Forecast NBA 2026-27Utah Jazz
● Updated · 7 Nov
Utah holds at 22 wins.
Keyonte George
Jaxson Hayes is the player who weighs most in this projection: +0.5 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 |
|---|---|---|---|
| Keyonte George | 27.8 | 73.6 | 2,032 |
| Ace Bailey | 23.5 | 76.0 | 1,772 |
| Lauri Markkanen | 27.1 | 64.2 | 1,727 |
| Isaiah Collier | 21.0 | 73.0 | 1,522 |
| Darryn Peterson | 23.6 | 64.6 | 1,512 |
| Brice Sensabaugh | 19.4 | 73.6 | 1,415 |
| Jaxson Hayes | 18.9 | 65.5 | 1,227 |
| Jaren Jackson Jr. | 23.5 | 50.6 | 1,179 |
| Kyle Filipowski | 18.5 | 60.8 | 1,115 |
| Svi Mykhailiuk | 16.6 | 66.6 | 1,095 |
| Josh Okogie | 15.3 | 65.4 | 996 |
| Josh Green | 14.3 | 59.3 | 839 |
| Jusuf Nurkic | 19.8 | 39.9 | 782 |
| Mo Bamba | 13.9 | 37.8 | 521 |
| Tony Bradley | 8.1 | 31.2 | 251 |
| Trey Alexander | 12.3 | 7.0 | 85 |
| Kobe Bufkin | 7.2 | 6.5 | 46 |
| Harrison Ingram | 6.5 | 5.3 | 34 |
- Allocated minutes
- 18,150
- Not assigned to players
- 1,530
- 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 |
|---|---|---|---|
| Keyonte George | 100.0 % | 73.6 | History and team context |
| Ace Bailey | 100.0 % | 76.0 | History and team context |
| Lauri Markkanen | 100.0 % | 64.2 | History and team context |
| Isaiah Collier | 100.0 % | 73.0 | History and team context |
| Darryn Peterson | 100.0 % | 64.6 | Historical average by draft band |
| Brice Sensabaugh | 100.0 % | 73.6 | History and team context |
| Jaxson Hayes | 100.0 % | 65.5 | History and team context |
| Jaren Jackson Jr. | 100.0 % | 50.6 | History and team context |
| Kyle Filipowski | 100.0 % | 60.8 | History and team context |
| Svi Mykhailiuk | 100.0 % | 66.6 | History and team context |
| Josh Okogie | 100.0 % | 65.4 | History and team context |
| Josh Green | 100.0 % | 59.3 | History and team context |
| Jusuf Nurkic | 81.7 % | 48.8 | History and team context |
| Mo Bamba | 100.0 % | 37.8 | History before the return |
| Tony Bradley | 100.0 % | 31.2 | History and team context |
| Trey Alexander | 24.8 % | 28.1 | History and team context |
| Kobe Bufkin | 24.8 % | 26.1 | History and team context |
| Harrison Ingram | 24.8 % | 21.3 | History and team context |
Since the first version, on 14 Aug, the projection has moved from 29.5 to 22.0 wins.
See every version
- 14 Aug29.5 wins
- 21 Aug+0.35 · trigger not stated29.9 wins
- 22 Aug0.00 · roster change29.9 wins
- 24 Aug-1.19 · roster change28.7 wins
- 25 Aug0.00 · roster change28.7 wins
- 26 Aug+0.02 · roster change28.7 wins
- 27 Aug-0.38 · roster change28.3 wins
- 28 Aug-0.18 · roster change28.1 wins
- 29 Aug0.00 · roster change28.1 wins
- 30 Aug+0.69 · roster change28.8 wins
- 31 Aug+0.01 · roster change28.8 wins
- 1 Sept+1.51 · roster change30.3 wins
- 2 Sept0.00 · roster change30.3 wins
- 3 Sept0.00 · roster change30.3 wins
- 4 Sept+0.01 · roster change30.3 wins
- 6 Sept0.00 · roster change30.3 wins
- 8 Sept-0.02 · roster change30.3 wins
- 9 Sept0.00 · roster change30.3 wins
- 10 Sept0.00 · roster change30.3 wins
- 11 Sept0.00 · roster change30.3 wins
- 12 Sept-0.02 · roster change30.3 wins
- 14 Sept+0.24 · roster change30.5 wins
- 15 Sept0.00 · roster change30.5 wins
- 16 Sept+0.01 · roster change30.6 wins
- 17 Sept+0.01 · roster change30.6 wins
- 18 Sept0.00 · roster change30.6 wins
- 19 Sept0.00 · roster change30.6 wins
- 20 Sept0.00 · roster change30.6 wins
- 24 Sept+1.21 · trigger not stated31.8 wins
- 25 Sept+0.05 · roster change31.8 wins
- 26 Sept+0.02 · roster change31.8 wins
- 27 Sept-0.02 · roster change31.8 wins
- 28 Sept0.00 · roster change31.8 wins
- 29 Sept+0.07 · roster change31.9 wins
- 30 Sept+0.01 · roster change31.9 wins
- 1 Oct-0.55 · roster change31.4 wins
- 2 Oct-0.18 · roster change31.2 wins
- 3 Oct-0.10 · roster change31.1 wins
- 4 Oct0.00 · roster change31.1 wins
- 5 Oct+0.88 · roster change31.9 wins
- 6 Oct0.00 · roster change31.9 wins
- 7 Oct0.00 · roster change31.9 wins
- 8 Oct-0.01 · roster change31.9 wins
- 9 Oct+0.02 · roster change32.0 wins
- 11 Oct+0.02 · roster change32.0 wins
- 12 Oct0.00 · roster change32.0 wins
- 13 Oct0.00 · trigger not stated32.0 wins
- 14 Oct+0.04 · roster change32.0 wins
- 15 Oct-0.01 · roster change32.0 wins
- 16 Oct0.00 · roster change32.0 wins
- 17 Oct0.00 · roster change32.0 wins
- 18 Oct-0.39 · roster change31.6 wins
- 19 Oct-0.38 · roster change31.2 wins
- 20 Oct-0.07 · roster change31.2 wins
- 21 Oct0.00 · roster change31.2 wins
- 22 Oct+0.02 · roster change31.2 wins
- 23 Oct-4.11 · roster change27.1 wins
- 24 Oct+0.02 · roster change27.1 wins
- 25 Oct+0.69 · roster change27.8 wins
- 26 Oct-0.04 · roster change27.8 wins
- 27 Oct-0.52 · roster change27.2 wins
- 28 Oct-1.18 · roster change26.1 wins
- 29 Oct-0.10 · roster change25.9 wins
- 30 Oct-0.38 · roster change25.6 wins
- 31 Oct+0.15 · roster change25.7 wins
- 1 Nov-0.37 · roster change25.4 wins
- 2 Nov-1.72 · roster change23.6 wins
- 3 Nov-0.10 · roster change23.5 wins
- 4 Nov-0.81 · roster change22.7 wins
- 5 Nov-0.10 · roster change22.6 wins
- 6 Nov+0.22 · roster change22.8 wins
- 7 Nov-0.82 · roster change22.0 wins
This is how the model has done in other years
Utah would win about 22 games; the model gives it a margin of 11 to 32 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: 11–32. Coverage of this forecasting procedure has not yet been validated.
Coverage of this forecasting procedure has not yet been validated.
- worse: 11 · wins · Nominal 80% range
- better: 32 · 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 Utah Jazz 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
Utah Jazz: 22.0 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