Forecast NBA 2026-27San Antonio Spurs
● Updated · 7 Nov
San Antonio drops from 62 to 55 wins.
Victor Wembanyama
Victor Wembanyama is the player who weighs most in this projection: +9.9 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 |
|---|---|---|---|
| Victor Wembanyama | 28.6 | 72.8 | 2,070 |
| Stephon Castle | 25.0 | 76.1 | 1,893 |
| De'Aaron Fox | 25.1 | 74.1 | 1,843 |
| Devin Vassell | 24.4 | 73.9 | 1,788 |
| Julian Champagnie | 21.9 | 76.7 | 1,666 |
| Dylan Harper | 21.1 | 74.0 | 1,547 |
| Keldon Johnson | 19.1 | 74.9 | 1,423 |
| Luke Kornet | 16.0 | 70.6 | 1,120 |
| Harrison Barnes | 17.4 | 63.4 | 1,093 |
| Tobias Harris | 20.1 | 51.0 | 1,016 |
| Carter Bryant | 11.4 | 66.9 | 754 |
| Tarris Reed Jr. | 11.1 | 45.3 | 501 |
| Jayden Quaintance | 13.4 | 32.9 | 438 |
| Ja'Kobi Gillespie | 10.2 | 30.7 | 310 |
| Jordan McLaughlin | 7.5 | 37.7 | 282 |
| Maliq Brown | 10.4 | 25.9 | 266 |
| David Jones Garcia | 6.4 | 22.2 | 140 |
- 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 |
|---|---|---|---|
| Victor Wembanyama | 100.0 % | 72.8 | History and team context |
| Stephon Castle | 100.0 % | 76.1 | History and team context |
| De'Aaron Fox | 100.0 % | 74.1 | History and team context |
| Devin Vassell | 100.0 % | 73.9 | History and team context |
| Julian Champagnie | 100.0 % | 76.7 | History and team context |
| Dylan Harper | 100.0 % | 74.0 | History and team context |
| Keldon Johnson | 100.0 % | 74.9 | History and team context |
| Luke Kornet | 100.0 % | 70.6 | History and team context |
| Harrison Barnes | 100.0 % | 63.4 | History and team context |
| Tobias Harris | 93.6 % | 54.5 | History and team context |
| Carter Bryant | 100.0 % | 66.9 | History and team context |
| Tarris Reed Jr. | 100.0 % | 45.3 | Historical average by draft band |
| Jayden Quaintance | 85.8 % | 38.3 | Historical average by draft band |
| Ja'Kobi Gillespie | 100.0 % | 30.7 | Historical average by draft band |
| Jordan McLaughlin | 100.0 % | 37.7 | History and team context |
| Maliq Brown | 100.0 % | 25.9 | Historical average by draft band |
| David Jones Garcia | 100.0 % | 22.2 | History and team context |
Since the first version, on 14 Aug, the projection has moved from 53.6 to 54.6 wins.
See every version
- 14 Aug53.6 wins
- 21 Aug+0.30 · trigger not stated53.9 wins
- 22 Aug0.00 · roster change53.9 wins
- 24 Aug+0.14 · roster change54.1 wins
- 25 Aug0.00 · roster change54.1 wins
- 26 Aug0.00 · roster change54.1 wins
- 27 Aug-0.37 · roster change53.7 wins
- 28 Aug-1.26 · roster change52.4 wins
- 29 Aug+0.01 · roster change52.5 wins
- 30 Aug-0.02 · roster change52.4 wins
- 31 Aug+1.65 · roster change54.1 wins
- 1 Sept-0.13 · roster change54.0 wins
- 2 Sept0.00 · roster change54.0 wins
- 3 Sept0.00 · roster change54.0 wins
- 4 Sept+0.01 · roster change54.0 wins
- 6 Sept0.00 · roster change54.0 wins
- 8 Sept-0.02 · roster change53.9 wins
- 9 Sept+0.01 · roster change54.0 wins
- 10 Sept-0.01 · roster change53.9 wins
- 11 Sept0.00 · roster change53.9 wins
- 12 Sept-0.01 · roster change53.9 wins
- 14 Sept+0.15 · roster change54.1 wins
- 15 Sept0.00 · roster change54.1 wins
- 16 Sept+0.01 · roster change54.1 wins
- 17 Sept+0.01 · roster change54.1 wins
- 18 Sept0.00 · roster change54.1 wins
- 19 Sept0.00 · roster change54.1 wins
- 20 Sept0.00 · roster change54.1 wins
- 24 Sept0.00 · trigger not stated54.1 wins
- 25 Sept+0.04 · roster change54.1 wins
- 26 Sept+0.02 · roster change54.2 wins
- 27 Sept-0.02 · roster change54.1 wins
- 28 Sept+0.03 · roster change54.2 wins
- 29 Sept-0.31 · roster change53.9 wins
- 30 Sept+0.01 · roster change53.9 wins
- 1 Oct+0.45 · roster change54.3 wins
- 2 Oct+0.16 · roster change54.5 wins
- 3 Oct-0.12 · roster change54.4 wins
- 4 Oct0.00 · roster change54.4 wins
- 5 Oct-0.45 · roster change53.9 wins
- 6 Oct0.00 · roster change53.9 wins
- 7 Oct0.00 · roster change53.9 wins
- 8 Oct0.00 · roster change53.9 wins
- 9 Oct+0.01 · roster change53.9 wins
- 11 Oct+0.02 · roster change53.9 wins
- 12 Oct0.00 · roster change53.9 wins
- 13 Oct0.00 · trigger not stated53.9 wins
- 14 Oct-0.10 · roster change53.8 wins
- 15 Oct+0.31 · roster change54.1 wins
- 16 Oct0.00 · roster change54.1 wins
- 17 Oct-0.40 · roster change53.8 wins
- 18 Oct+0.42 · roster change54.2 wins
- 19 Oct-0.35 · roster change53.8 wins
- 20 Oct-0.08 · roster change53.7 wins
- 21 Oct0.00 · roster change53.7 wins
- 22 Oct-2.66 · roster change51.1 wins
- 23 Oct-0.46 · roster change50.6 wins
- 24 Oct+0.03 · roster change50.6 wins
- 25 Oct-1.26 · roster change49.4 wins
- 26 Oct+2.20 · roster change51.6 wins
- 27 Oct-0.18 · roster change51.4 wins
- 28 Oct-2.49 · roster change48.9 wins
- 29 Oct+3.02 · roster change51.9 wins
- 30 Oct+0.54 · roster change52.5 wins
- 31 Oct+0.06 · roster change52.5 wins
- 1 Nov+0.04 · roster change52.6 wins
- 2 Nov+1.52 · roster change54.1 wins
- 3 Nov-0.43 · roster change53.7 wins
- 4 Nov+1.09 · roster change54.8 wins
- 5 Nov+0.33 · roster change55.1 wins
- 6 Nov-0.73 · roster change54.4 wins
- 7 Nov+0.28 · roster change54.6 wins
This is how the model has done in other years
San Antonio would win about 55 games; the model gives it a margin of 44 to 65 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: 44–65. Coverage of this forecasting procedure has not yet been validated.
Coverage of this forecasting procedure has not yet been validated.
- worse: 44 · wins · Nominal 80% range
- better: 65 · 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 San Antonio Spurs 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
San Antonio Spurs: 54.6 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