Forecast NBA 2026-27Milwaukee Bucks
● Updated · 7 Nov
Milwaukee drops from 32 to 24 wins.
Ryan Rollins
Tyler Herro is the player who weighs most in this projection: +1.3 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 |
|---|---|---|---|
| Ryan Rollins | 27.1 | 74.0 | 1,988 |
| Tyler Herro | 26.4 | 69.1 | 1,809 |
| Jaime Jaquez Jr. | 23.5 | 74.8 | 1,747 |
| AJ Green | 22.3 | 75.0 | 1,664 |
| Myles Turner | 22.4 | 73.1 | 1,626 |
| Kel'el Ware | 21.2 | 74.6 | 1,571 |
| Kyle Kuzma | 20.7 | 71.7 | 1,474 |
| Brayden Burries | 19.7 | 64.6 | 1,263 |
| Kasparas Jakucionis | 17.1 | 69.3 | 1,177 |
| Nate Ament | 16.5 | 54.9 | 898 |
| Ousmane Dieng | 15.9 | 53.5 | 846 |
| Jericho Sims | 14.9 | 50.0 | 741 |
| Gary Trent Jr. | 15.7 | 37.7 | 589 |
| Bogoljub Markovic | 8.9 | 25.9 | 230 |
| Caris LeVert | 14.2 | 11.8 | 166 |
| Cormac Ryan | 19.0 | 7.6 | 144 |
| Kam Jones | 11.2 | 9.9 | 110 |
| Pete Nance | 12.0 | 9.2 | 109 |
- Allocated minutes
- 18,152
- Not assigned to players
- 1,528
- 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 |
|---|---|---|---|
| Ryan Rollins | 100.0 % | 74.0 | History and team context |
| Tyler Herro | 100.0 % | 69.1 | History and team context |
| Jaime Jaquez Jr. | 100.0 % | 74.8 | History and team context |
| AJ Green | 100.0 % | 75.0 | History and team context |
| Myles Turner | 100.0 % | 73.1 | History and team context |
| Kel'el Ware | 100.0 % | 74.6 | History and team context |
| Kyle Kuzma | 100.0 % | 71.7 | History and team context |
| Brayden Burries | 100.0 % | 64.6 | Historical average by draft band |
| Kasparas Jakucionis | 100.0 % | 69.3 | History and team context |
| Nate Ament | 100.0 % | 54.9 | Historical average by draft band |
| Ousmane Dieng | 100.0 % | 53.5 | History and team context |
| Jericho Sims | 100.0 % | 50.0 | History and team context |
| Gary Trent Jr. | 100.0 % | 37.7 | History and team context |
| Bogoljub Markovic | 100.0 % | 25.9 | Historical average by draft band |
| Caris LeVert | 81.7 % | 14.4 | History and team context |
| Cormac Ryan | 48.9 % | 15.6 | History and team context |
| Kam Jones | 66.5 % | 14.9 | History and team context |
| Pete Nance | 66.5 % | 13.8 | History and team context |
Since the first version, on 14 Aug, the projection has moved from 34.9 to 23.7 wins.
See every version
- 14 Aug34.9 wins
- 21 Aug-0.97 · trigger not stated33.9 wins
- 22 Aug0.00 · roster change33.9 wins
- 24 Aug+2.07 · roster change36.0 wins
- 25 Aug0.00 · roster change36.0 wins
- 26 Aug0.00 · roster change36.0 wins
- 27 Aug+0.99 · roster change37.0 wins
- 28 Aug-2.97 · roster change34.0 wins
- 29 Aug0.00 · roster change34.0 wins
- 30 Aug-0.02 · roster change34.0 wins
- 31 Aug+2.00 · roster change36.0 wins
- 1 Sept-2.22 · roster change33.8 wins
- 2 Sept0.00 · roster change33.8 wins
- 3 Sept0.00 · roster change33.8 wins
- 4 Sept+0.02 · roster change33.8 wins
- 6 Sept0.00 · roster change33.8 wins
- 8 Sept-0.01 · roster change33.8 wins
- 9 Sept0.00 · roster change33.8 wins
- 10 Sept0.00 · roster change33.8 wins
- 11 Sept0.00 · roster change33.8 wins
- 12 Sept-0.02 · roster change33.8 wins
- 14 Sept-0.06 · roster change33.7 wins
- 15 Sept0.00 · roster change33.7 wins
- 16 Sept+0.04 · roster change33.8 wins
- 17 Sept0.00 · roster change33.8 wins
- 18 Sept0.00 · roster change33.8 wins
- 19 Sept0.00 · roster change33.8 wins
- 20 Sept0.00 · roster change33.8 wins
- 24 Sept+0.06 · trigger not stated33.8 wins
- 25 Sept+0.02 · roster change33.8 wins
- 26 Sept+0.01 · roster change33.8 wins
- 27 Sept-0.02 · roster change33.8 wins
- 28 Sept+0.03 · roster change33.9 wins
- 29 Sept+0.34 · roster change34.2 wins
- 30 Sept+0.01 · roster change34.2 wins
- 1 Oct-0.40 · roster change33.8 wins
- 2 Oct+0.30 · roster change34.1 wins
- 3 Oct-0.27 · roster change33.8 wins
- 4 Oct0.00 · roster change33.8 wins
- 5 Oct+0.41 · roster change34.2 wins
- 6 Oct0.00 · roster change34.2 wins
- 7 Oct0.00 · roster change34.2 wins
- 8 Oct+0.03 · roster change34.3 wins
- 9 Oct+0.10 · roster change34.4 wins
- 11 Oct+0.03 · roster change34.4 wins
- 12 Oct-0.12 · roster change34.3 wins
- 13 Oct0.00 · trigger not stated34.3 wins
- 14 Oct-0.39 · roster change33.9 wins
- 15 Oct-0.01 · roster change33.9 wins
- 16 Oct0.00 · roster change33.9 wins
- 17 Oct-0.02 · roster change33.9 wins
- 18 Oct-0.10 · roster change33.8 wins
- 19 Oct+0.26 · roster change34.0 wins
- 20 Oct-2.35 · roster change31.7 wins
- 21 Oct0.00 · roster change31.7 wins
- 22 Oct+0.03 · roster change31.7 wins
- 23 Oct-2.59 · roster change29.1 wins
- 24 Oct+0.03 · roster change29.1 wins
- 25 Oct-2.23 · roster change26.9 wins
- 26 Oct-0.21 · roster change26.7 wins
- 27 Oct-0.07 · roster change26.6 wins
- 28 Oct+2.63 · roster change29.3 wins
- 29 Oct+0.05 · roster change29.3 wins
- 30 Oct-4.18 · roster change25.1 wins
- 31 Oct+0.01 · roster change25.1 wins
- 1 Nov-0.37 · roster change24.8 wins
- 2 Nov-1.72 · roster change23.1 wins
- 3 Nov-0.11 · roster change22.9 wins
- 4 Nov+0.64 · roster change23.6 wins
- 5 Nov+0.02 · roster change23.6 wins
- 6 Nov+0.67 · roster change24.3 wins
- 7 Nov-0.58 · roster change23.7 wins
This is how the model has done in other years
Milwaukee would win about 24 games; the model gives it a margin of 13 to 34 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: 13–34. Coverage of this forecasting procedure has not yet been validated.
Coverage of this forecasting procedure has not yet been validated.
- worse: 13 · wins · Nominal 80% range
- better: 34 · 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 Milwaukee Bucks 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
Milwaukee Bucks: 23.7 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