Forecast NBA 2026-27Boston Celtics
● Updated · 7 Nov
Boston rises from 56 to 57 wins.
Derrick White
Jayson Tatum is the player who weighs most in this projection: +4.5 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 |
|---|---|---|---|
| Derrick White | 28.5 | 75.1 | 2,128 |
| Payton Pritchard | 27.6 | 76.5 | 2,101 |
| Jayson Tatum | 30.3 | 62.0 | 1,866 |
| Neemias Queta | 24.0 | 72.5 | 1,726 |
| Sam Hauser | 21.0 | 73.9 | 1,544 |
| Paul George | 25.2 | 60.2 | 1,507 |
| Baylor Scheierman | 18.1 | 71.0 | 1,279 |
| Jordan Walsh | 18.1 | 69.6 | 1,253 |
| Mitchell Robinson | 20.2 | 61.2 | 1,231 |
| Hugo Gonzalez | 15.4 | 73.0 | 1,117 |
| Luka Garza | 15.6 | 67.7 | 1,047 |
| Mike Conley | 12.6 | 36.1 | 452 |
| Ron Harper Jr. | 10.9 | 34.0 | 369 |
| Dillon Mitchell | 12.1 | 25.9 | 310 |
| Devin Carter | 16.0 | 10.2 | 162 |
| Amari Williams | 7.4 | 7.1 | 52 |
- Allocated minutes
- 18,144
- Not assigned to players
- 1,536
- 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 |
|---|---|---|---|
| Derrick White | 100.0 % | 75.1 | History and team context |
| Payton Pritchard | 100.0 % | 76.5 | History and team context |
| Jayson Tatum | 100.0 % | 62.0 | History and team context |
| Neemias Queta | 100.0 % | 72.5 | History and team context |
| Sam Hauser | 100.0 % | 73.9 | History and team context |
| Paul George | 100.0 % | 60.2 | History and team context |
| Baylor Scheierman | 100.0 % | 71.0 | History and team context |
| Jordan Walsh | 100.0 % | 69.6 | History and team context |
| Mitchell Robinson | 100.0 % | 61.2 | History and team context |
| Hugo Gonzalez | 100.0 % | 73.0 | History and team context |
| Luka Garza | 100.0 % | 67.7 | History and team context |
| Mike Conley | 100.0 % | 36.1 | History and team context |
| Ron Harper Jr. | 100.0 % | 34.0 | History and team context |
| Dillon Mitchell | 100.0 % | 25.9 | Historical average by draft band |
| Devin Carter | 66.5 % | 15.4 | History and team context |
| Amari Williams | 24.8 % | 28.6 | History and team context |
Since the first version, on 14 Aug, the projection has moved from 48.5 to 57.2 wins.
See every version
- 14 Aug48.5 wins
- 21 Aug-0.56 · trigger not stated47.9 wins
- 22 Aug0.00 · roster change47.9 wins
- 24 Aug+3.27 · roster change51.2 wins
- 25 Aug0.00 · roster change51.2 wins
- 26 Aug0.00 · roster change51.2 wins
- 27 Aug+0.38 · roster change51.5 wins
- 28 Aug-1.40 · roster change50.1 wins
- 29 Aug0.00 · roster change50.1 wins
- 30 Aug-0.02 · roster change50.1 wins
- 31 Aug+1.04 · roster change51.2 wins
- 1 Sept-3.24 · roster change47.9 wins
- 2 Sept0.00 · roster change47.9 wins
- 3 Sept0.00 · roster change47.9 wins
- 4 Sept+0.02 · roster change48.0 wins
- 6 Sept0.00 · roster change48.0 wins
- 8 Sept-0.01 · roster change47.9 wins
- 9 Sept0.00 · roster change47.9 wins
- 10 Sept0.00 · roster change47.9 wins
- 11 Sept0.00 · roster change47.9 wins
- 12 Sept-0.01 · roster change47.9 wins
- 14 Sept-0.22 · roster change47.7 wins
- 15 Sept0.00 · roster change47.7 wins
- 16 Sept+0.03 · roster change47.7 wins
- 17 Sept0.00 · roster change47.7 wins
- 18 Sept0.00 · roster change47.7 wins
- 19 Sept0.00 · roster change47.7 wins
- 20 Sept0.00 · roster change47.7 wins
- 24 Sept+0.05 · trigger not stated47.8 wins
- 25 Sept+0.02 · roster change47.8 wins
- 26 Sept+0.01 · roster change47.8 wins
- 27 Sept-0.02 · roster change47.8 wins
- 28 Sept-0.88 · roster change46.9 wins
- 29 Sept+0.01 · roster change46.9 wins
- 30 Sept+0.01 · roster change46.9 wins
- 1 Oct+1.04 · roster change48.0 wins
- 2 Oct+0.26 · roster change48.2 wins
- 3 Oct-0.23 · roster change48.0 wins
- 4 Oct0.00 · roster change48.0 wins
- 5 Oct-1.03 · roster change47.0 wins
- 6 Oct0.00 · roster change47.0 wins
- 7 Oct0.00 · roster change47.0 wins
- 8 Oct+0.02 · roster change47.0 wins
- 9 Oct+0.02 · roster change47.0 wins
- 11 Oct+0.03 · roster change47.0 wins
- 12 Oct0.00 · roster change47.0 wins
- 13 Oct0.00 · trigger not stated47.0 wins
- 14 Oct-0.05 · roster change47.0 wins
- 15 Oct-0.01 · roster change47.0 wins
- 16 Oct0.00 · roster change47.0 wins
- 17 Oct-0.01 · roster change47.0 wins
- 18 Oct-0.09 · roster change46.9 wins
- 19 Oct+0.14 · roster change47.0 wins
- 20 Oct-0.01 · roster change47.0 wins
- 21 Oct0.00 · roster change47.0 wins
- 22 Oct-1.30 · roster change45.7 wins
- 23 Oct-0.04 · roster change45.7 wins
- 24 Oct-0.01 · roster change45.7 wins
- 25 Oct+0.81 · roster change46.5 wins
- 26 Oct0.00 · roster change46.5 wins
- 27 Oct+0.15 · roster change46.6 wins
- 28 Oct+6.80 · roster change53.4 wins
- 29 Oct-1.30 · roster change52.1 wins
- 30 Oct+0.02 · roster change52.1 wins
- 31 Oct+0.18 · roster change52.3 wins
- 1 Nov+0.21 · roster change52.5 wins
- 2 Nov+0.49 · roster change53.0 wins
- 3 Nov+0.80 · roster change53.8 wins
- 4 Nov-1.72 · roster change52.1 wins
- 5 Nov+0.36 · roster change52.5 wins
- 6 Nov-0.70 · roster change51.8 wins
- 7 Nov+5.47 · roster change57.2 wins
This is how the model has done in other years
Boston would win about 57 games; the model gives it a margin of 47 to 68 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: 47–68. Coverage of this forecasting procedure has not yet been validated.
Coverage of this forecasting procedure has not yet been validated.
- worse: 47 · wins · Nominal 80% range
- better: 68 · 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 Boston Celtics 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
Boston Celtics: 57.2 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