Forecast NBA 2026-27Charlotte Hornets
● Updated · 7 Nov
Charlotte drops from 44 to 23 wins.
Brandon Miller
Kon Knueppel is the player who weighs most in this projection: +2.9 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 |
|---|---|---|---|
| Brandon Miller | 27.5 | 72.6 | 1,980 |
| Naz Reid | 23.7 | 75.6 | 1,777 |
| Grayson Allen | 23.9 | 70.6 | 1,675 |
| Moussa Diabate | 24.3 | 69.0 | 1,663 |
| Royce O'Neale | 21.5 | 74.1 | 1,578 |
| Sion James | 19.5 | 76.6 | 1,486 |
| Ryan Kalkbrenner | 19.2 | 73.4 | 1,402 |
| Dennis Schroder | 19.8 | 67.7 | 1,331 |
| Kon Knueppel | 28.9 | 37.6 | 1,080 |
| Tidjane Salaun | 16.1 | 62.7 | 1,006 |
| Christian Anderson | 14.5 | 61.1 | 880 |
| Coby White | 20.4 | 39.2 | 795 |
| Hannes Steinbach | 16.7 | 38.1 | 632 |
| Liam McNeeley | 12.2 | 41.0 | 494 |
| PJ Hall | 10.6 | 23.8 | 251 |
| Grant Williams | 16.5 | 8.7 | 142 |
- Allocated minutes
- 18,172
- Not assigned to players
- 1,508
- 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 |
|---|---|---|---|
| Brandon Miller | 100.0 % | 72.6 | History and team context |
| Naz Reid | 100.0 % | 75.6 | History and team context |
| Grayson Allen | 100.0 % | 70.6 | History and team context |
| Moussa Diabate | 100.0 % | 69.0 | History and team context |
| Royce O'Neale | 100.0 % | 74.1 | History and team context |
| Sion James | 100.0 % | 76.6 | History and team context |
| Ryan Kalkbrenner | 100.0 % | 73.4 | History and team context |
| Dennis Schroder | 100.0 % | 67.7 | History and team context |
| Kon Knueppel | 100.0 % | 37.6 | History and team context |
| Tidjane Salaun | 100.0 % | 62.7 | History and team context |
| Christian Anderson | 100.0 % | 61.1 | Historical average by draft band |
| Coby White | 100.0 % | 39.2 | History and team context |
| Hannes Steinbach | 100.0 % | 38.1 | Historical average by draft band |
| Liam McNeeley | 100.0 % | 41.0 | History and team context |
| PJ Hall | 100.0 % | 23.8 | History and team context |
| Grant Williams | 66.5 % | 13.1 | History and team context |
Since the first version, on 14 Aug, the projection has moved from 42.0 to 22.9 wins.
See every version
- 14 Aug42.0 wins
- 21 Aug-1.29 · trigger not stated40.7 wins
- 22 Aug0.00 · roster change40.7 wins
- 24 Aug+7.80 · roster change48.5 wins
- 25 Aug0.00 · roster change48.5 wins
- 26 Aug+0.05 · roster change48.5 wins
- 27 Aug-0.46 · roster change48.0 wins
- 28 Aug-7.45 · roster change40.6 wins
- 29 Aug0.00 · roster change40.6 wins
- 30 Aug-0.01 · roster change40.6 wins
- 31 Aug+7.82 · roster change48.4 wins
- 1 Sept-7.75 · roster change40.7 wins
- 2 Sept-0.01 · roster change40.6 wins
- 3 Sept0.00 · roster change40.6 wins
- 4 Sept+0.03 · roster change40.7 wins
- 6 Sept0.00 · roster change40.7 wins
- 8 Sept-0.01 · roster change40.7 wins
- 9 Sept+0.01 · roster change40.7 wins
- 10 Sept-0.01 · roster change40.7 wins
- 11 Sept0.00 · roster change40.7 wins
- 12 Sept-0.02 · roster change40.6 wins
- 14 Sept-0.10 · roster change40.5 wins
- 15 Sept0.00 · roster change40.5 wins
- 16 Sept+0.03 · roster change40.6 wins
- 17 Sept+0.01 · roster change40.6 wins
- 18 Sept0.00 · roster change40.6 wins
- 19 Sept0.00 · roster change40.6 wins
- 20 Sept0.00 · roster change40.6 wins
- 24 Sept-0.90 · trigger not stated39.7 wins
- 25 Sept+0.02 · roster change39.7 wins
- 26 Sept+0.01 · roster change39.7 wins
- 27 Sept-0.02 · roster change39.7 wins
- 28 Sept-0.47 · roster change39.2 wins
- 29 Sept+2.04 · roster change41.3 wins
- 30 Sept+0.01 · roster change41.3 wins
- 1 Oct-0.05 · roster change41.2 wins
- 2 Oct+0.25 · roster change41.5 wins
- 3 Oct-0.22 · roster change41.3 wins
- 4 Oct0.00 · roster change41.3 wins
- 5 Oct+0.06 · roster change41.3 wins
- 6 Oct0.00 · roster change41.3 wins
- 7 Oct0.00 · roster change41.3 wins
- 8 Oct+0.01 · roster change41.3 wins
- 9 Oct+0.02 · roster change41.4 wins
- 11 Oct+0.03 · roster change41.4 wins
- 12 Oct0.00 · roster change41.4 wins
- 13 Oct0.00 · trigger not stated41.4 wins
- 14 Oct-0.19 · roster change41.2 wins
- 15 Oct-0.02 · roster change41.2 wins
- 16 Oct0.00 · roster change41.2 wins
- 17 Oct+0.11 · roster change41.3 wins
- 18 Oct-0.10 · roster change41.2 wins
- 19 Oct-0.37 · roster change40.8 wins
- 20 Oct0.00 · roster change40.8 wins
- 21 Oct0.00 · roster change40.8 wins
- 22 Oct0.00 · roster change40.8 wins
- 23 Oct+1.55 · roster change42.4 wins
- 24 Oct0.00 · roster change42.4 wins
- 25 Oct-9.64 · roster change32.7 wins
- 26 Oct+0.45 · roster change33.2 wins
- 27 Oct+0.01 · roster change33.2 wins
- 28 Oct-0.10 · roster change33.1 wins
- 29 Oct+0.09 · roster change33.2 wins
- 30 Oct+0.29 · roster change33.5 wins
- 31 Oct-0.46 · roster change33.0 wins
- 1 Nov-2.49 · roster change30.5 wins
- 2 Nov-1.41 · roster change29.1 wins
- 3 Nov+1.78 · roster change30.9 wins
- 4 Nov-3.06 · roster change27.8 wins
- 5 Nov-2.42 · roster change25.4 wins
- 6 Nov+0.46 · roster change25.9 wins
- 7 Nov-2.97 · roster change22.9 wins
This is how the model has done in other years
Charlotte would win about 23 games; the model gives it a margin of 12 to 33 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: 12–33. Coverage of this forecasting procedure has not yet been validated.
Coverage of this forecasting procedure has not yet been validated.
- worse: 12 · wins · Nominal 80% range
- better: 33 · 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 Charlotte Hornets 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
Charlotte Hornets: 22.9 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