Lillard's Role Is More Exposed Than Morant's in Portland's New Backcourt
Both guards project as near-identical high-usage lead guards, but Lillard returns from a fully lost season with no current-form data while Morant's recent sample shows a stable, only mildly-shifted role — making Lillard the one whose usage is more likely to bend.
Published: · Figures as of August 25, 2026
Asked: Portland will have Ja Morant and a returning Damian Lillard in the same backcourt. Which player’s value is more likely to change because of the other?
Lillard's role looks more likely to bend than Morant's
Both players project as nearly identical high-usage lead guards when healthy — the redundancy, not either man's decline, is the real story here. Given that overlap, the data points to Damian Lillard's role being the one more likely to change, mainly because he is coming back with zero current-season evidence behind him while Ja Morant already has a fresh, stable-looking sample.
The overlap is real
In each man's last full-ish healthy season, their shot-creation profiles are almost interchangeable:
| Season | Games | FGA/g | PPG | AST/g | |
|---|---|---|---|---|---|
| Lillard | 2024-25 | 59 | 17.0 | 24.9 | 7.0 |
| Morant | 2024-25 | 50 | 17.8 | 23.2 | 7.3 |
Two players who each want the ball at a nearly identical rate can't both keep their old volume in the same backcourt — someone's usage compresses. That's the mechanism behind the question, and it's supported by these numbers, not assumed.
Who has the more uncertain current form
- Lillard did not play a single game last season — 81 games missed, running from opening night (2025-10-22) through April 12. There is no current-season line for him at all, and DataBaller's own deployment-shift model has no reading on him either, because that model requires appearances within the trailing year and he has none.
- Morant, despite four separate absence stretches with Memphis last season (60 missed games combined), still logged 20 games and produced close to his career rate: 19.45 PPG, 8.05 APG, 16.1 FGA/game. The stored deployment-shift read on that window (value 0.287, full confidence) shows his role was only moderately in flux relative to his own baseline — assist rate per minute up, three-point rate down, but usage per minute essentially flat (a -0.08 standard-deviation move). In plain terms: when he was actually on the floor this season, he was still playing his usual high-usage game.
So one of these two players has an established, only mildly-shifted recent role; the other has no measured role at all coming off a fully lost year. When a team has to allocate ball-handling touches between two players with historically equal claims on them, the one with a live, stable read is in a stronger position to keep his usage, and the one returning from total absence is the one whose role is more exposed to change.
What this can't tell you
Neither player has logged a shared minute with the other, so there is no observed on-court chemistry number to point to — any shared-lineup split at this stage would be built on a sample of zero games, the exact small-sample trap that makes raw on-off readings unreliable even with real minutes behind them. This is a projection from overlapping usage histories and current-form asymmetry, not a measured fit outcome, and it says nothing about who plays better beside the other — only whose role is more likely to move.
Confidence: Medium. The usage overlap and the current-data asymmetry are both real and measured; how Portland's coaching staff actually splits touches once games are played is not something this data can see yet.