Forecast NBA 2026-27Minnesota Timberwolves
● Updated · 7 Nov
Minnesota rises from 49 to 56 wins.
Jaden McDaniels
Anthony Edwards is the player who weighs most in this projection: +4.2 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 |
|---|---|---|---|
| Jaden McDaniels | 29.9 | 76.6 | 2,276 |
| LaMelo Ball | 28.8 | 72.9 | 2,086 |
| Ayo Dosunmu | 26.6 | 72.9 | 1,927 |
| Rudy Gobert | 27.9 | 69.5 | 1,927 |
| Anthony Edwards | 34.5 | 52.3 | 1,788 |
| Jonathan Kuminga | 23.3 | 68.1 | 1,578 |
| Bones Hyland | 18.0 | 68.9 | 1,228 |
| Cody Williams | 20.0 | 50.4 | 999 |
| Joan Beringer | 15.3 | 65.2 | 988 |
| Jaylen Clark | 14.1 | 65.2 | 909 |
| Trey Lyles | 14.9 | 60.5 | 897 |
| Terrence Shannon Jr. | 13.5 | 51.2 | 688 |
| Isaiah Evans | 11.9 | 38.1 | 452 |
| Zyon Pullin | 9.6 | 19.9 | 190 |
| Donte DiVincenzo | 26.9 | 6.6 | 176 |
| Rocco Zikarsky | 12.0 | 5.4 | 64 |
- Allocated minutes
- 18,173
- Not assigned to players
- 1,507
- 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 |
|---|---|---|---|
| Jaden McDaniels | 100.0 % | 76.6 | History and team context |
| LaMelo Ball | 100.0 % | 72.9 | History and team context |
| Ayo Dosunmu | 100.0 % | 72.9 | History and team context |
| Rudy Gobert | 100.0 % | 69.5 | History and team context |
| Anthony Edwards | 100.0 % | 52.3 | History and team context |
| Jonathan Kuminga | 100.0 % | 68.1 | History and team context |
| Bones Hyland | 100.0 % | 68.9 | History and team context |
| Cody Williams | 100.0 % | 50.4 | History and team context |
| Joan Beringer | 100.0 % | 65.2 | History and team context |
| Jaylen Clark | 100.0 % | 65.2 | History and team context |
| Trey Lyles | 100.0 % | 60.5 | History before the return |
| Terrence Shannon Jr. | 100.0 % | 51.2 | History and team context |
| Isaiah Evans | 100.0 % | 38.1 | Historical average by draft band |
| Zyon Pullin | 100.0 % | 19.9 | History and team context |
| Donte DiVincenzo | 93.6 % | 7.0 | History and team context |
| Rocco Zikarsky | 24.8 % | 21.6 | History and team context |
Since the first version, on 14 Aug, the projection has moved from 45.5 to 56.3 wins.
See every version
- 14 Aug45.5 wins
- 21 Aug-0.30 · trigger not stated45.2 wins
- 22 Aug0.00 · roster change45.2 wins
- 24 Aug+1.59 · roster change46.8 wins
- 25 Aug0.00 · roster change46.8 wins
- 26 Aug+0.03 · roster change46.8 wins
- 27 Aug+0.14 · roster change46.9 wins
- 28 Aug-0.12 · roster change46.8 wins
- 29 Aug0.00 · roster change46.8 wins
- 30 Aug-0.56 · roster change46.3 wins
- 31 Aug+0.57 · roster change46.8 wins
- 1 Sept-2.18 · roster change44.6 wins
- 2 Sept0.00 · roster change44.6 wins
- 3 Sept0.00 · roster change44.6 wins
- 4 Sept+0.01 · roster change44.7 wins
- 6 Sept0.00 · roster change44.7 wins
- 8 Sept-0.01 · roster change44.6 wins
- 9 Sept0.00 · roster change44.6 wins
- 10 Sept0.00 · roster change44.6 wins
- 11 Sept0.00 · roster change44.6 wins
- 12 Sept-0.02 · roster change44.6 wins
- 14 Sept+0.10 · roster change44.7 wins
- 15 Sept0.00 · roster change44.7 wins
- 16 Sept+0.02 · roster change44.8 wins
- 17 Sept0.00 · roster change44.8 wins
- 18 Sept0.00 · roster change44.8 wins
- 19 Sept+0.01 · roster change44.8 wins
- 20 Sept0.00 · roster change44.8 wins
- 24 Sept-0.01 · trigger not stated44.8 wins
- 25 Sept+0.03 · roster change44.8 wins
- 26 Sept+0.01 · roster change44.8 wins
- 27 Sept-0.01 · roster change44.8 wins
- 28 Sept-0.70 · roster change44.1 wins
- 29 Sept+0.09 · roster change44.2 wins
- 30 Sept+0.01 · roster change44.2 wins
- 1 Oct-0.08 · roster change44.1 wins
- 2 Oct+0.17 · roster change44.3 wins
- 3 Oct-0.11 · roster change44.2 wins
- 4 Oct0.00 · roster change44.2 wins
- 5 Oct+0.07 · roster change44.2 wins
- 6 Oct0.00 · roster change44.2 wins
- 7 Oct0.00 · roster change44.2 wins
- 8 Oct0.00 · roster change44.2 wins
- 9 Oct+0.02 · roster change44.3 wins
- 11 Oct+0.02 · roster change44.3 wins
- 12 Oct0.00 · roster change44.3 wins
- 13 Oct0.00 · trigger not stated44.3 wins
- 14 Oct+0.10 · roster change44.4 wins
- 15 Oct-0.02 · roster change44.4 wins
- 16 Oct0.00 · roster change44.4 wins
- 17 Oct+0.02 · roster change44.4 wins
- 18 Oct-0.08 · roster change44.3 wins
- 19 Oct+0.89 · roster change45.2 wins
- 20 Oct-0.06 · roster change45.1 wins
- 21 Oct0.00 · roster change45.1 wins
- 22 Oct+0.02 · roster change45.1 wins
- 23 Oct+5.32 · roster change50.5 wins
- 24 Oct+0.02 · roster change50.5 wins
- 25 Oct+3.85 · roster change54.3 wins
- 26 Oct-0.10 · roster change54.2 wins
- 27 Oct+3.91 · roster change58.1 wins
- 28 Oct-1.70 · roster change56.4 wins
- 29 Oct-1.29 · roster change55.1 wins
- 30 Oct-2.58 · roster change52.6 wins
- 31 Oct+0.34 · roster change52.9 wins
- 1 Nov+1.68 · roster change54.6 wins
- 2 Nov-1.05 · roster change53.5 wins
- 3 Nov+0.21 · roster change53.8 wins
- 4 Nov-0.39 · roster change53.4 wins
- 5 Nov+1.03 · roster change54.4 wins
- 6 Nov+1.68 · roster change56.1 wins
- 7 Nov+0.27 · roster change56.3 wins
This is how the model has done in other years
Minnesota would win about 56 games; the model gives it a margin of 46 to 67 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: 46–67. Coverage of this forecasting procedure has not yet been validated.
Coverage of this forecasting procedure has not yet been validated.
- worse: 46 · wins · Nominal 80% range
- better: 67 · 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 Minnesota Timberwolves 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
Minnesota Timberwolves: 56.3 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