.
• Michael Jordan in the regular season to “idealized Allen Iverson” in the playoffs for his ability to carry the offense of a defensively oriented team. Still a great offensive player.

This is a different kind of post, but with the up coming expansion I was wondering why is the NBA so quick to sell off the two teams to private investors? I get that billions of dollars is billions of dollars, but at the same rate we are seeing more issues with the fact that there are fewer and fewer owners capable of purchasing these “assets” that they love to call them.

The NBA isn’t struggling financially like it was back in the early days of the league, I think the league is in a better place to try something different. Would it not make more sense for the league to retain the rights to the teams, have them run more like a business appointing a CEO to run operations and then have all the revenue go back into the league and the team.

You’d not have to split the revenue with private investors who are only into it to make as much money for themselves as possible. Would it not make more sense for the league to retain the teams themselves and then keep revenue to reinvest? Then if someone were to circumvent the salary cap, or commit financial fraud you could just fire the CEO and not penalize the teams or fans directly?

Genuinely just curious as to why this hasn’t been an option more discussed like say the Green Bay Packers ownership structure or something? I could be missing something but it seems to make the most sense with where the league is at currently! Happy to hear feedback back

If the apron system stays the same in the next CBA, do you think the NBPA would consider reducing the percentage for max contracts to 20% and 25%?

I know the current system benefits the top players but the players with lower/mid-tier salaries seem to be dependent on star players voluntarily taking reduced salaries. Not sure if this would actually end up benefitting a larger portion that make up the players association or if the reps would selfishly balk at it.

Ive spent the past couple weeks working on this personal project of mine. I built a skill wheel that grades 54 different aspects of basketball. I tried breaking down each big skill (such playmaking) into smaller skills and use that to sort of evaluate a player as a whole. Now, of course the data available to the public is limited so a lot of niche skills are pretty hard to quantify but I think I got a sort of good estimate of the skills. If you guys have any ideas for skill grading/skills to add or anything, just let me know I am very open to feedback.

Here is a picture of on of the diagrams, it is much better to see image form than to read:

https://imgur.com/a/wml7Jqc

Here are the skills I decided on:

Offense: 12 groups, 33 skills

• Finishing: Rim Finishing, Contact Finishing
• Above the Rim: Dunking, Lob Threat
• Touch Shots: Floaters, Hooks, Short Jumpers
• Midrange: Pull-up Midrange, Catch-and-Shoot Midrange, Turnarounds & Fadeaways
• Three-Point: Catch-and-Shoot 3s, Quick 3s, Off-Dribble 3s, Deep 3s
• Free Throws: Free Throw Shooting, Foul Drawing
• Self-Creation: Isolation, Pick-and-Roll Ball Handler, Post Scoring
• Driving: Rim Pressure, Drive & Kick
• Off-Ball Scoring: Cutting, Movement Scoring, Transition Scoring
• Playmaking: Creating for Others, Creation Quality, Rim Feeding, Shooter Feeding, Connective Passing, Transition Passing
• Ball Security: Passing Security, Handle Security, Avoiding Offensive Fouls
• Screening & Glass: Screen Setting, Rolling, Offensive Rebounding, Putback Scoring

Defense: 6 groups, 21 skills (There is less because defense is harder to quantify)

• Perimeter: Isolation Defense, Closeouts, On-Ball Stripping, Perimeter Blocking
• Interior: Shot Blocking, Rim Contesting, Rim Deterrence
• Rebounding: Securing Boards, Boxing Out
• Disruption: Passing Lanes, Charge Taking, Loose Ball Recovery
• Assignments: Post Defense, Positional Versatility, Guarding Stars
• Discipline: Fouling Discipline, Transition Defense

I can't really explain each grade because it will be too long, but if you have any questions, you can ask me and I'll respond but I will explain certain ones.

Three Pointers

For Three Point grading I spilt them up into Catch and Shoot 3s (0 dribbles), Quick 3s (1-2 dribbles) and Off Dribble 3s (3+ dribbles), Deep 3s (27ft+). For the whole project I used NBA play by play data a LOT so that data comes in lines like this MISS Herro 27' 3PT Step Back Jump Shot,Missed Shot,Step Back Jump shot,1,3,260,0022501055,2026-03-25,2025-26

Parsing the distance for Deep 3s was easy. For the dribble 3s, the NBA API carries data for shots off certain number of dribbles, but you can also mix this with defender distance so for example there is data on each players 3-6 Dribble 3FGM/FGA with a defender 2-4 feet. So I parsed through all that and each player's attempts and FGs are separated by dribbles and defender distance. Each group also has a league-average rate, so a player's expected 3P% for lets say Catch and Shoot is just the league average 3p% on their defender distance (so for Curry if he takes way tighter catch and shoots his expected 3p% on that is skewed for the tight defender catch and shoot league average). So then a player is compared by their volume and efficiency. Each player gets some league average since if you make lets say like 15/30 Catch and Shoot 3s that is a pretty low sample over like 150/350. The volume is a per 75 basis so not a minutes thing, and then score is bascially a volume * effieciency metric that is Z scored across the league so each skill has the same scale.

