SportiveWorld

Forecast NBA 2026-27New York Knicks

Updated · 7 Nov

New York drops from 53 to 45 wins.

45.5projected wins35–56forecast interval53wins in 2025-26
projected winsforecast interval2025-26
Jalen Brunson

Jalen Brunson

Karl-Anthony Towns is the player who weighs most in this projection: +2.8 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
Jalen Brunson30.474.62,255
Mikal Bridges28.176.42,129
OG Anunoby28.973.42,102
Karl-Anthony Towns27.873.72,034
Josh Hart25.870.01,793
Miles McBride22.368.11,505
Landry Shamet20.066.41,319
Andre Drummond16.466.51,080
Jose Alvarado17.448.8845
Jordan Clarkson13.261.0798
Tyler Kolek12.756.0706
Mohamed Diawara11.744.0511
James Wiseman11.735.0406
Dalton Knecht10.031.2311
Pacome Dadiet8.427.6229
Tyler Nickel9.711.0107
Allocated minutes
18,130
Not assigned to players
1,550
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
Jalen Brunson100.0 %74.6History and team context
Mikal Bridges100.0 %76.4History and team context
OG Anunoby100.0 %73.4History and team context
Karl-Anthony Towns100.0 %73.7History and team context
Josh Hart100.0 %70.0History and team context
Miles McBride100.0 %68.1History and team context
Landry Shamet100.0 %66.4History and team context
Andre Drummond100.0 %66.5History and team context
Jose Alvarado100.0 %48.8History and team context
Jordan Clarkson100.0 %61.0History and team context
Tyler Kolek100.0 %56.0History and team context
Mohamed Diawara100.0 %44.0History and team context
James Wiseman100.0 %35.0History before the return
Dalton Knecht100.0 %31.2History and team context
Pacome Dadiet100.0 %27.6History and team context
Tyler Nickel50.4 %21.9Historical average by draft band

Since the first version, on 14 Aug, the projection has moved from 44.9 to 45.5 wins.

37.049.045.514 Aug7 Nov
See every version
  • 14 Aug44.9 wins
  • 21 Aug-0.37 · trigger not stated44.5 wins
  • 22 Aug0.00 · roster change44.5 wins
  • 24 Aug+3.18 · roster change47.7 wins
  • 25 Aug0.00 · roster change47.7 wins
  • 26 Aug-0.01 · roster change47.7 wins
  • 27 Aug+0.20 · roster change47.9 wins
  • 28 Aug-3.51 · roster change44.4 wins
  • 29 Aug0.00 · roster change44.4 wins
  • 30 Aug-0.01 · roster change44.4 wins
  • 31 Aug+3.03 · roster change47.4 wins
  • 1 Sept-3.16 · roster change44.2 wins
  • 2 Sept0.00 · roster change44.2 wins
  • 3 Sept0.00 · roster change44.2 wins
  • 4 Sept+0.01 · roster change44.2 wins
  • 6 Sept0.00 · roster change44.2 wins
  • 8 Sept0.00 · roster change44.2 wins
  • 9 Sept0.00 · roster change44.2 wins
  • 10 Sept0.00 · roster change44.2 wins
  • 11 Sept0.00 · roster change44.2 wins
  • 12 Sept-0.03 · roster change44.2 wins
  • 14 Sept-0.20 · roster change44.0 wins
  • 15 Sept0.00 · roster change44.0 wins
  • 16 Sept+0.02 · roster change44.0 wins
  • 17 Sept0.00 · roster change44.0 wins
  • 18 Sept0.00 · roster change44.0 wins
  • 19 Sept+0.01 · roster change44.0 wins
  • 20 Sept0.00 · roster change44.0 wins
  • 24 Sept+0.02 · trigger not stated44.1 wins
  • 25 Sept+0.02 · roster change44.1 wins
  • 26 Sept+0.01 · roster change44.1 wins
  • 27 Sept-0.01 · roster change44.1 wins
  • 28 Sept+0.48 · roster change44.6 wins
  • 29 Sept-1.90 · roster change42.7 wins
  • 30 Sept+0.01 · roster change42.7 wins
  • 1 Oct+1.68 · roster change44.4 wins
  • 2 Oct+0.33 · roster change44.7 wins
  • 3 Oct-0.30 · roster change44.4 wins
  • 4 Oct0.00 · roster change44.4 wins
  • 5 Oct-2.06 · roster change42.3 wins
  • 6 Oct-0.29 · roster change42.0 wins
  • 7 Oct0.00 · roster change42.0 wins
  • 8 Oct+0.02 · roster change42.0 wins
  • 9 Oct+0.01 · roster change42.1 wins
  • 11 Oct+0.03 · roster change42.1 wins
  • 12 Oct0.00 · roster change42.1 wins
  • 13 Oct0.00 · trigger not stated42.1 wins
  • 14 Oct+0.14 · roster change42.2 wins
  • 15 Oct-0.02 · roster change42.2 wins
  • 16 Oct0.00 · roster change42.2 wins
  • 17 Oct0.00 · roster change42.2 wins
  • 18 Oct+0.19 · roster change42.4 wins
  • 19 Oct+1.84 · roster change44.2 wins
  • 20 Oct+0.03 · roster change44.3 wins
  • 21 Oct0.00 · roster change44.3 wins
  • 22 Oct-2.37 · roster change41.9 wins
  • 23 Oct-0.05 · roster change41.9 wins
  • 24 Oct+0.03 · roster change41.9 wins
  • 25 Oct-0.60 · roster change41.3 wins
  • 26 Oct+0.05 · roster change41.3 wins
  • 27 Oct-2.95 · roster change38.4 wins
  • 28 Oct+0.23 · roster change38.6 wins
  • 29 Oct+3.53 · roster change42.1 wins
  • 30 Oct+0.57 · roster change42.7 wins
  • 31 Oct-0.49 · roster change42.2 wins
  • 1 Nov-0.04 · roster change42.2 wins
  • 2 Nov+0.18 · roster change42.4 wins
  • 3 Nov+0.42 · roster change42.8 wins
  • 4 Nov+0.72 · roster change43.5 wins
  • 5 Nov+0.37 · roster change43.9 wins
  • 6 Nov+1.77 · roster change45.6 wins
  • 7 Nov-0.17 · roster change45.5 wins

This is how the model has done in other years

New York would win about 45 games; the model gives it a margin of 35 to 56 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 New York Knicks 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: 35–56. Coverage of this forecasting procedure has not yet been validated.

Coverage of this forecasting procedure has not yet been validated.

  • worse: 35 · wins · Nominal 80% range
  • better: 56 · 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 New York Knicks 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

New York Knicks: 45.5 projected wins in 2026-27

45.5 winscompared against: 53 wins (-7.53 · -14 %) · New York Knicks in 2025-26, real wins

What has changed since the first version

45.5 winscompared against: 44.9 wins (+0.59 · +1 %) · New York Knicks, 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