NBA (National Basketball Association) · Tuesday, 3 November, MSK

Los Angeles Clippers — Toronto Raptors

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Model prediction for 3 November

Los Angeles Clippers48%
Toronto Raptors52%
Model estimate at MSK

Preliminary forecast: the match is more than a week away. Closer to it the model takes in fresh form, injuries and line-ups, and the numbers may move.

In short

Evenly matched: Los Angeles Clippers 48%, Toronto Raptors 52%.

The model expects a score around 113:113 — 226 points in total.

Over 225.5 points (incl. overtime) — 50%.

Why

  • Los Angeles Clippers without Brandon Ingram, Jordan Miller, Max Strus: that costs the team about 5.8 points a game.
  • Los Angeles Clippers play the second night of a back-to-back: in NBA history that is worth about 1.7 points of margin.

Probabilities

Expected points (incl. overtime): Los Angeles Clippers — Toronto Raptors112.5–113.4
Total over 225.5 (incl. OT)50%
Total under 225.5 (incl. OT)50%

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All totals and handicaps, team totals, the regulation 1X2, who may miss the game, every factor and how the estimate moved before kick-off.

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  • Toronto Raptors points
  • Regulation 1X2
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Form

Los Angeles Clippers

  • 16.04Golden State Warriors121:126
  • 13.04Golden State Warriors115:110
  • 11.04away · Portland Trail Blazers97:116
  • 09.04Oklahoma City Thunder110:128
  • 08.04Dallas Mavericks116:103

Toronto Raptors

  • 04.05away · Cleveland Cavaliers102:114
  • 02.05Cleveland Cavaliers112:110
  • 30.04away · Cleveland Cavaliers120:125
  • 26.04Cleveland Cavaliers93:89
  • 24.04Cleveland Cavaliers126:104

Head to head

  • 26.03.2026Los Angeles Clippers — Toronto Raptors119:94
  • 17.01.2026Toronto Raptors — Los Angeles Clippers117:121 OT
  • 02.02.2025Toronto Raptors — Los Angeles Clippers115:108
  • 10.11.2024Los Angeles Clippers — Toronto Raptors105:103
  • 27.01.2024Toronto Raptors — Los Angeles Clippers107:127

Full record: 14 meetings →

NBA on the same day

This is the model’s statistical estimate, not a recommendation. An outcome at 52% will not happen in roughly 48 matches out of 100. How to read probabilities →