This is the fourth annual NBA Player Tiers project, in which Seth Partnow names the top 125 players in the league after each season and then separates them into five distinct categories of value, each with their own sub-categories to further delineate them. These are not meant to be read as firm 1-125 player rankings. Rather, they’re meant to separate solid starters from the very best superstars, and every level in between. This is how NBA front offices assess player value across the league when building their teams.
Previous NBA Player Tiers: ’20 | ’21 | ’22 | ’23: Tier 5
Near the higher end of the talent spectrum, small increases in player ability tend to lead to large changes in impact toward playoff success and ultimately championship viability. While “Tier 5” level production provides some incremental help in that regard, my past research suggests Tier 4 is where the real value starts to kick in:
Tier 5 players are nice and can be just the type of guys who push a team over the top in a close playoff series, but a team has to have enough Top 75-ish talent for those small bonuses to even matter.
This season, Tier 4 consists of 41 players, broken into three sub-tiers.
Tier 4C: 67-80
Impact role players
Marcus Smart, Bruce Brown, Kentavious Caldwell-Pope, Alex Caruso
I’m sure it’s possible for a playoff team to have too many capable, positionally versatile defenders who aren’t offensive liabilities. But I don’t think I’ve seen that roster in practice, and this group illustrates why. Smaller guys who can guard (to a point) bigger players and have some combination of shooting and on-ball playmaking prove themselves time and again in the postseason. Things might not work great if they are asked to take on more expansive offensive roles, but that’s why these players are here and not slightly higher.
Youths
Cade Cunningham, Josh Giddey, Jalen Williams, Keegan Murray
Giddey and Williams are primed to be key parts of what might be a breakout year for Oklahoma City. Though I probably would have voted for Paolo Banchero if I had a Rookie of the Year ballot, Williams was my “hipster pick” because of his size, versatile skill set and physical readiness to handle the NBA game. As the Thunder improve, Giddey probably needs to prove himself a little more as a shooter to keep progressing as a player, as with all the other talent they have added offensively, he probably won’t have the ball enough for just his playmaking to be sufficient.
Murray was last year’s winner of the “One Rookie per Year Will Have a Positive Impact on a Playoff Team” award. The Kings experimented with him taking on more of an initiation role in his brief summer-league stint, and it will be worth watching to see if he remains in the well-defined 3-and-D-type slot in which they used him last season.
As for Cunningham, I just want to see him get an injury-free run of games with teammates who can competently space the floor and move off the ball. I’m not sure that’s likely to happen in Detroit any time soon, but one can hope.
Numbers over impact
Jerami Grant, Tyler Herro, Bojan Bogdanović, Zach LaVine, Deandre Ayton, John Collins
In general, I’m less enamored with guys who profile as moderately efficient scorers without offering much else. While this doesn’t perfectly fit this group of players — especially in the case of LaVine, who possibly deserves to be higher, but four playoff games in nine years, the last five of which have seen him operate as a primary option, certainly raise questions about his overall impact — it doesn’t not do so. If there is another commonality here, it’s questionable defense, though neither Grant nor Ayton is awful on that end.
I mentioned in the Tier 5/Intro installment that, while the tiers are meant to be as contract agnostic as possible, this is the group for which it becomes most difficult to completely ignore cap implications, as “Yay, Points!” players tend to get paid too much to be easily fit into roles where they might most help a title team.
Would LaVine be a difference-maker as a third/fourth option on a top team? Maybe? Probably? But unlike an Andrew Wiggins or Aaron Gordon, we haven’t seen it. And given his salary, we are unlikely to do so, and I’d rather someone else pay to find out if he can.
Victor Wembanyama breaks the mold. (Brian Babineau / NBAE via Getty Images)
Tier 4B: 55-66
‘The One’
Let’s get this out of the way: In the (public) history of the tiers project, I’ve never included a rookie in the Top 125. There are two main, interrelated reasons.
The first one is that rookies are almost always bad. I don’t mean in terms of being underskilled or undertalented. Rather, the speed and precision of the NBA means they make a lot of mistakes, especially on defense. And those mistakes add up quickly.