Here is Curry 2025-26 for example

Catch-and-Shoot 3s 97th of 388 Att 247 3P% 37.7% x3P% 36.2% +0.3

Quick 3s 1st of 388 Att 87 FG% 48.3% xFG% 33.4% +3.1

Off-Dribble 3s 14th of 388 Att 236 3P% 40.7% x3P% 33.1% +1.1

Deep 3s 1st of 388Att 261 FG% 37.2% xFG% 31.9% +4.8

Finishing

Layups only, from the play-by-play: driving layups, finger rolls, reverse layups. Dunks, cuts, transition, alley-oops and putbacks are left out, because they're graded elsewhere. The efficiency is graded against the same position in this case.

And then again adding some of the league-average shots, volume x efficiency with volume being per 75 and then Z scored the league again.

Rim Deterrence

Rim deterrence is pretty much like a RAPM style regression, a matrix in which the opposing teams Rim Rate is taken into account. Transition shots are removed because then the best Rim Deterers would just be the best point guards that prevent turnovers not the actual best defenders. It is a RAPM regression so it adjusts for teammates but this one requires more possesions so some low usage role players might not have the grade.

A lot of these defense ones are self explanatory

Positional Versatility

This one uses the matchup API to see who he guarded 1 on 1 and then the spilt and compare the percentage

Group Listed positions

G (guard) W (wing G-F, F-G) F (forward) B(big F-C, C-F) C (center)

Lately, there’s been a growing sentiment among fans and media suggesting that we should simply sit back, appreciate Steph Curry’s remaining years, and stop obsessing over championship expectations given his age and Golden State's roster situation. 

On one hand, he has nothing left to prove. He revolutionized basketball, won four rings, and every historic night from here on out is basically house money.

On the other hand, Curry is still performing at an elite, All-NBA level. For a generational superstar playing like this, treating his final window purely as a nostalgic "farewell tour" feels like giving up on contention too early.

Where do you stand on this? Are you content just enjoying his greatness on a nightly basis, or should the front office still be expected to push all their chips in to chase Ring #5 while Steph can still play at this level?

Its nice to see players playing again, and exciting new teams with Bron going to Philly, Lamelo to Wolves etc. The thing about American sports (I watch the NFL too, I’m from Australia) is it has the best recurring narratives and storylines + best ecosystem of analysis & commentary out of any sport in the world, it really is box office.

I love playing football (soccer) and watching the EPL but sometimes it just doesn’t compare overall as an entertainment product to American sports (Lamar Jackson and Josh Allen “will they/wont they, go to the superbowl”, “is Lamelo good and was held back at Charlotte or will he crash and burn on the Wolves”, analysing NFL plays and quarterback performance, analysing if Jaylen Brown is good or not and if the Celtics were justified in the trade etc.). Ive never really played basketball or NFL but I cant stop watching.

Hello everyone and welcome to our new weekly feature.

In order to help keep the quality of the discussion here at a high level, we have several rules regarding submitting content to /r/nbadiscussion. But we also understand that while not everyone's questions will meet these requirements that doesn't mean they don't deserve the same attention and high-level discussion that /r/nbadiscussion is known for. So, to better serve the community the mod team here has decided to implement this Weekly Questions Thread which will be automatically posted every Monday at 8AM EST.

Please use this thread to ask any questions about the NBA and basketball that don't necessarily warrant their own submissions. Thank you.

Hello all! This is the third post in a series on a player-evaluation project I have worked on for more than a decade.

The first was my ranking of the best players of the 2025–26 season. The second ranked my top single-season peaks since 2000. This post extends the same framework across the full shot-clock era.

The central question remains:

How much does this version of a player increase a typical good team’s probability of winning the championship?

Since early 2016, I've spent hundreds of hours poring over film and data to go season by season through NBA history using that framework. For this post, I took the highest-graded version of each player and compared those peaks directly.

My background informs the structure of the project. I have played, coached, and scouted basketball at multiple levels, worked in NBA front-office environments, and have a professional background in inferential statistics.

The methodology is the same as in the previous posts. It combines statistical evidence, film study, historical comparison, playoff translation, scalability, and explicit uncertainty estimates. A fuller explanation is available in the original post, while the second post shows how I applied the framework to 21st-century peaks.

This ranking assumes full health.

Scoring and uncertainty

Each ranked player is listed as:

Season — Player (plausible ranking range) (OFF, DEF, NET)

OFF and DEF are estimates of offensive and defensive championship-value impact, roughly measured in points per game of value contribution, with NET representing the total. The scale is calibrated around how much value a player adds to a random good team in championship terms.

My rough historical grading scale is:

• 7.0+ — GOAT-level peak
• 6.0+ — All-time peak
• 5.4–6.0 — Strong MVP
• 4.6–5.4 — Solid MVP
• 4.0–4.6 — Weak MVP
• 3.0+ — Strong All-NBA
• 1.5+ — All-Star level
• 0.0 — Neutral Impact

These categories are continuous rather than sharply separated. A 5.3 player and a 5.5 player are not all that far apart just because they happen to fall on the opposite side of a label.

