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35,492 NBA and 6,469 WNBA games

Did NBA offenses become solar systems?

"Heliocentrism" is the idea that modern NBA offenses orbit one star who creates most of the scoring, while the WNBA stayed more egalitarian. This study tests both halves of that idea on every regular-season game the play-by-play covers: 35,492 NBA games from 1996-97 to 2025-26 and 6,469 WNBA games from 1997 to 2026, with 1,838,338 assisted baskets. The short answer: the typical NBA team spreads its scoring slightly more than it did thirty years ago, not less; the WNBA has not changed measurably; and 2026 is the only one of the 30 seasons compared in which the WNBA was clearly the more concentrated league.

NBA top creator, per game
31.5% to 30.5%
First five seasons against the last five: a change of -1.0 point (95% interval -1.9 to -0.1).
WNBA top creator, per game
31.0% to 31.5%
A change of +0.4 points (95% interval -0.8 to +1.7): no measurable shift.
2026 league gap
-3.0 points
NBA 2025-26 minus WNBA 2026 (95% interval -5.3 to -0.6): the WNBA's top creators carried more.
Season totals overstate
-3.9 vs -1.0
The NBA's fall in points on season totals, against the per-game measure that removes missed games.
The question

Crediting every basket to the player who created it

The play-by-play records one thing about who set up a basket: on an assisted make, the passer. So every made field goal is credited to one creator, the passer when it was assisted and the shooter when it was not, weighted by the shot's points. For each team the study then measures the top creator's share of the points created, the top two creators' share, and the effective number of creators (1 divided by the sum of squared shares, which weighs the large shares and barely moves for a bench player with two assists).

The primary measures are computed within each game and averaged over a team's games. That choice came from the first pass: on season totals, a star who misses games lowers the share even if the offense runs through them every night they play. Both versions are reported. Eras are compared by the first five seasons against the last five, with 95% Welch intervals for the change; season means carry 95% t intervals across teams.

How a basket is credited and how one game's credit becomes shares1. Credit each made basket to one creatorAssisted makeA. Edwards makes a three,assisted by J. McDaniels+3 points to J. McDaniels, the passerUnassisted makeR. Gobert makes a two,with no assist recorded+2 points to R. Gobert, the shooter2. Add up one game: MIN at MIA, January 3, 2026own unassisted makesassists to teammatesA. Edwards27 (26.2%)J. Randle20 (19.4%)D. DiVincenzo15 (14.6%)N. Reid10 (9.7%)J. McDaniels10 (9.7%)B. Hyland9 (8.7%)M. Conley6 (5.8%)R. Gobert6 (5.8%)Created points in the game: 103Top creator's share27 / 103 = 26.2%Effective number of creators1 / sum of squared shares1 / 0.161 = 6.21equal creators would give thesame concentration3. Repeat for every game. A team's measure is the average over its games, and a season'sleague value is the average over its teams.
How a basket is credited and how one game's credit becomes shares1. Credit each made basket to one creatorAssisted makeA. Edwards makes a three,assisted by J. McDaniels+3 points to J. McDaniels, the passerUnassisted makeR. Gobert makes a two,with no assist recorded+2 points to R. Gobert, the shooter2. Add up one game: MIN at MIA,January 3, 2026own unassisted makesassists to teammatesA. Edwards27 (26.2%)J. Randle20 (19.4%)D. DiVincenzo15 (14.6%)N. Reid10 (9.7%)J. McDaniels10 (9.7%)B. Hyland9 (8.7%)M. Conley6 (5.8%)R. Gobert6 (5.8%)Created points in the game: 103Top creator's share27 / 103 = 26.2%Effective number of creators1 / sum of squared shares1 / 0.161 = 6.21equal creators would give the sameconcentration3. Repeat for every game. A team's measure isthe average over its games, and a season'sleague value is the average over its teams.
The crediting rule on a real Minnesota game from the 2025-26 season. The assisted three counts for the passer, not the shooter; the unassisted putback counts for the shooter. Adding up the game gives each player's share, the top creator's share, and the effective number of creators, and every measure in this study starts from that arithmetic.

Passers are matched to players by name within the shooter's team and game, in three passes, each accepted only when it finds exactly one player. At least 99.8% of assisted baskets resolve in every season, and 993 (0.05%) are left out. Parsed team assists equal the league's game logs in at least 99.7% of team-games in every season except WNBA 1997 (92.1%) and WNBA 1998 (94.2%), and made field goals match in at least 99.9%. Every table was computed in Python and again in R from the same events, and the two agree on every cell.

The NBA

The typical NBA offense spread out slightly

Over 1996-97 to 2000-01, the average NBA team's top creator accounted for 31.5% of its created points in a game. Over 2021-22 to 2025-26 it was 30.5%, a change of -1.0 point with a 95% interval of -1.9 to -0.1. The effective number of creators per game rose from 5.32 to 5.53 (+0.21, interval +0.08 to +0.34). The most recent season, 2025-26, was the least concentrated NBA season of the 30, at 29.1% (27.8% to 30.5%).

The top creator's share of a team's created points per game, averaged across teams. The NBA carries its 95% band, and the dashed segments are its first-five and last-five season means. The NBA line drifts down after the late 2000s and ends at its lowest season; the light WNBA line, shown for reference, moves around a flat level.

A hinge fit on the season means puts the NBA's turn in 2008, but its approximate 95% set runs from 2005 to 2022. The data date a slow drift, not a moment when the league changed.

Season totals

Counting by season overstates the decline nearly four times over

On season totals the NBA's top creator share fell from 25.9% to 22.0%, a change of -3.9 points (95% interval -5.3 to -2.5), and the effective number of creators rose from 7.32 to 8.87. That reads like a league moving away from stars. Per game, the change is -1.0 point. The difference is what a rise in games missed by top players would produce, though games played were not measured here, so that cause is unverified. Any usage or concentration claim built on season totals mixes availability into it.