The second point is that, for even the most highly touted first-year prospect, there is a degree of “prove it” in terms of competitiveness against NBA size and athleticism. Much in the same way as the college one-and-done role has helped to diffuse some of the hype over guys who had marvelous prep or AAU careers built on a physical superiority that disappeared once they reached NCAA play, there is a finding-out period in terms of where a player’s positional size and athleticism really fit against the world’s best.
Had I been doing this exercise a little longer, the most recent player who would have challenged the “no rookies” rule would have been Luka Dončić, simply because he had done a lot more “proving it” against professional adults than would be possible for any college prospect. And all due respect to Dončić, who I had as easily the best prospect that year, but Victor Wembanyama is on another level coming into the league.
I don’t want to re-litigate where Wembanyama ranks among prospects over the last several decades, other than to say that where he stands relative to guys like LeBron James, Shaquille O’Neal and Tim Duncan, being even a reasonable discussion in that regard illustrates the point that he’s in no way a “normal” first overall pick.
Beyond that, the pathway to Wembanyama finding ways to make an impact even as he susses out the intricacies of the NBA game is pretty wide. His combination of size, movement skills and motor suggest he’ll be a defensive playmaker from day one. Even with plenty of questions still to answer about how he ultimately projects on offense, I think that gets him to Top 75-ish level out of the box.
B-plus bigs
Brook Lopez, Myles Turner, Nic Claxton, Jarrett Allen, Karl-Anthony Towns
It’s a weird time to be a big man in the NBA.
The last few seasons have seen the reversal of a previous trend. Of the first 28 MVPs awarded, 25 went to fours or fives through Moses Malone winning in 1982-83. Over the next 25 seasons, 10 bigs took home the hardware. However, the previous five have been split between Giannis Antetokounmpo, Nikola Jokić and Joel Embiid. It is still possible for bigs to dominate at the very top levels.
But what has declined is the perceived value of the sub-elite big.
The importance for floor spacing, the rise of switching and the increased ability of teams to hunt mismatches in the form of “one-position” defenders has made playing two bigs a relative rarity, with pure “five-out” systems getting plenty of looks as well.
The result is that all but the very best bigs become sometimes food. The idea of “playing rim-protector X off the floor” is something we hear every postseason, and while the degree to which this actually happens tends to be overstated, there will be matchups that are challenging for big men.
For the very, very best, they give enough in other areas where it’s usually best to live with some of their matchup disadvantages. But get to the next level or two down, their value needs to encompass the fact that they are much more likely to play 25 than 35 minutes in a competitive playoff game. They might be 25 good minutes, but that’s role player territory, not quite the level of Tier 3-plus stars.
B-plus guards
Austin Reaves, Fred VanVleet, Tyrese Maxey, Dejounte Murray
The NBA is awash with backcourt talent right now. The flipside of there being so many good playmakers is that the level of competition is always high, especially in the postseason. This is a group that can compete with many of the best backcourt players in the league, but the goal is playing to a draw rather than expecting to create an edge.
Is this damning with faint praise? Perhaps. But depending on how we define positions, there are about 25 guards ahead of this group, so putting them in the Top 60 to 70 is simply math.
Grab bag
• Franz Wagner could easily jump a sub-tier, if not more, this coming season. He has the makings of an elite role player between his shooting, playmaking and positional versatility. But that playmaking and creative juice on the ball leave open the possibility of crossing the “role player barrier” between Tiers 4 and 3. If the Magic take a big step forward into playoffs, Wagner’s continued improvement is likely to be a big reason why.
• Julius Randle is perhaps the best illustration of the differences between regular-season accumulation and impactful postseason play in the NBA. His high-volume, decent-efficiency skill set has proven extremely useful in two of the last three seasons. Combine this with Thibs-ian minute loads, and he has created tons of regular-season wins. But in the playoffs, the diet of tough isolation shots has caught up with him. Over the past three regular seasons and two accompanying playoff runs, he has held steady at 29.2 percent usage, but his 55.4 percent true shooting in the regular season (which incorporates 2021-22’s disastrous 50.9 percent) has fallen off a cliff to 46.2 percent across the two playoff runs.
