NBA Post All-Star Break Usage Winners and Losers – Real vs Fake Breakouts

NBA post all star break usage winners losers is one of the clearest ways to evaluate how roles shift across the league, as the All-Star break consistently marks a turning point in every season. From this point, teams tend to split into two distinct paths – competitive teams tightening rotations for wins, and tanking teams expanding roles to evaluate young talent. In this article, we break down the key usage winners and losers from both sides.

NBA Post All Star Break Usage Winners

Player Pre ASB USG Post ASB USG Δ USG Pre ASB MPG Post ASB MPG Δ MPG
Matas Buzelis (CHI) 21.2 24.7 +3.5 28.3 31.5 +3.2
Cooper Flagg (DAL) 24.7 30.5 +5.8 34.1 32.1 -2.0
Maxime Raynaud (SAC) 16.5 19.7 +3.2 23.5 32.2 +8.7
Kyle Filipowski (UTA) 18.0 23.3 +5.3 22.1 26.6 +4.5
Bilal Coulibaly (WAS) 16.9 23.0 +6.1 26.8 25.4 -1.4
Isaiah Collier (UTA) 18.5 28.4 +9.9 25.5 26.5 +1.0
Jalen Suggs (ORL) 22.5 21.5 -1.0 26.7 28.9 +2.2
Devin Vassell (SAS) 18.3 16.3 -2.0 30.8 30.0 -0.8

Post All-Star break deltas are calculated using pre vs post ASB splits.

Isaiah Collier, Kyle Filipowski and Bilal Coulibaly stand out as context-driven spikes rather than true role growth. Their post All-Star break usage increases come in stretched rotations and non-competitive environments, making these jumps less likely to fully carry over.

The rest of the group profiles much cleaner. Their usage growth is tied to more stable roles, giving them a stronger chance to translate these gains into next season.

Matas Buzelis (CHI)
USG Δ
+3.5
role expansion
Minutes Δ
+3.2
stable increase
Shot Volume
+3.6 FGA
Efficiency
~
TS neutral
Cooper Flagg (DAL)
USG Δ
+5.8
primary creator shift
Minutes Δ
~+2
stable role
Shot Volume
+3.1 FGA
Efficiency
TS -3.7
Maxime Raynaud (SAC)
USG Δ
+3.2
expanded role
Minutes Δ
+8.7
rotation jump
Shot Volume
+4.4 FGA
Efficiency
+
TS +5.4
Jalen Suggs (ORL)
USG Δ
+2.5
secondary growth
Minutes Δ
~+2
steady role
Efficiency
+
TS ~+2
Role Type
2nd
not primary usage
Devin Vassell (SAS)
USG Δ
+2.1
minor increase
Minutes Δ
~
flat role
Efficiency
+
TS ~+1
Signal
low
limited change

Matas Buzelis, Cooper Flagg and Maxime Raynaud stand out as the most meaningful usage risers once context is accounted for, but for different reasons. Buzelis benefits from a full organizational reset in Chicago, where a shift in leadership and roster direction has created a clear runway for him to grow into a central role. Flagg, on the other hand, has already proven he can handle that responsibility, with his second-half usage spike reflecting a real offensive takeover rather than a temporary adjustment. Raynaud sits somewhere in between – his jump was driven by Sacramento’s late-season context, but with potential roster changes ahead, there is a realistic path for that role to persist.

Jalen Suggs and Devin Vassell profile as more stable contributors than true breakout cases. Suggs continues to deliver strong two-way impact and remains a key piece regardless of how Orlando reshapes the roster, while Vassell’s increase is more incremental, tied to steady involvement rather than a structural role change.

NBA Post All Star Break Usage Losers

Player Pre ASB USG Post ASB USG Δ USG Pre ASB MPG Post ASB MPG Δ MPG
Zion Williamson (NOP) 26.2 22.7 -3.5 29.7 29.7 0.0
James Harden (CLE) 29.6 24.3 -5.3 35.2 34.0 -1.2
Josh Giddey (CHI) 25.0 21.6 -3.4 32.1 32.1 0.0
Jaylen Brown (BOS) 36.0 33.0 -3.0 34.2 34.9 +0.7
Kawhi Leonard (LAC) 32.9 31.9 -1.0 32.8 30.9 -1.9

Post All-Star break deltas are calculated using pre vs post ASB splits from the uploaded CSV files.

James Harden and Jaylen Brown both require deeper context, as their post All-Star break usage drops are tied to broader team dynamics rather than simple role loss. The impact of these shifts is covered in more detail in James Harden Cavaliers impact analysis and in the Celtics with and without Jayson Tatum breakdown.

Josh Giddey’s drop is driven by a combination of role change and availability. After the trade deadline, Chicago added more backcourt creators in Rob Dillingham, Anfernee Simons and Collin Sexton, which reduced his on-ball opportunities. At the same time, a lingering hamstring injury led to strict minute management late in the season and eventually a full shutdown. Along with a noticeable drop in shooting efficiency, this points to a decline that is heavily context-driven rather than purely performance-based.

Kawhi Leonard’s usage dip follows a familiar pattern tied to health. Late-season ankle issues combined with his ongoing load management resulted in reduced minutes and a naturally lower offensive load, especially in the final stretch of the season.

Zion Williamson’s decline is more structural. With the addition of Dejounte Murray and a shift toward a more balanced offensive approach, the Pelicans moved away from the “Point Zion” style. This reduced his on-ball creation responsibilities and brought his usage down to one of the lowest levels of his career, despite still maintaining overall impact within the system.

What Carries Into Next Season

• Matas Buzelis – real role growth in a full rebuild environment, clear pathway to becoming a primary piece
• Cooper Flagg – already operating as a lead option, usage increase is sustainable with upside tied to efficiency
• Maxime Raynaud – strong late-season jump, but highly dependent on Sacramento roster decisions
• Jalen Suggs – stable two-way contributor, role security remains high regardless of offseason moves
• Devin Vassell – minor usage growth, profiles more as a steady contributor than a breakout

• Josh Giddey – usage drop driven by injuries and backcourt additions, not a pure decline signal
• Zion Williamson – structural offensive shift reduced usage, impact still present in a different role
• Kawhi Leonard – health and load management continue to cap both minutes and usage
• James Harden / Jaylen Brown – usage changes tied to team context and lineup structure rather than individual regression

NBA post all star break usage winners losers often highlight which role changes are sustainable, and separating real growth from context-driven shifts is key when projecting into next season.