Why season totals overstate the declineIllustrationa made-up team, 10 games123out456out7out8910star: 30 of 100 points when playingteammate: 15, or 25 when the star is outTop share in each game, averaged:28.5%Star's share of season totals:21.0%Same star, same role every night; only the missedgames pull the season-total share down.The real NBA change1996-97 to 2000-01 against2021-22 to 2025-26, in pointsSeason totals-3.995% interval -5.3 to -2.5Per game-1.095% interval -1.9 to -0.10
Why season totals overstate the declineIllustrationa made-up team, 10 games123out456out7out8910star: 30 of 100 points when playingteammate: 15, or 25 when the star is outTop share in each game, averaged:28.5%Star's share of season totals:21.0%Same star, same role every night; only the missedgames pull the season-total share down.The real NBA change1996-97 to 2000-01 against 2021-22 to 2025-26,in pointsSeason totals-3.995% interval -5.3 to -2.5Per game-1.095% interval -1.9 to -0.10
Left, an illustration with a made-up team: the star's role is the same in every game played, yet the season-total share comes out well below the per-game average, because the games the star missed count in the denominator. Right, the real NBA change from the first five seasons to the last five, measured both ways, with 95% intervals.

The same gap runs through every season, not only the two eras compared.

The NBA's top creator share by season, per game (blue) and on season totals (grey, dotted), with 95% bands. The season-total line sits lower and falls further.
League against league

The WNBA is now the more concentrated league

Season by season, the NBA's per-game top creator share was higher than the WNBA's, with an interval excluding zero, in 5 of 30 seasons (WNBA years 2001, 2006, 2007, 2009, and 2016). The WNBA's was higher in one: 2026, where the gap was -3.0 points (-5.3 to -0.6), the NBA's 29.1% against the WNBA's 32.1%. In most seasons the two leagues cannot be told apart.

NBA minus WNBA in the per-game top creator share, each WNBA season paired with the NBA season ending that year, with a 95% Welch band. Blue points are seasons where the NBA was clearly more concentrated, grey points are seasons the two leagues cannot be told apart, and the one orange point, 2026, is the season the WNBA was clearly more concentrated.

Both leagues assist more of their baskets than they did, which spreads creation by how it is counted. The NBA's assisted share rose from 60.9% to 62.3% (+1.4 points, interval +0.4 to +2.3), and the WNBA's from 62.4% to 67.4% (+4.9, interval +3.5 to +6.4). Part of the NBA's per-game fall is this counting effect, not only a change in who has the ball.

Share of made field goals that were assisted, by season, with 95% bands. Both leagues rise, the WNBA by more. More assists spread credit away from the scorer by construction, which ties this rise to the NBA's per-game fall above.
The stars

Heliocentric teams exist; a heliocentric league does not

Individual team-seasons do orbit one player. On season totals, the 2008-09 Hornets ran 47.9% of their created points through Chris Paul, and the 2016-17 Thunder 46.8% through Russell Westbrook. Against their own league and season, the standouts include Trae Young's 2021-22 Hawks (39.1%, 2.84 standard deviations above that season's teams) and Luka Doncic's 2023-24 Mavericks (37.4%, 2.62). In the WNBA, Courtney Vandersloot's 2020 Sky (39.6%) and Caitlin Clark's 2024 Fever (39.5%) top the list. These teams are outliers in their seasons. The league averages show the typical NBA team did not follow them.

Two teams' creators as shares of their created pointsEach bar is one team's created points for a season;each segment is one player's shareNOH 2008-09The most concentrated NBA team-seasonC. Paul 47.9%next: D. West 14.8%Effectivecreators3.7of 15 playersMIN 2025-26The typical 2025-26 NBA team (median top share)J. Randle 19.7%next: A. Edwards 16.9%Effectivecreators9.0of 21 players
Two teams' creators as shares of their created pointsEach bar is one team's created points for a season;each segment is one player's shareNOH 2008-09The most concentrated NBA team-seasonC. Paul 47.9%next: D. West 14.8%15 players created points;effective creators 3.7MIN 2025-26The typical 2025-26 NBA team (median top share)J. Randle 19.7%next: A. Edwards 16.9%21 players created points;effective creators 9.0
The 2008-09 Hornets beside the typical 2025-26 NBA team (Minnesota, the median of that season's top creator shares), each bar split into every player's share of the season's created points. Chris Paul's segment is nearly half the Hornets' bar; Minnesota's is about a fifth, and its credit is spread across more players.

Set against every team-season, those standouts sit far above their leagues in every era, while the league means stay flat or drift down.

Every team-season's top creator share on season totals (NBA blue, WNBA orange), the two league means, and the six teams named above. Teams above the cloud appear in the late 1990s and in every decade since; the league mean never rises toward them.
Limits

What this does not show

An assist credits only the last pass. A drive and kick credits the player who kicked, and the pass before it is invisible, so creation by primary ball handlers is undercounted, and a rise in assists spreads creation by construction. Assists are also a scorekeeper's judgment that varies by arena and era, which this study does not adjust for. Free throws carry no assist in the feed and are left out, so a star who draws fouls creates more than these shares show. The study covers the regular season only, and team-seasons from one franchise inside a five-season block are treated as independent, so the era intervals are somewhat narrow. Passers are matched by name text, and a confident wrong match is possible where two teammates share it, though the matcher refuses any name that fits more than one player.

Method, code, and verification

The full technical write-up (data provenance, model specification, validation gates, and stated limitations) is the README. The analysis is implemented independently in R and Python and reconciled to numeric tolerance; run_checks.sh replays every gate.