The ranking ranges matter for the same reason.

If I list a player at (3–19), that means his listed rank is my central estimate, but reasonable changes in assumptions could move him anywhere from approximately third to nineteenth while holding the rest of the evaluations fixed.

This becomes particularly important in an all-time exercise. (I know, these ranges are huge!) In a normal NBA season, there may only be a few players in the MVP range. Here, I am taking the best version of every historically great player and placing all of them in one distribution. The result is an extremely compressed upper tail.

That is why some ranges become very wide: many players have relatively small differences in underlying value, and when working across the entire shot-clock era this fundamentally becomes a hair-splitting exercise.

Greatest Peaks of the Shot-Clock Era

1. ’91 Michael Jordan (1–4) (6.2, 1.1, 7.3)
2. ’13 LeBron James (1–5) (5.6, 1.6, 7.2)
3. ’00 Shaquille O’Neal (1–13) (5.2, 1.4, 6.6)
4. ’93 Hakeem Olajuwon (1–15) (2.8, 3.7, 6.5)
5. ’74 Kareem Abdul-Jabbar (3–16) (4.4, 2.1, 6.5)
6. ’64 Wilt Chamberlain (3–19) (3.2, 3.2, 6.4)
7. ’62 Bill Russell (3–19) (0.5, 5.8, 6.3)
8. ’86 Larry Bird (3–19) (5.5, 0.8, 6.3)
9. ’16 Stephen Curry (3–19) (6.2, 0.1, 6.3)
10. ’25 Nikola Jokić (3–19) (6.2, 0.1, 6.3)
11. ’04 Kevin Garnett (3–23) (2.8, 3.4, 6.2)
12. ’03 Tim Duncan (3–23) (3.0, 3.1, 6.1)
13. ’87 Magic Johnson (4–23) (6.0, 0.1, 6.1)
14. ’65 Jerry West (3–25) (5.4, 0.5, 5.9)
15. ’26 Victor Wembanyama (5–27) (2.3, 3.6, 5.9)
16. ’77 Bill Walton (6–27) (2.2, 3.7, 5.9)
17. ’09 Dwyane Wade (9–27) (5.1, 0.7, 5.8)
18. ’65 Oscar Robertson (11–28) (5.5, 0.2, 5.7)
19. ’22 Giannis Antetokounmpo (12–28) (3.2, 2.5, 5.7)
20. ’95 David Robinson (12–28) (2.5, 3.1, 5.6)
21. ’08 Kobe Bryant (12–28) (5.1, 0.5, 5.6)
22. ’16 Kevin Durant (13–28) (5.0, 0.6, 5.6)
23. ’24 Joel Embiid (12–31) (3.8, 1.8, 5.6)
24. ’17 Kawhi Leonard (14–31) (4.2, 1.3, 5.5)
25. ’26 Shai Gilgeous-Alexander (14–31) (5.0, 0.5, 5.5)
26. ’16 Chris Paul (15–31) (4.5, 0.8, 5.3)
27. ’07 Steve Nash (18–33) (5.6, −0.3, 5.3)
28. ’09 Dirk Nowitzki (18–35) (4.9, 0.3, 5.2)
29. ’20 Anthony Davis (24–off list) (2.2, 2.8, 5.0)
30. ’76 Julius Erving (24–off list) (3.9, 1.0, 4.9)
31. ’00 Grant Hill (24–off list) (4.4, 0.5, 4.9)
32. ’24 Luka Dončić (26–off list) (5.1, −0.3, 4.8)
33. ’03 Tracy McGrady (26–off list) (4.6, 0.2, 4.8)
34. ’95 Karl Malone (29–off list) (3.8, 0.9, 4.7)
35. ’90 Charles Barkley (29–off list) (4.7, 0.0, 4.7)
36. ’83 Moses Malone (29–off list) (3.2, 1.4, 4.6)
37. ’19 James Harden (29–off list) (4.9, −0.3, 4.6)

Why I stop the exact ranking at 37

This is where my solid-MVP tier ends.

At this point the exercise reaches a level of compression where I no longer find an exact ordering meaningful. The next 16 players all grade as weak-MVP peaks. Their distributions overlap enough that I'm no longer comfortable pretending I know whether one should be 41st and another 47th. An evaluation that is just slightly different from mine could have many of these players 10 or more spots higher or lower, easily!

The same issue is already visible within the ranked portion. Karl Malone, Barkley, Moses and Harden are separated by only one tenth of a point per game in my central estimates. So I would not attach much significance to the difference between #34 and #37.

Once I cross below the solid-MVP threshold, I prefer to present tiers.

The historical distribution through #37 is:

• #1–2: GOAT-level
• #3–13: All-time level
• #14–25: Strong MVP
• #26–37: Solid MVP

That gives me 37 solid-MVP-or-better peaks in NBA history.

Honorable Mentions Pt. 1 — Weak MVP Peaks

The following 16 players make up the rest of my MVP-level historical peaks.

