Forecast NBA 2026-27Sacramento Kings
● Updated · 7 Nov
Sacramento drops from 22 to 18 wins.
Zach LaVine
Domantas Sabonis is the player who weighs most in this projection: +2.6 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 |
|---|---|---|---|
| Zach LaVine | 27.5 | 68.2 | 1,861 |
| Domantas Sabonis | 27.4 | 66.1 | 1,796 |
| Precious Achiuwa | 22.3 | 72.6 | 1,606 |
| Keegan Murray | 28.3 | 54.0 | 1,520 |
| Darius Acuff Jr. | 23.5 | 64.6 | 1,505 |
| Maxime Raynaud | 24.9 | 59.9 | 1,482 |
| De'Andre Hunter | 22.4 | 63.7 | 1,418 |
| Nique Clifford | 19.2 | 70.3 | 1,338 |
| Malik Monk | 19.5 | 65.7 | 1,272 |
| Daeqwon Plowden | 19.4 | 48.8 | 942 |
| Emanuel Sharp | 13.4 | 64.6 | 858 |
| Leaky Black | 22.7 | 36.6 | 823 |
| Alex Karaban | 13.5 | 45.3 | 606 |
| Dylan Cardwell | 18.3 | 33.1 | 601 |
| Jonathan Mogbo | 11.8 | 39.3 | 462 |
| Sean Pedulla | 9.8 | 5.4 | 52 |
| Ben Simmons | 15.8 | 0.7 | 11 |
- 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 |
|---|---|---|---|
| Zach LaVine | 100.0 % | 68.2 | History and team context |
| Domantas Sabonis | 100.0 % | 66.1 | History and team context |
| Precious Achiuwa | 100.0 % | 72.6 | History and team context |
| Keegan Murray | 100.0 % | 54.0 | History and team context |
| Darius Acuff Jr. | 100.0 % | 64.6 | Historical average by draft band |
| Maxime Raynaud | 93.6 % | 64.0 | History and team context |
| De'Andre Hunter | 100.0 % | 63.7 | History and team context |
| Nique Clifford | 100.0 % | 70.3 | History and team context |
| Malik Monk | 100.0 % | 65.7 | History and team context |
| Daeqwon Plowden | 100.0 % | 48.8 | History and team context |
| Emanuel Sharp | 100.0 % | 64.6 | Historical average by draft band |
| Leaky Black | 100.0 % | 36.6 | History and team context |
| Alex Karaban | 100.0 % | 45.3 | Historical average by draft band |
| Dylan Cardwell | 100.0 % | 33.1 | History and team context |
| Jonathan Mogbo | 100.0 % | 39.3 | History and team context |
| Sean Pedulla | 24.8 % | 21.7 | History and team context |
| Ben Simmons | 61.3 % | 1.2 | History before the return |
Since the first version, on 14 Aug, the projection has moved from 24.6 to 17.7 wins.
See every version
- 14 Aug24.6 wins
- 21 Aug+0.37 · trigger not stated24.9 wins
- 22 Aug0.00 · roster change24.9 wins
- 24 Aug+2.96 · roster change27.9 wins
- 25 Aug0.00 · roster change27.9 wins
- 26 Aug-0.01 · roster change27.9 wins
- 27 Aug+0.83 · roster change28.7 wins
- 28 Aug-2.34 · roster change26.4 wins
- 29 Aug0.00 · roster change26.4 wins
- 30 Aug-0.01 · roster change26.4 wins
- 31 Aug+1.38 · roster change27.7 wins
- 1 Sept-3.12 · roster change24.6 wins
- 2 Sept-0.01 · roster change24.6 wins
- 3 Sept0.00 · roster change24.6 wins
- 4 Sept+0.01 · roster change24.6 wins
- 6 Sept0.00 · roster change24.6 wins
- 8 Sept-0.01 · roster change24.6 wins
- 9 Sept-0.03 · roster change24.6 wins
- 10 Sept0.00 · roster change24.6 wins
- 11 Sept0.00 · roster change24.6 wins
- 12 Sept-0.02 · roster change24.6 wins
- 14 Sept+0.23 · roster change24.8 wins
- 15 Sept0.00 · roster change24.8 wins
- 16 Sept+0.02 · roster change24.8 wins
- 17 Sept0.00 · roster change24.8 wins
- 18 Sept0.00 · roster change24.8 wins
- 19 Sept+0.01 · roster change24.8 wins
- 20 Sept0.00 · roster change24.8 wins
- 24 Sept-0.01 · trigger not stated24.8 wins
- 25 Sept+0.05 · roster change24.9 wins
- 26 Sept+0.02 · roster change24.9 wins
- 27 Sept-0.02 · roster change24.9 wins
- 28 Sept+0.03 · roster change24.9 wins
- 29 Sept-1.14 · roster change23.7 wins
- 30 Sept0.00 · roster change23.7 wins
- 1 Oct-0.12 · roster change23.6 wins
- 2 Oct+0.13 · roster change23.8 wins
- 3 Oct-0.10 · roster change23.6 wins
- 4 Oct0.00 · roster change23.6 wins
- 5 Oct+0.12 · roster change23.8 wins
- 6 Oct0.00 · roster change23.8 wins
- 7 Oct0.00 · roster change23.8 wins
- 8 Oct0.00 · roster change23.8 wins
- 9 Oct+0.01 · roster change23.8 wins
- 11 Oct+0.02 · roster change23.8 wins
- 12 Oct0.00 · roster change23.8 wins
- 13 Oct0.00 · trigger not stated23.8 wins
- 14 Oct-0.03 · roster change23.8 wins
- 15 Oct-0.01 · roster change23.8 wins
- 16 Oct0.00 · roster change23.8 wins
- 17 Oct+0.01 · roster change23.8 wins
- 18 Oct-0.08 · roster change23.7 wins
- 19 Oct+0.23 · roster change23.9 wins
- 20 Oct+0.34 · roster change24.3 wins
- 21 Oct0.00 · roster change24.3 wins
- 22 Oct+0.03 · roster change24.3 wins
- 23 Oct-3.60 · roster change20.7 wins
- 24 Oct0.00 · roster change20.7 wins
- 25 Oct-0.04 · roster change20.6 wins
- 26 Oct0.00 · roster change20.6 wins
- 27 Oct-1.33 · roster change19.3 wins
- 28 Oct-0.50 · roster change18.8 wins
- 29 Oct-1.88 · roster change16.9 wins
- 30 Oct-0.01 · roster change16.9 wins
- 31 Oct-0.52 · roster change16.4 wins
- 1 Nov-0.18 · roster change16.2 wins
- 2 Nov-1.50 · roster change14.7 wins
- 3 Nov+0.86 · roster change15.6 wins
- 4 Nov+2.69 · roster change18.3 wins
- 5 Nov-0.03 · roster change18.3 wins
- 6 Nov-0.12 · roster change18.1 wins
- 7 Nov-0.44 · roster change17.7 wins
This is how the model has done in other years
Sacramento would win about 18 games; the model gives it a margin of 7 to 28 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: 7–28. Coverage of this forecasting procedure has not yet been validated.
Coverage of this forecasting procedure has not yet been validated.
- worse: 7 · wins · Nominal 80% range
- better: 28 · 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 Sacramento Kings 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
Sacramento Kings: 17.7 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