Forecast NBA 2026-27Miami Heat
● Updated · 7 Nov
Miami drops from 43 to 34 wins.
Bam Adebayo
Giannis Antetokounmpo is the player who weighs most in this projection: +6.3 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 |
|---|---|---|---|
| Bam Adebayo | 29.8 | 75.3 | 2,230 |
| Giannis Antetokounmpo | 31.0 | 67.7 | 2,085 |
| Andrew Wiggins | 26.3 | 72.3 | 1,890 |
| Davion Mitchell | 25.7 | 73.8 | 1,885 |
| Pelle Larsson | 23.8 | 73.2 | 1,731 |
| Tim Hardaway Jr. | 22.0 | 73.2 | 1,597 |
| Bobby Portis | 21.3 | 70.2 | 1,484 |
| Klay Thompson | 17.7 | 69.2 | 1,216 |
| Nikola Jovic | 16.2 | 57.1 | 919 |
| Dru Smith | 14.9 | 51.4 | 760 |
| Ryan Conwell | 12.3 | 54.9 | 671 |
| Simone Fontecchio | 13.4 | 45.8 | 609 |
| Nick Richards | 11.1 | 46.5 | 513 |
| Myron Gardner | 10.1 | 44.7 | 449 |
| Keshad Johnson | 10.4 | 8.0 | 83 |
| Vladislav Goldin | 6.0 | 5.2 | 31 |
- 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 |
|---|---|---|---|
| Bam Adebayo | 100.0 % | 75.3 | History and team context |
| Giannis Antetokounmpo | 100.0 % | 67.7 | History and team context |
| Andrew Wiggins | 100.0 % | 72.3 | History and team context |
| Davion Mitchell | 100.0 % | 73.8 | History and team context |
| Pelle Larsson | 100.0 % | 73.2 | History and team context |
| Tim Hardaway Jr. | 100.0 % | 73.2 | History and team context |
| Bobby Portis | 100.0 % | 70.2 | History and team context |
| Klay Thompson | 100.0 % | 69.2 | History and team context |
| Nikola Jovic | 100.0 % | 57.1 | History and team context |
| Dru Smith | 100.0 % | 51.4 | History and team context |
| Ryan Conwell | 100.0 % | 54.9 | Historical average by draft band |
| Simone Fontecchio | 100.0 % | 45.8 | History and team context |
| Nick Richards | 100.0 % | 46.5 | History and team context |
| Myron Gardner | 100.0 % | 44.7 | History and team context |
| Keshad Johnson | 48.9 % | 16.3 | History and team context |
| Vladislav Goldin | 24.8 % | 21.0 | History and team context |
Since the first version, on 14 Aug, the projection has moved from 39.7 to 34.4 wins.
See every version
- 14 Aug39.7 wins
- 21 Aug+0.41 · trigger not stated40.1 wins
- 22 Aug0.00 · roster change40.1 wins
- 24 Aug-1.47 · roster change38.6 wins
- 25 Aug0.00 · roster change38.6 wins
- 26 Aug0.00 · roster change38.6 wins
- 27 Aug-0.16 · roster change38.5 wins
- 28 Aug+0.10 · roster change38.6 wins
- 29 Aug-0.06 · roster change38.5 wins
- 30 Aug-0.01 · roster change38.5 wins
- 31 Aug-0.03 · roster change38.5 wins
- 1 Sept-0.27 · roster change38.2 wins
- 2 Sept0.00 · roster change38.2 wins
- 3 Sept0.00 · roster change38.2 wins
- 4 Sept+0.02 · roster change38.2 wins
- 6 Sept0.00 · roster change38.2 wins
- 8 Sept0.00 · roster change38.2 wins
- 9 Sept0.00 · roster change38.2 wins
- 10 Sept0.00 · roster change38.2 wins
- 11 Sept0.00 · roster change38.2 wins
- 12 Sept-0.03 · roster change38.2 wins
- 14 Sept-0.09 · roster change38.1 wins
- 15 Sept0.00 · roster change38.1 wins
- 16 Sept+0.04 · roster change38.1 wins
- 17 Sept0.00 · roster change38.1 wins
- 18 Sept0.00 · roster change38.1 wins
- 19 Sept0.00 · roster change38.1 wins
- 20 Sept0.00 · roster change38.1 wins
- 24 Sept-1.40 · trigger not stated36.8 wins
- 25 Sept+0.02 · roster change36.8 wins
- 26 Sept+0.01 · roster change36.8 wins
- 27 Sept+0.02 · roster change36.8 wins
- 28 Sept+0.10 · roster change36.9 wins
- 29 Sept-0.03 · roster change36.9 wins
- 30 Sept-0.29 · roster change36.6 wins
- 1 Oct+0.01 · roster change36.6 wins
- 2 Oct+0.23 · roster change36.8 wins
- 3 Oct-0.20 · roster change36.6 wins
- 4 Oct0.00 · roster change36.6 wins
- 5 Oct-0.01 · roster change36.6 wins
- 6 Oct0.00 · roster change36.6 wins
- 7 Oct0.00 · roster change36.6 wins
- 8 Oct+0.02 · roster change36.6 wins
- 9 Oct+0.01 · roster change36.6 wins
- 11 Oct-0.16 · roster change36.5 wins
- 12 Oct0.00 · roster change36.5 wins
- 13 Oct0.00 · trigger not stated36.5 wins
- 14 Oct+0.08 · roster change36.6 wins
- 15 Oct-0.02 · roster change36.5 wins
- 16 Oct0.00 · roster change36.5 wins
- 17 Oct-0.01 · roster change36.5 wins
- 18 Oct+1.43 · roster change38.0 wins
- 19 Oct+0.09 · roster change38.0 wins
- 20 Oct+0.03 · roster change38.1 wins
- 21 Oct0.00 · roster change38.1 wins
- 22 Oct-0.02 · roster change38.1 wins
- 23 Oct-5.48 · roster change32.6 wins
- 24 Oct-0.01 · roster change32.6 wins
- 25 Oct-2.61 · roster change30.0 wins
- 26 Oct-0.44 · roster change29.5 wins
- 27 Oct+0.14 · roster change29.7 wins
- 28 Oct-0.31 · roster change29.4 wins
- 29 Oct0.00 · roster change29.4 wins
- 30 Oct+4.53 · roster change33.9 wins
- 31 Oct+0.49 · roster change34.4 wins
- 1 Nov+2.54 · roster change36.9 wins
- 2 Nov+0.20 · roster change37.1 wins
- 3 Nov-0.25 · roster change36.9 wins
- 4 Nov-1.62 · roster change35.2 wins
- 5 Nov+0.72 · roster change36.0 wins
- 6 Nov+0.34 · roster change36.3 wins
- 7 Nov-1.89 · roster change34.4 wins
This is how the model has done in other years
Miami would win about 34 games; the model gives it a margin of 24 to 45 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: 24–45. Coverage of this forecasting procedure has not yet been validated.
Coverage of this forecasting procedure has not yet been validated.
- worse: 24 · wins · Nominal 80% range
- better: 45 · 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 Miami Heat 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
Miami Heat: 34.4 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