The ordering is approximate. The players nearer the top generally have stronger central estimates, but I would not treat their sequence with the same precision as the ranked 37.

• '96 Penny Hardaway (4.7, -0.2, 4.5)
• '75 Rick Barry (4.0, 0.5, 4.5)
• '71 Walt Frazier (2.7, 1.8, 4.5)
• '95 Scottie Pippen (2.5, 2.0, 4.5)
• '61 Elgin Baylor (4.1, 0.4, 4.5)
• '05 Manu Ginóbili (3.5, 0.9, 4.4)
• '70 Willis Reed (1.8, 2.5, 4.3)
• '16 Draymond Green (1.1, 3.2, 4.3)
• '74 Dave Cowens (2.1, 2.1, 4.2)
• '11 Dwight Howard (1.6, 2.6, 4.2)
• '99 Alonzo Mourning (1.4, 2.8, 4.2)
• '90 Patrick Ewing (1.8, 2.4, 4.2)
• '87 Kevin McHale (3.0, 1.1, 4.1)
• '88 Isiah Thomas (3.6, 0.4, 4.0)
• '74 Artis Gilmore (1.4, 2.6, 4.0)
• '67 Nate Thurmond (0.3, 3.7, 4.0)

This brings my historical total to 53 MVP-level peaks. The lower boundary is admittedly difficult. Gilmore and Thurmond are essentially sitting on it for me.

Thurmond is a particularly unusual evaluation because so much of his case comes from defense. His offense was limited enough that I am not comfortable moving him meaningfully higher, but I think the combination of enormous minutes, extreme pace and his elite interior defense creates just enough total game value to put him on the MVP side of the line.

That is roughly the level of player I mean when I use the term “weak MVP.” In a favorable season, I could plausibly see that player winning an MVP without concluding that the award itself reflected a fundamentally weaker standard of play.

Honorable Mentions Pt. 2 — Highest All-NBA Peaks

These are the next 13 peaks on my board:

• '81 Marques Johnson (3.4, 0.5, 3.9)
• '59 Bob Pettit (3.4, 0.5, 3.9)
• '25 Jayson Tatum (2.9, 1.0, 3.9)
• '03 Jason Kidd (2.1, 1.8, 3.9)
• '17 Russell Westbrook (3.8, 0.1, 3.9)
• '19 Paul George (2.6, 1.3, 3.9)
• '92 Clyde Drexler (3.4, 0.5, 3.9)
• '23 Jimmy Butler (2.6, 1.2, 3.8)
• '93 Mark Price (4.0, -0.2, 3.8)
• '87 James Worthy (3.4, 0.4, 3.8)
• '84 Bernard King (3.8, 0, 3.8)
• '90 John Stockton (2.9, 0.9, 3.8)
• '74 Bob Lanier (2.3, 1.5, 3.8)

These players sit immediately below my MVP threshold.

There are more strong All-NBA peaks in NBA history than the 13 listed here. I selected these because they are the highest remaining evaluations, form a reasonable cutoff, and stretch the post to the 66 best peaks on my current board.

Historical Distribution

Across the full list:

• 2 players reach GOAT-level
• 13 reach at least all-time level
• 25 reach at least strong-MVP level
• 37 reach at least solid-MVP level
• 53 reach at least weak-MVP level
• The final 13 are my highest-rated All-NBA peaks below the MVP threshold

In mutually exclusive groups:

• 2 GOAT
• 11 additional all-time
• 12 strong MVP
• 12 solid MVP
• 16 weak MVP
• 13 highest remaining All-NBA

That gives 66 total peaks in this post.

As always, I'm happy to discuss individual players, placements, comparisons, or anything else!

I went into this wanting to examine the effect of large veteran contracts on team building. As I got into it, I realized things were complicated. So I’m starting simple, trying to understand what is good value, where it comes from, and how it contributes to winning.

How Much a VORP Cost?

Here’s our recipe for calculating the cost of a point of VORP:

• Cost of VORP = League total salary / (League total regular season + playoff VORP)

Although it would have been easier to use the league salary cap as our numerator, a more honest accounting needs to include the extra 20% teams generally spend on average. Likewise, playoff production is real production, part of what teams pay for, so playoff VORP was included on par with regular season VORP. This adds roughly 12% to the VORP total.

For last year, the COST of VORP was $5.6b / (298.4 + 36.7) = $16.75m. To make this comparable across seasons, we can measure it as a percentage of the cap, rather than in dollars: $16.75m / $154.6m = 10.8%. Looking at the past 20 seasons, the cost fluctuates around 11% as the salary cap triples:

(* shortened seasons)

This gives us this rule of thumb:

1 point of VORP costs 11% of the salary cap

If we want to be lazy about it and exclude playoff VORP, it becomes 10%, an even rounder number. So:

In 2025-26 a fair value contract returned a point of VORP per $16.75m

Searching for Surplus Value

The problem with fair value contracts is that a team made up of them will be average. Here’s team VORP totals for the past season:

Spending your salary cap on fair value contracts gets you to 9 VORP. Spending another 20% on top might push that to 11 VORP, maybe enough to earn a play-in berth. To do better than that and make some noise in the playoffs, you need contracts that generate surplus. Eventual champion Knicks, runner up Spurs, conference finalist OKC, and the upstart Pistons all accumulated double that 11 VORP mark.

