Forecast NBA 2026-27Dallas Mavericks
● Updated · 7 Nov
Dallas rises from 26 to 37 wins.
Cooper Flagg
Cooper Flagg is the player who weighs most in this projection: +2.3 projected impact.
The players contributing the most projected impact to this roster. Impact is on its real scale, not a 0-99 score.
How the minutes are allocated
Roster used by the projection · 2026-27 · 7 Nov
| Player | Min/game | Expected games | Season minutes |
|---|---|---|---|
| Cooper Flagg | 30.1 | 72.2 | 2,159 |
| P.J. Washington | 25.2 | 71.5 | 1,792 |
| Max Christie | 24.0 | 71.5 | 1,704 |
| Zaccharie Risacher | 21.7 | 73.8 | 1,590 |
| Naji Marshall | 23.8 | 59.6 | 1,409 |
| Daniel Gafford | 19.8 | 69.2 | 1,361 |
| Morez Johnson Jr. | 18.7 | 64.6 | 1,200 |
| Walter Clayton Jr. | 17.1 | 68.0 | 1,155 |
| Kyrie Irving | 23.3 | 47.0 | 1,088 |
| Marcus Sasser | 12.5 | 59.8 | 745 |
| Santi Aldama | 22.9 | 30.9 | 703 |
| Sergio de Larrea | 12.4 | 52.1 | 641 |
| Moussa Cisse | 12.5 | 49.5 | 613 |
| Caleb Martin | 12.6 | 46.7 | 585 |
| Jett Howard | 12.4 | 42.9 | 529 |
| Dereck Lively II | 16.6 | 31.2 | 515 |
| Tobi Lawal | 8.1 | 45.3 | 364 |
- Allocated minutes
- 18,153
- Not assigned to players
- 1,527
- Team budget
- 19,680
Minutes per game are conditional on playing. Season minutes include expected participation and an overtime adjustment; the entire roster's minutes per game do not have to add up to 240.
The availability model is under review: it uses the probability of appearing at the start and does not yet include all late returns. This table shows the published reference, not a recalibration.
Where the allocation comes from
| Player | Probability of an opening appearance | Games conditional on an opening appearance | Minutes method |
|---|---|---|---|
| Cooper Flagg | 100.0 % | 72.2 | History and team context |
| P.J. Washington | 100.0 % | 71.5 | History and team context |
| Max Christie | 100.0 % | 71.5 | History and team context |
| Zaccharie Risacher | 100.0 % | 73.8 | History and team context |
| Naji Marshall | 100.0 % | 59.6 | History and team context |
| Daniel Gafford | 100.0 % | 69.2 | History and team context |
| Morez Johnson Jr. | 100.0 % | 64.6 | Historical average by draft band |
| Walter Clayton Jr. | 100.0 % | 68.0 | History and team context |
| Kyrie Irving | 100.0 % | 47.0 | History before the return |
| Marcus Sasser | 100.0 % | 59.8 | History and team context |
| Santi Aldama | 100.0 % | 30.9 | History and team context |
| Sergio de Larrea | 100.0 % | 52.1 | Historical average by draft band |
| Moussa Cisse | 100.0 % | 49.5 | History and team context |
| Caleb Martin | 100.0 % | 46.7 | History and team context |
| Jett Howard | 100.0 % | 42.9 | History and team context |
| Dereck Lively II | 42.7 % | 73.0 | History before the return |
| Tobi Lawal | 100.0 % | 45.3 | Historical average by draft band |
Since the first version, on 14 Aug, the projection has moved from 31.5 to 37.0 wins.
