SportiveWorld

Forecast NBA 2026-27Chicago Bulls

Updated · 7 Nov

Chicago drops from 31 to 20 wins.

19.7projected wins9–30forecast interval31wins in 2025-26
projected winsforecast interval2025-26
Josh Giddey

Josh Giddey

Tre Jones is the player who weighs most in this projection: +1.9 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

PlayerMin/gameExpected gamesSeason minutes
Josh Giddey28.972.82,091
Matas Buzelis26.477.12,017
Norman Powell25.069.21,718
Tre Jones24.371.01,715
Caleb Wilson24.863.41,561
Isaac Okoro20.971.31,481
Jalen Smith19.968.21,345
Leonard Miller16.962.61,051
Buddy Hield13.865.8902
Zach Collins13.450.2667
Patrick Williams17.535.4613
Jaylin Sellers12.248.1584
Tobe Awaka12.643.0537
Jordan Hawkins11.345.7514
Noa Essengue10.447.2490
Dailyn Swain14.232.8463
Nic Claxton24.415.7382
Allocated minutes
18,131
Not assigned to players
1,549
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
PlayerProbability of an opening appearanceGames conditional on an opening appearanceMinutes method
Josh Giddey100.0 %72.8History and team context
Matas Buzelis100.0 %77.1History and team context
Norman Powell100.0 %69.2History and team context
Tre Jones100.0 %71.0History and team context
Caleb Wilson100.0 %63.4Historical average by draft band
Isaac Okoro100.0 %71.3History and team context
Jalen Smith100.0 %68.2History and team context
Leonard Miller100.0 %62.6History and team context
Buddy Hield100.0 %65.8History and team context
Zach Collins100.0 %50.2History before the return
Patrick Williams100.0 %35.4History and team context
Jaylin Sellers100.0 %48.1History and team context
Tobe Awaka100.0 %43.0History and team context
Jordan Hawkins100.0 %45.7History and team context
Noa Essengue100.0 %47.2History and team context
Dailyn Swain100.0 %32.8Historical average by draft band
Nic Claxton93.6 %16.8History and team context

Since the first version, on 14 Aug, the projection has moved from 36.5 to 19.7 wins.

18.039.019.714 Aug7 Nov
See every version
  • 14 Aug36.5 wins
  • 21 Aug-0.16 · trigger not stated36.4 wins
  • 22 Aug0.00 · roster change36.4 wins
  • 24 Aug+1.33 · roster change37.7 wins
  • 25 Aug0.00 · roster change37.7 wins
  • 26 Aug+0.01 · roster change37.7 wins
  • 27 Aug-0.50 · roster change37.2 wins
  • 28 Aug+0.79 · roster change38.0 wins
  • 29 Aug0.00 · roster change38.0 wins
  • 30 Aug-0.02 · roster change38.0 wins
  • 31 Aug-0.36 · roster change37.6 wins
  • 1 Sept-1.34 · roster change36.3 wins
  • 2 Sept-0.01 · roster change36.3 wins
  • 3 Sept0.00 · roster change36.3 wins
  • 4 Sept+0.02 · roster change36.3 wins
  • 6 Sept0.00 · roster change36.3 wins
  • 8 Sept-0.01 · roster change36.3 wins
  • 9 Sept+0.01 · roster change36.3 wins
  • 10 Sept0.00 · roster change36.3 wins
  • 11 Sept0.00 · roster change36.3 wins
  • 12 Sept-0.03 · roster change36.2 wins
  • 14 Sept-0.07 · roster change36.2 wins
  • 15 Sept0.00 · roster change36.2 wins
  • 16 Sept+0.04 · roster change36.2 wins
  • 17 Sept0.00 · roster change36.2 wins
  • 18 Sept0.00 · roster change36.2 wins
  • 19 Sept0.00 · roster change36.2 wins
  • 20 Sept0.00 · roster change36.2 wins
  • 24 Sept+0.03 · trigger not stated36.2 wins
  • 25 Sept+0.02 · roster change36.3 wins
  • 26 Sept+0.01 · roster change36.3 wins
  • 27 Sept-0.02 · roster change36.3 wins
  • 28 Sept+0.90 · roster change37.1 wins
  • 29 Sept+0.01 · roster change37.2 wins
  • 30 Sept+0.03 · roster change37.2 wins
  • 1 Oct-0.13 · roster change37.1 wins
  • 2 Oct-0.17 · roster change36.9 wins
  • 3 Oct+0.20 · roster change37.1 wins
  • 4 Oct0.00 · roster change37.1 wins
  • 5 Oct+0.14 · roster change37.2 wins
  • 6 Oct0.00 · roster change37.2 wins
  • 7 Oct0.00 · roster change37.2 wins
  • 8 Oct-0.79 · roster change36.4 wins
  • 9 Oct-0.18 · roster change36.3 wins
  • 11 Oct+0.03 · roster change36.3 wins
  • 12 Oct0.00 · roster change36.3 wins
  • 13 Oct0.00 · trigger not stated36.3 wins
  • 14 Oct-0.14 · roster change36.1 wins
  • 15 Oct-0.01 · roster change36.1 wins
  • 16 Oct0.00 · roster change36.1 wins
  • 17 Oct-0.01 · roster change36.1 wins
  • 18 Oct-0.09 · roster change36.0 wins
  • 19 Oct0.00 · roster change36.0 wins
  • 20 Oct+0.16 · roster change36.2 wins
  • 21 Oct0.00 · roster change36.2 wins
  • 22 Oct-0.12 · roster change36.1 wins
  • 23 Oct-7.68 · roster change28.4 wins
  • 24 Oct+0.01 · roster change28.4 wins
  • 25 Oct+1.92 · roster change30.3 wins
  • 26 Oct-1.01 · roster change29.3 wins
  • 27 Oct-0.06 · roster change29.3 wins
  • 28 Oct-5.86 · roster change23.4 wins
  • 29 Oct+0.05 · roster change23.4 wins
  • 30 Oct+0.12 · roster change23.6 wins
  • 31 Oct-0.17 · roster change23.4 wins
  • 1 Nov-0.20 · roster change23.2 wins
  • 2 Nov+0.25 · roster change23.4 wins
  • 3 Nov-0.16 · roster change23.3 wins
  • 4 Nov-1.22 · roster change22.1 wins
  • 5 Nov-0.04 · roster change22.0 wins
  • 6 Nov-2.45 · roster change19.6 wins
  • 7 Nov+0.14 · roster change19.7 wins

This is how the model has done in other years

Chicago would win about 20 games; the model gives it a margin of 9 to 30 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

Forecast

Game by game: what Forecast expects from each Chicago Bulls game

Professional DNA

How the team behind that number actually plays

What if…?

What happened when its highest-impact player was missing
Technical detail

Uncertainty

Nominal 80% range: 9–30. Coverage of this forecasting procedure has not yet been validated.

Coverage of this forecasting procedure has not yet been validated.

  • worse: 9 · wins · Nominal 80% range
  • better: 30 · 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 Chicago Bulls 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

Chicago Bulls: 19.7 projected wins in 2026-27

19.7 winscompared against: 31 wins (-11.28 · -36 %) · Chicago Bulls in 2025-26, real wins

What has changed since the first version

19.7 winscompared against: 36.5 wins (-16.79 · -46 %) · Chicago Bulls, first version stored on 2026-08-14

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