This is the very definition of a floor-raising but ceiling-limiting profile, a player type who is exceptionally hard to value through the prism of championship contention, as getting to the playoffs is the first step in winning a title, and having a regular-season innings-eater or two can help a team get to the postseason without overly taxing its top players.
But building with or around such players is difficult, both because of the need to move away from their preferred style once the playoffs start and, more importantly, because players of this nature get paid handsomely for that regular-season accumulation. It’s simply not realistic to expect to be able to afford a championship roster knowing that a near-max-making regular-season workhorse is going to have to take a much smaller role if a team has designs on deep playoff runs.
Tier 4A: 40-54
A-plus role players
Aaron Gordon, Andrew Wiggins, O.G. Anunoby, Derrick White
If one were to name three traits that define what it means to be a top role player in today’s NBA — the sort of player who can make a massive positive impact in just about any roster situation — they would be: elite defense, positional versatility and very good offensive output in a tertiary role. I’m not sure I need to do more to describe this group other than to say the “tertiary role” tends to be the bit that separates the very top of Tier 4 from breaking the “role player barrier” into Tier 3.
While Anunoby and White have never been asked to step into a primary offensive role full time, I would question their ability to do so and maintain efficiency in much the same way that we’ve seen Gordon and Wiggins be miscast as offensive engines before finding their niche as cutters, rim runners, offensive rebounders and spot-up shooters, anything but primary creators. As a combo guard, White gets more on-ball reps than the other three but at not quite the level of the established star guards in Tiers 3 and up.
Small guards
Chris Paul, CJ McCollum, Darius Garland
For as much as the NBA game has changed over the past two decades, placing more emphasis on speed and skill than on size and strength, the level of physicality in the playoffs remains immense. One of the ways this manifests is the willingness of offenses to hunt out the more diminutive of opposing backcourt players and relentlessly run actions at them. Whether it’s an endless series of crunching ball screens or working to get the little guys switched onto the big ballhandling wings who star for many top contenders, these types of players have targets on their backs.
Some of these players are good enough that the trade between their own offensive output and the defensive liabilities is still favorable, but those are the Currys, Morants and Lillards, which occupy the higher tiers. For many years, Paul was up among them, but the age-related decline in his offensive tools has become apparent over the last few postseasons. Garland’s first playoff run had its ups and downs, with plenty more chances for him to tip the matchup balance back in his favor over the coming years. McCollum has had his postseason moments but has largely been less effective than in regular seasons with the higher overall caliber of postseason defenders able to limit his off-the-dribble, midrange and floater game.
Elite shooters
Michael Porter Jr., Desmond Bane, Kristaps Porziņģis
In NBA circles, there is a distinct opponent prep and player evaluation when it comes to players whose primary skill is the ability to space the floor. There are “threats,” and there are “weapons.”
A threat is simply a player who shoots it well enough that he needs to be guarded and accounted for. A weapon is someone you gear your defense toward limiting their shot attempts as a high priority. The key differentiators between the two are of course shooting accuracy, but more important is shooting versatility.
A great standstill shooter can be defended by shutting off his catches, usually by improving point of attack defense. A player who can shoot on the move, off the dribble or over a contest requires a bit more planning and forethought. Plenty of players lower down or off the tiers completely might qualify as “weapons,” but these three in particular combine that shooting ability with something a little more special that allows them to be more than simply shooting specialists. Whether it’s Bane’s playmaking and off-the-dribble creation, Porter’s ability to take and make shots over even tight coverage or Porziņģis’ rim protection, those “extras” are the sort of additional skills that can often make a difference between teams at the top end.
In 2023, Paolo Banchero was the third player in Magic franchise history to be named Rookie of the Year. (Rich Storry / USA Today)
High hopes
Evan Mobley, Paolo Banchero
Two of the teams that appear poised to take a run at ascending into the elite of the Eastern Conference are so poised because of the potential for improvement from their young stars.
