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Wed 28 Oct, 11:00 Sydney

Detroit Pistons at New York Knicks

Near even. Logistic regression is the primary probability because it had the best holdout log loss. The largest contributions toward New York Knicks are Net-rating gap and Away absences. Other rating features can point the other way when this one already carries the same information.

48%
52%

Model agreement

Three separate probabilities. There is no combined model. Home win chance:

Logistic regression · primary

52%

DET 48%

Gradient boosting

37%

DET 63%

Elo

44%

DET 56%

These home probabilities differ by at least 10 points.

What the logistic model is using

Each number is that feature’s push, in log-odds, after scaling. The model starts from a baseline home log-odds of +0.30. Positive pushes favor New York Knicks. This is not an estimate of what would happen if one statistic changed.

Toward NYK

  • Net-rating gap+0.28

    season net rating, home minus away

  • Offensive-rating gap+0.25

    season points scored per 100 possessions, home minus away

  • Away absences+0.22

    away players from the recent roster projected out

  • Home key absences+0.16

    home players with 20+ expected minutes projected out

Toward DET

  • Blended net rating-0.48

    season net rating blended with last year, home minus away

  • Shooting gap-0.23

    effective field-goal percentage, home minus away

  • Rotation-impact gap-0.22

    impact of the players projected to play, home minus away

  • Home absences-0.16

    home players from the recent roster projected out

NYK offence against DET defence

Season-to-date rates. The last row pairs the offence’s offensive rebound rate with the defence’s own defensive rebound rate.

MetricNYK offenceDET defence
Points per 100102.3105.7
Effective FG47.6%48.0%
Turnover rate16.4%12.3%
Offensive boards / defensive boards26.6%74.7%

DET offence against NYK defence

Season-to-date rates. The last row pairs the offence’s offensive rebound rate with the defence’s own defensive rebound rate.

MetricDET offenceNYK defence
Points per 100118.3108.6
Effective FG56.3%51.9%
Turnover rate18.0%13.1%
Offensive boards / defensive boards32.3%80.0%

Pace and schedule

Season pace describes how many possessions a team usually plays. The average below is only that description. It is not added on top of the win probability, and it is not a predicted score.

DET pace

100.0

NYK pace

99.4

Average of the two

99.7

DET

Rest days 1

Not a back-to-back

Games in the last 7 days 3

Last 10 net rating +12.7

Free throws per shot 0.23

NYK

Rest days 1

Not a back-to-back

Games in the last 7 days 3

Last 10 net rating -6.4

Free throws per shot 0.19

Projected rotation

Injury report 27 October 2026, 7:00 AM ET. Players ruled out are removed from the win probability. Questionable and doubtful players stay on the last-game assumption and are listed with that status. Last games used are 2026-10-25 and 2026-10-25.

Detroit Pistons

Last played 2026-10-25 · 2 key players projected out

PlayerLast minExpectedImpactStatus
Daniss Jenkins3827-1.8—
John Collins3426+3.4—
Cade Cunningham3327+8.0—
Duncan Robinson3227+7.3—
Kevin Huerter2624+2.5—
Ronald Holland II · fewer minutes2318-4.5—
Paul Reed · fewer minutes2317-0.6—
Javonte Green · fewer minutes2216-0.8—
Isaiah Joe · fewer minutes415-1.4Questionable
Tolu Smith · fewer minutes36-8.3—
Elijah Harkless———Questionable
Isaac Jones———Questionable
Ausar Thompson———Questionable
Jalen Duren · ruled out———Out
Ugonna Onyenso · ruled out———Out

New York Knicks

Last played 2026-10-25 · 0 key players projected out

PlayerLast minExpectedImpactStatus
Mikal Bridges3528-1.8—
Josh Hart3531-7.0—
OG Anunoby3533+3.3—
Karl-Anthony Towns3331+4.0—
Jalen Brunson3235-2.2—
Landry Shamet · fewer minutes2222+2.6—
Tyler Kolek · fewer minutes159-4.3—
Miles McBride · fewer minutes1319+6.5—
Andre Drummond · fewer minutes718-6.1—
James Wiseman · fewer minutes717-6.0—
Jose Alvarado · ruled out———Out