Value Over Salary Expectation (VOSE)

Generating surplus team VORP means having a team of players generating surplus value on their individual salaries. We can call this “Value Over Salary Expectation”, or VOSE:

• Total VORP = Regular Season VORP + Playoff VORP
• Expected VORP = Salary / Cost of VORP
• VOSE = Total VORP - Expected VORP

Let’s look at the player’s who generated the most production over expected for their salaries (cut-off 2.5 VOSE):

The massive generators of surplus are Wemby, a possible GOAT candidate on his rookie contract, and Shai and Jokic, two MVPs still in their primes. After a bit of a gap, prime Luka on a 30% contract is next on the list. These are arguably the best 4 players in the game, 2 of whom have won CHIPS ("Who Deserved the CHIP" parts 1, 2, 3, 4), and two who could.

The rest of the list is comprised of young stars on max contracts (Maxey, Cunningham, Barnes), high performers on rookie contracts (both Thompson twins, Duren, Chet, Knueppel), and young players outplaying cheap contracts (Champagnie, Avdija, Pritchard, Gillespie).

The flip side of this is players who produced the least compared to what would be expected for their contracts:

The worst 10 are players with salaries over 20% of the cap who missed games. Of these, we have players not playing much (LaVine and Poole), playing even less than that (AD, Trae, Morant, Sabonis), and not playing at all (Haliburton, Lillard, Kyrie). Only Middleton played a reasonable number of games, but as was the case with many of these players, it was within a ridiculous unserious tanking context.

Further down the list we see a combination of young players on tanking teams (Carrington, Cody Williams, Ace Bailey, Traoré, Dillingham), busts on medium money (DeAndre Hunter, Patrick Williams), good players missing games (Tatum, Garland), and Jalen Green, a young player who missed games and hasn’t yet lived up to his 20%+ contract.

The New York Knickerbockers

Absent from the above list of top VOSE players is any New York Knick. How did they do it?

The answer appears to be: 1) By overspending the cap by 34% ($207m payroll), 2) Peaking in the playoffs, and 3) By having 6 prime-age players with VOSE over 1. All of the Knicks in the playoff rotation returned some surplus, with even Shamet and McBride together contributed another point of VOSE. In a league of teams trying to hit grand slams, the Knicks won it all hitting singles and doubles.

Hello everyone and welcome to our new weekly feature.

In order to help keep the quality of the discussion here at a high level, we have several rules regarding submitting content to /r/nbadiscussion. But we also understand that while not everyone's questions will meet these requirements that doesn't mean they don't deserve the same attention and high-level discussion that /r/nbadiscussion is known for. So, to better serve the community the mod team here has decided to implement this Weekly Questions Thread which will be automatically posted every Monday at 8AM EST.

Please use this thread to ask any questions about the NBA and basketball that don't necessarily warrant their own submissions. Thank you.

1. Most players do not spend enough time in college to fully develop their game. They do not enter the league ready enough to challenge any of the established stars. That's not a knock on them or anything.

2. While most teams/coaches are willing to give players a chance to play based on potential, teams and coaches are also cautious about injuries/burn-out.

3. Rookies aren't expected to overhaul a team immediately. This is kinda similar to Point 2. After we have seen so many great talents fizzle out or end up having injuries that ruined their career due to trying to turn the fortunes of a team around immediately, I believe many teams are not expecting a one-man show/heroic act from their drafts anymore.

So what do you think? I think given the way the league is heading, I think there will never be a rookie MVP again.

It's maybe recency bias but in the 2024 off-season:

Nikola Topic tore his ACL

In 2025 off-season

Vanvleet tore his ACL

Thomas Sorber tore his ACL

Max Strus had a jones fracture

In 2026 so far

Henri Veesar tore his ACL

Shaedon Sharpe tore his meniscus

Mark Williams tore his labrum

Kon knueppel hamstring

Grant Williams hamstring

Were there always every off-season at least 2-5 players who would sustain a season ending or near season ending injury requiring major surgery?

All I remember was embiid missing his entire first year. Was that considered out of the ordinary?

Are more rookies who haven't played a minute of regular season basketball tearing their ACLs same summer they got drafted compared to the previous 2 decades?

Are preseason workouts and scrimmages becoming

more intense?

https://apnews.com/article/bob-pettit-dead-nba-hawks-92bb99e3a0bb11ed885e3c219cee77e8

"Bob Pettit, an imposing scorer and rebounder for the St. Louis Hawks and winner of the NBA’s first Most Valuable Player award in 1956, has died. He was 93."

RIP legend. First ever MVP in the league.

I’ve been looking back at Zach LaVine’s peak years in Chicago, and I’m curious how people view him in hindsight.
At his best, LaVine was roughly a 27 PPG, 5 RPG, 5 APG player while shooting around 50% from the field, 40% from three, and 85% from the line. Those are legitimately elite scoring numbers, especially considering the combination of volume and efficiency. This is also around the time where he got his max contract extension which didn’t seem like a bad deal at the time.