Banchero has the more straightforward path. He wasn’t particularly efficient as a rookie, weighed down by his sub-30 percent from deep, but simply being able to carry high-20s usage without being an utter disaster illustrates his potential to grow into an offensive hub. That he is one of only 12 rookies — and six non-centers — to average at least 10 FTA/100 possessions in their first year further shows that he already knows how to create advantages for himself. The easiest route to becoming a top star is to be a high-usage, high-efficiency big wing, preferably with some playmaking chops; Banchero averaged 3.7 assists per game, showing potential in that area as well. He still has to improve a great deal to become that elite offensive engine, but the road is straight, even if it climbs up a steep hill.
Mobley is a more interesting case. The Cavs’ acquisition of Donovan Mitchell got in the way of him taking on an expanded offensive role in his second season. Between Mitchell, Garland and Caris LeVert off the bench, there weren’t a lot of extra on-ball reps to go around. But Mobley did see a large jump in efficiency while having similar offensive volume in Year 1, and combining that improvement with his out-of-the-box excellent-bordering-on-elite defensive impact gives you a damn good player. In the top range of the tiers, there are a few spots occupied by bigs who balance their moderate offensive loads with elite interior defense, and that is certainly a path open to Mobley, though he probably needs to become more able to play a decent share of his minutes at the five for that route to be open. Alternatively, continued development of his offensive game, either in terms of being able to reliably create for himself or becoming a willing and reliable 3-point shooter and floor spacer, gives him an alternative road up the Tiers.
Hard to build around
Brandon Ingram, Domantas Sabonis
Even before the Kings’ first-round matchup against the Warriors, Sabonis’ potential playoff limitations were well-known, but Golden State was just about the worst opponent for him. The Dubs were perhaps uniquely prepared to exploit his weaknesses on both ends of the floor, and his relative ineffectiveness across the series is a harsh memory on which to leave his season. That ending shouldn’t obscure the degree to which Sabonis keyed Sacramento’s run to the Western Conference’s third seed in the first place. In many ways, he is the gold-plated version of a player like Julius Randle, a borderline elite floor raiser. But try to imagine what a roster featuring him as the best or second-best player would have to look like to be a genuine title threat, and I’m not sure you can do it.
On the other hand, Ingram is very much the right player type to be higher up the list. He just isn’t quite good enough at those “big wing” things to actually get there. There are 11 ballhandling wing players in Tiers 1-3, give or take. According to NBA Shot Charts 3-year RAPM, nine have been more impactful than Ingram over that period. The two finishing lower are the playoff-proven Khris Middleton — though as I’ll discuss when we get to him, Middleton used up his single-year injury “mulligan” last season — and the rapidly ascending Anthony Edwards.
Relative to those in the tiers above, Ingram is much worse defensively, not quite as efficient offensively, not quite effective enough as a playmaker and has frequently struggled to integrate his game with top-level teammates, most notably Zion Williamson. Ingram received a lot of credit for New Orleans’ spirited loss to Phoenix in the 2022 playoffs, but it’s fair to say that considering how the Suns deconstructed over the following year, some of the shine is off that performance for both Ingram and the Pelicans in general.
The good news for Ingram is that he is young enough (he turns 26 in September), and the Pels roster should be good enough that, unlike with Sabonis (for whom we know how the movie is likely to end), Ingram will have several more chances to prove me wrong and show that he is good enough to be the driving force behind a top-level team.