See every version
- 14 Aug31.5 wins
- 21 Aug-0.51 · trigger not stated31.0 wins
- 22 Aug0.00 · roster change31.0 wins
- 24 Aug-0.27 · roster change30.7 wins
- 25 Aug0.00 · roster change30.7 wins
- 26 Aug+0.01 · roster change30.7 wins
- 27 Aug+0.92 · roster change31.6 wins
- 28 Aug+1.99 · roster change33.6 wins
- 29 Aug0.00 · roster change33.6 wins
- 30 Aug-0.01 · roster change33.6 wins
- 31 Aug-2.81 · roster change30.8 wins
- 1 Sept+1.15 · roster change32.0 wins
- 2 Sept0.00 · roster change32.0 wins
- 3 Sept0.00 · roster change32.0 wins
- 4 Sept+0.01 · roster change32.0 wins
- 6 Sept0.00 · roster change32.0 wins
- 8 Sept0.00 · roster change32.0 wins
- 9 Sept0.00 · roster change32.0 wins
- 10 Sept-0.01 · roster change32.0 wins
- 11 Sept0.00 · roster change32.0 wins
- 12 Sept-0.01 · roster change32.0 wins
- 14 Sept+0.13 · roster change32.1 wins
- 15 Sept0.00 · roster change32.1 wins
- 16 Sept+0.02 · roster change32.1 wins
- 17 Sept0.00 · roster change32.1 wins
- 18 Sept0.00 · roster change32.1 wins
- 19 Sept0.00 · roster change32.1 wins
- 20 Sept0.00 · roster change32.1 wins
- 24 Sept0.00 · trigger not stated32.1 wins
- 25 Sept+0.05 · roster change32.2 wins
- 26 Sept-0.38 · roster change31.8 wins
- 27 Sept-0.08 · roster change31.7 wins
- 28 Sept+0.55 · roster change32.3 wins
- 29 Sept+0.10 · roster change32.4 wins
- 30 Sept0.00 · roster change32.4 wins
- 1 Oct+1.20 · roster change33.5 wins
- 2 Oct+0.15 · roster change33.7 wins
- 3 Oct-0.12 · roster change33.6 wins
- 4 Oct0.00 · roster change33.6 wins
- 5 Oct-1.19 · roster change32.4 wins
- 6 Oct0.00 · roster change32.4 wins
- 7 Oct0.00 · roster change32.4 wins
- 8 Oct-0.01 · roster change32.4 wins
- 9 Oct+0.02 · roster change32.4 wins
- 11 Oct+0.01 · roster change32.4 wins
- 12 Oct0.00 · roster change32.4 wins
- 13 Oct0.00 · trigger not stated32.4 wins
- 14 Oct+0.08 · roster change32.5 wins
- 15 Oct-0.02 · roster change32.5 wins
- 16 Oct0.00 · roster change32.5 wins
- 17 Oct-0.03 · roster change32.4 wins
- 18 Oct+0.47 · roster change32.9 wins
- 19 Oct-0.32 · roster change32.6 wins
- 20 Oct+0.37 · roster change33.0 wins
- 21 Oct0.00 · roster change33.0 wins
- 22 Oct0.00 · roster change33.0 wins
- 23 Oct-2.14 · roster change30.8 wins
- 24 Oct0.00 · roster change30.8 wins
- 25 Oct+3.94 · roster change34.8 wins
- 26 Oct-2.27 · roster change32.5 wins
- 27 Oct+0.02 · roster change32.5 wins
- 28 Oct-0.77 · roster change31.7 wins
- 29 Oct-0.18 · roster change31.6 wins
- 30 Oct+5.41 · roster change37.0 wins
- 31 Oct+0.71 · roster change37.7 wins
- 1 Nov+0.89 · roster change38.6 wins
- 2 Nov0.00 · roster change38.6 wins
- 3 Nov+0.15 · roster change38.7 wins
- 4 Nov-4.00 · roster change34.7 wins
- 5 Nov-0.15 · roster change34.6 wins
- 6 Nov+1.30 · roster change35.9 wins
- 7 Nov+1.08 · roster change37.0 wins
This is how the model has done in other years
Dallas would win about 37 games; the model gives it a margin of 26 to 47 that is not yet well measured.
We tested it on seasons already played, knowing which players each team had: on average, we were off by about 7 wins per team.
The final record for the 2026-27 season is not available yet; when it ends, we will show the actual wins alongside the projected wins, without changing the forecast.
This is an estimate with the data we have: it does not read injury reports, and a trade does not count until we run it again. Every figure comes from games already played.
From here
Technical detail
Uncertainty
Nominal 80% range: 26–47. Coverage of this forecasting procedure has not yet been validated.
Coverage of this forecasting procedure has not yet been validated.
- worse: 26 · wins · Nominal 80% range
- better: 47 · wins · Nominal 80% range
How this model has performed
Measured on seasons already played, not on this one. Every figure with its window and its status.
- Nominal 80% range: — · Coverage of this forecasting procedure has not yet been validated.
- Coverage recorded on 12 August for the residual interval: coverage 81.30 % · Coverage of this forecasting procedure has not yet been validated.
- Average error in wins from the season simulation: average error 7.30 · 2019-2025 · n=210 · validated · rosters that actually played (information known after the fact)
- Average error in conference seeding: average error 2.64 · 2019-2025 · n=210 · validated · rosters that actually played (information known after the fact)
- Average error in wins from the earlier, coarser method: average error 6.93 · 2005-2025 · n=555 · experimental
The real outcome
The final record for the 2026-27 season is not available yet; when it ends, we will show the actual wins alongside the projected wins, without changing the forecast.
The question
How many games will Dallas Mavericks win in 2026-27?
What this does not prove
- Coverage of this forecasting procedure has not yet been validated.
- This is not a betting line or a market probability: it is expected wins with a range.
- It rests on today's roster. A later trade is not inside it until the model is rerun.
- The win split does not break the schedule down game by game.
The evidence
Dallas Mavericks: 37.0 projected wins in 2026-27
What has changed since the first version
Where it comes from
Confidence: low · Rights: Licensed data: viewable here; ask before redistributing.
- Source: 2026-11-07
- Model input: 2026-11-07
- Computation: 2026-11-07
- This answer: 2026-11-07
Where this comes from: Team season projection · up to date · Roster the projection consumed · up to date · Player projection · up to date · Today's rosters · up to date · Game results · closed season · its clock is the season · Measured model accuracy · closed season · its clock is the season