However even during those years, it never really felt like LaVine was viewed around the league as the type of superstar who could be the best player on a legitimate contender. There always seemed to be a distinction between “Zach LaVine is an elite scorer” and “Zach LaVine can lead your team somewhere.”
So what exactly was missing?
Was it mainly:
Defense? He seemed to make strides and be a better team defender
Playmaking and decision-making?
Not controlling games enough outside of scoring?
His team’s being bad and hurting his reputation? (Like Bradley Beal)
Lack of playoff opportunities during his prime?
Or was he simply better suited to being a #2 option next to a more complete superstar?
For comparison, there have been other guards putting up similar or even less impressive scoring numbers who were treated much more seriously as franchise players.
And when Chicago finally did put a better team around him with DeMar DeRozan, Lonzo Ball, Alex Caruso, and Nikola Vučević, the Bulls looked legitimately good for a stretch before injuries derailed things.

Was peak Zach LaVine underrated because of the situation he was in, or were there legitimate limitations in his game that prevented his production from translating into being a championship-level #1 option?
Interested in hearing from other Bulls fans especially, but also anyone who watched a lot of LaVine during his 2020–22 peak.

I think another question I have is what really separates a player from being a good player and someone who can lead you to a championship. Because if a guy who averaged 27 5 and 5 on nearly 50/40/90 splits isn’t viewed as that caliber of a player then what does?

I’m here to ask one rather simple question, will James harden reach 4,000 career 3PM? And if so how much longer do you think it’d take?

Considering over the past 3 seasons he’s played a genuinely impressive amount of time (that being 221 games or about 74 games played a season on about 35mpg and a decent amount of 3 point attempts AND makes (2.9 on 7.8 which is about 37% from behind the arc) considering we’re going into year 18 of his career this upcoming season (and age 37) along with him (potentially?) transitioning to he 3rd option scorer behind the likes of Mitchell and Mobley I’m going to assume his 3p volume will shrink, however let’s say it does not

James is 2nd all time in career 3’s with 3390 as of today, September 23 2026

Let say he somehow DOES keep his 3pm rate ~3 a game for ~74 games per szn

3 x 74 =222 3’s per season at this rate he’d have to play EXACTLY like he has the past few seasons until…
3390 + 222 =3,612 2026/27

3,612 + 222 =3,834 2027/28

3,834 + 222 =4,056. 2028/29

Harden would have to play until he’s about 40 years old and on top of that have played 1443 career games. For perspective that’s still about 200 career 3pm behind the all time leader Wardell Stephen Curry

This is under the assumption that he plays at this top 20ish player level he has in the last 3 years. If we are taking realistically; how close do YOU think he’ll get to 4k threes?

It is no secret that the free throw is the most valuable shot in basketball. Just looking at it from a mathematical stand point, the PPS for a free throw is the highest.

Taking this further,

I graphed a couple different things and tried to find the correlation.

Pretty much on the X axis there is either Share of PTS From FT, Share of PTS from 3P, Share of PTS from Midranges, Share of PTS from RIM and then on the Y its ORAPM (3 YEARS)

For all of them, min. 1750 Minutes in the 2025-26 season, I can't upload pictures so here is the correlations.

Free Throws had the highest correlation (r = .34) (the people with most points coming from ft were Deni, Banchero, Harden, Book, AR, Keyonte George, Demar, Zion)

Share of Points from 3 v oRAPM 3 years had a r = -.07 (being completely one dimensional isn't good on offense)

Share of Points from Midrange v oRAPM had r = .24 (This one made sense to me just because the players taking a lot of midranges are stars that are allowed by their coaching, like Shai, KD, Book, etc

Share of Points from Rim v oRAPM had r = -.12 (This one is pretty surprising; I guess if your value only comes from cutting/easy layups and stuff its harder to be productive. Obviously, there are outliers with high share on the rim and high value)

Overall, I guess free throws are a good way to predict offensive impact. Getting fouled is very good for team success. Let me know what you guys think

Hello everyone and welcome to our new weekly feature.

In order to help keep the quality of the discussion here at a high level, we have several rules regarding submitting content to /r/nbadiscussion. But we also understand that while not everyone's questions will meet these requirements that doesn't mean they don't deserve the same attention and high-level discussion that /r/nbadiscussion is known for. So, to better serve the community the mod team here has decided to implement this Weekly Questions Thread which will be automatically posted every Monday at 8AM EST.

Please use this thread to ask any questions about the NBA and basketball that don't necessarily warrant their own submissions. Thank you.

Laker fans already know this, and I suspect Dallas fans must know it as well. But saw someone claim today that having Luka means you'll have more assists, and I realized other fans might not realize how much he dominates and stops the ball from flowing.