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Tier 4
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$40.2/$32.1/$24.1
23
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$27.4/$21.9/$16.4
89
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$30.6/$24.5/$18.4
65
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$32.3/$25.8/$19.3
55
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$32.2/$25.8/$19.3
56
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$23.2/$18.5/$13.9
120
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$35.5/$28.4/$21.3
40
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$39.7/$31.7/$23.8
26
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$36.0/$28.8/$21.6
39
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$29.2/$23.3/$17.5
78
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$33.0/$26.4/$19.8
49
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$37.3/$29.8/$22.4
32
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$37.9/$30.3/$22.7
30
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$44.7/$35.7/$26.8
15
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$14.5/$11.6/$8.7
244
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$39.8/$31.8/$23.9
25
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$39.2/$31.4/$23.5
28
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$36.5/$29.2/$21.9
36
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$29.9/$23.9/$17.9
70
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$18.6/$14.9/$11.2
179
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$33.6/$26.9/$20.1
47
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$33.0/$26.4/$19.8
52
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$30.2/$24.2/$18.1
68
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$36.0/$28.8/$21.6
37
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$33.0/$26.4/$19.8
51
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$27.3/$21.8/$16.4
90
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$34.1/$27.3/$20.5
46
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$32.7/$26.2/$19.6
54
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$22.6/$18.1/$13.5
129
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$25.9/$20.7/$15.5
100
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$24.2/$19.3/$14.5
111
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$20.8/$16.6/$12.4
154
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$18.2/$14.6/$10.9
186
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$9.9/$7.9/$5.9
328
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$25.5/$20.4/$15.3
102
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$23.4/$18.7/$14.0
118
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$37.1/$29.6/$22.2
34
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$16.8/$13.5/$10.1
209
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$18.1/$14.5/$10.9
188
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$17.2/$13.8/$10.3
200
(2500/2000/1500 min. played)
Million
Tier 5
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$23.1/$18.5/$13.8
124
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$28.0/$22.4/$16.8
83
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$21.3/$17.0/$12.7
149
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$28.0/$22.4/$16.8
84
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$24.8/$19.9/$14.9
107
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$25.3/$20.3/$15.2
104
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$24.0/$19.2/$14.4
114
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$31.7/$25.4/$19.0
59
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$14.5/$11.6/$8.7
243
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$16.9/$13.5/$10.1
207
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$19.3/$15.5/$11.6
173
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$30.5/$24.4/$18.3
67
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$21.2/$16.9/$12.7
152
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$40.5/$32.4/$24.3
21
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$16.5/$13.2/$9.9
217
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$16.1/$12.8/$9.6
222
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$36.5/$29.2/$21.9
35
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$29.2/$23.3/$17.5
79
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$18.8/$15.0/$11.2
176
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$22.5/$18.0/$13.5
131
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$25.3/$20.2/$15.1
106
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$37.6/$30.0/$22.5
31
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$26.3/$21.0/$15.8
96
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$7.9/$6.3/$4.7
357
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$21.3/$17.0/$12.7
148
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$22.2/$17.8/$13.3
134
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$28.9/$23.1/$17.3
81
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$34.1/$27.3/$20.5
45
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$9.9/$7.9/$5.9
330
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$27.8/$22.2/$16.7
85
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$24.0/$19.2/$14.4
115
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$20.7/$16.5/$12.4
157
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$14.8/$11.9/$8.9
242
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$16.6/$13.2/$9.9
215
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$9.8/$7.8/$5.8
334
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$26.7/$21.4/$16.0
93
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$15.6/$12.4/$9.3
230
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$31.1/$24.8/$18.6
62
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$23.0/$18.4/$13.8
125
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$18.3/$14.7/$11.0
182
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$9.9/$7.9/$5.9
327
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$34.8/$27.8/$20.9
42
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$17.1/$13.7/$10.3
204
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$6.7/$5.4/$4.0
379
(2500/2000/1500 min. played)
Million
3-yr Avg. Estimated +/-
per 100 possessions
3-yr Regularized Adjusted +/-
per 100 possessions
Prod. Value Est.
$15.1/$12.1/$9.0
236
(2500/2000/1500 min. played)
Million
About this story: Edited by Rob Peterson. Development by Marc Mazzoni. Design by Drew Jordan. Design direction by Amy Cavenaile and Ray Orr. Support and production by Brooks Varni.
(Illustration: John Bradford / The Athletic; Photos: Christian Petersen, Ethan Miller / Getty Images)