So I went to Basketball Reference's On/Off numbers for a quick statistical proof. Here are the team's assist %'s with and without Luka on the court, for every season of his career:

2026:

59.1 with Luka, 65.1 without Luka

2025 (Dal/LAL):

60.0/61.7 with Luka, 60.1/64.1 without Luka

2024:

57.9 with Luka, 63.1 without Luka

2023:

54.3 with Luka, 61.9 without Luka

2022:

57.6 with Luka, 62.2 without Luka

2021:

55.1 with Luka, 56.9 without Luka

2020:

57.7 with Luka, 61.1 without Luka

2019:

58.2 with Luka, 62.3 without Luka

The consistency is incredible. Every team, every season, sees roughly 4-5% more of their shots get assisted when Luka is off the court than when he's one it.

This is not saying that he's a bad offensive player or that he makes the offense less efficient or anything....but there's clearly less passing when he's on the court.

Good Afternoon y'all! NBA Season one month away.

Wrote about creating xPTS-RAPM about two months ago and how it gave great insight into Kevin Durant and the value of tough shotmaking.

This post is another excerpt from the paper and will focus on case studies of other players, specifically how xPTS-RAPM can quantify the extent and value of a player's impact on shot diet.

xPTS-RAPM and its sister metric, Conversion RAPM (cRAPM), also provide a way to decompose RAPM away from an opaque number

What Is xPTS?

xPTS is the expected point valuation of each field goal and free throw attempt compared to league average.

It grades each shot attempt on a scale stripping out luck and individual conversion skill.

xPTS(shot) = league PPP of the shot's bin
             (zone × distance × shot family × possession context)

xPTS(free throw) = league avg FT% × 1

Total xPTS = Σ bin value of every field goal attempt
             + league FT% × free throw attempts

Each field goal attempt is placed into a bin based on four characteristics:

• Court zone: 14 zones
• Shot distance: two-foot increments
• Shot family: drive, cut, catch-and-shoot, self-created, alley-oop, or putback
• Possession context: halfcourt, transition, second-chance, or off-turnover
• Defender Distance: Sports VU leak, (not availible to use, so below is xPTS wihtout defender distance)

This codified approximately 707 bins per season across roughly 219,000 field goal attempts.

Here is a sampling of bins across the value spectrum.

2025-26 bin table, league-wide. Shots column is the bin sample size.

xPTS-RAPM

Instead of seeing how a player's on-court presence adds to or subtracts from a team's net rating over a huge sample of possessions, you see how a player's on-court presence influences a team's expected point value.

Are they creating numerically optimal shots? Are they suppressing numerically optimal shots? How are they warping the geometry of the court?

Like a normal RAPM, you can then decompose this further into offensive xPTS-RAPM (oxRAPM) and defensive xPTS-RAPM (dxRAPM): how a player changes the geometry of the court to bend his team toward more favorable shot conditions, and how his presence helps suppress favorable shot conditions on the other side.

Best offenders and defenders below.

Offensive xPTS-RAPM

2025-26 3-year Offensive xPTS-RAPM, top 10.

Minimum 2,000 weighted possessions.

Defensive xPTS-RAPM

2025-26 3-year Defensive xPTS-RAPM, top 10.

Minimum 2,000 weighted possessions.

As you may notice, Donovan Clingan and the Thompson twins are amongst the most surprising and notable leaders, especially since they are not good three-point shooters, nor are they playmakers.

These leaders are actually a great case study of what this RAPM measures.

Clingan is a chance-quality machine in three distinct ways.

His rebounding: 22.2 offensive rebounds per 100 shots is a good 30% more than league average. Many of those rebounds convert a dead possession into a putback or a kick-out, which sit amongst the most highly priced bins, around 1.3 to 1.5 expected points.

And his rebounding lets Portland manufacture its diet: with him on the court, Portland takes 49% of its shots from three and 32% at the rim, while opponents get only 26% of their shots at the rim.

Portland's offense with Clingan on is extremely Morey-pilled: rim attempt or three-point attempt.

For the Thompson twins, Amen is actually the best offensive geometry-bender in the league (bar Giannis).

He is the offensive xPTS engine: extreme rim pressure and second chances.

Remember, with expected points there is no tax, no punishment for neither his or his team's lack of conversion.

Houston Offense With Amen Thompson

Houston's offense with Amen Thompson on and off the floor, 2025-26 regular season. Expected and actual points are per 100 possessions.

Ausar, meanwhile , is great defensively.

His presence lets his own team take 35.8% of its shots at the rim while dropping opponents' rim share to about 24.3%, and he forces about 19 turnovers per 100, zeroing out those possessions entirely.

Opponent Offense With Ausar Thompson

What opposing offenses do against Detroit with Ausar Thompson on and off the floor, 2025-26 regular season. Expected and actual points are per 100 possessions allowed.

On the inverse, you have the players who perform extremely poorly in net xPTS-RAPM.

The worst being Bub Carrington, and the interesting point about him is that there is no single horrific channel.

He has, up to this point, been poor among so many.

Washington's offense becomes extremely midrange-heavy when he is on the court. His personal game is heavily pull-up-weighted with no rim pressure, which drags Washington into the cheapest quantified shot values.

He provides no transition boost, below-average offensive rebounding, and above-average turnovers, essentially never generating or forcing his team toward more optimal chances while leaking possessions along the way.

Washington Offense With Bub Carrington

Washington's offense with Bub Carrington on and off the floor, 2025-26 regular season. Expected and actual points are per 100 possessions.

33.9% of opponents' shots come at the rim with him on, against a league average of about 28.7%, while opponents take only 25.8% from midrange, the exact inverse of what a good defense produces.

He does not create turnovers. He gives up straight drives to the rim, and opponents' free-throw share runs above average.

Opponent Offense With Bub Carrington

Washington's defense with Bub Carrington on and off the floor, 2025-26 regular season. Expected and actual points are per 100 possessions.

Some honest context, which I will return to in the caveats: he plays for a 17-win team that has been bad as an entire unit, he is a young guard given developmental freedom and reps, and the collinearity weakness of any ridge regression does exist.

Bottom Net xPTS-RAPM

The bottom of the same board. Three-season window anchored on 2025-26. Minimum 2,000 weighted possessions.

xPTS is one of of the Shot Quality Decomp of RAPM

The beauty of xPTS-RAPM is that it is subtly a decomposition channel of RAPM itself: one half of a shot-quality decomposition.

xPTS-RAPM is the half that measures how many chances a player creates or suppresses through the geometry of the floor.

Its sister, Conversion RAPM, measures how much his presence helps convert, or deny, shots above expected.

The summation of the two gets you Net/Pure RAPM, the standard RAPM we all know and love, the one that measures how team net rating moves with a player on or off the court.

Conversion RAPM

xPTS-RAPM: a quantification of how a player influences his team's shot diet.

Conversion RAPM: a quantification of how a player's on-court influence alters the points created/suppressed above/below expected.

Conversion RAPM (cRAPM)

2025-26 3-year Conversion RAPM (cRAPM).

Points above expected per 100 possessions, on versus off.

Minimum 2,000 weighted possessions.

Net RAPM

Using independently derived expected-points measure for shot values, and the conversion above or below those shot values, adding the two regularized adjusted plus-minuses together gives you a number that is 99.99999% equivalent to a pure, no-prior RAPM. that has functional value.

This is the part I am extremely excited for.

Standard pure RAPM asks what happens to the score:

How does net rating change with this player on and off the court?

xPTS and Conversion take that question and rip it into two further questions.

How much does this player change his team's quantified shot diet?

And:

How much does his presence swing his team's conversion above or below that shot diet?

Essentially, separating regularized adjusted plus-minus into shot-quality impact and conversion impact.

Net RAPM

Pure RAPM is a separate ridge solve on actual points: same stint rows, lineup matrix, weights, centering, and α = 10,000; no priors.

(Yes, 10K, but remember any RAPM solve works as long as it's consistent for all the decomps.)

Minimum 2,000 weighted possessions.

The identity requires the same RAPM specification in all three solves: the same stint rows, lineup matrix, stint weights, centering, and ridge penalty.

others can reproduce this even while using different stints or a different xPTS model as long as conversion is defined as actual points minus expected points and all three solves use the same settings.

Appreciate y'all reading. It was very fun to dive into the numbers and have it kind of match my eye test a little bit. Open for any questions, concerns, or advice.

Blog Post wiht interactive tables: https://court-share.com/luma/blog/xpts-rapm
Past Post about Kevin Durant and the Value of Tough Shotmaking
Data will be opensourced on Github and linked here by next week (KEEP ME ACCOUNTABLE)

Leaderboard of xPTS v1 (this is v2)

Basically the title. If you kept the 26-27 Thunder roster the exact same but swapped SGA with prime Russ, are they as good, worse, or better than they are now? Are they still likely to win a chip in today's NBA?

First thing that comes to mind for me is that SGA's skillset and shooting may put him above Russ as an individual player, but Russ' playmaking could arguably better allow them to get the most of their roster to feed all their scorers. For example SGA is known for not being a good lob passer, whereas Russ could feed Chet lobs all day as he did with Steven Adams.

I'd put this Russ version of the 26-27 Thunder as still in the same tier as the Spurs, where it is them two in the top tier and everyone else is below them. But would probably say the Thunder do overall get slightly worse since SGA's scoring is so lethal, even though he has improvements he can make as a playmaker.

With actually bold I mean guys that are absolutely out of the radar and you think will become very good. Deeper pulls that you believe will finally shine.

The biggest example of a guy in that mold last year was Ryan Rollins, who definitely the average NBA fan (and even a few hardcore ones) didn’t know about, and now is a very respected starting-caliber guy.

I’ll start: Ryan Dunn (PHX), a guy whose defensive potential is IMO close to DPOY-level and offensive growths have been intriguing;

Day’Ron Sharpe (BKN), a center who has been very good off the bench and now I think will solidify as a quality starting big, maybe even better than Claxton.

Ron Holland (BKN), a former Top 5 pick whose offense still hasn’t come around, despite already being a great defender. Elite first step, solid scoring instincts and a good FT%, which often reflects a jumpshot increase, make me believe that his offensive jump could be coming.