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

Cleveland Cavaliers — Oklahoma City Thunder

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Model prediction for 3 November

Cleveland Cavaliers39%
Oklahoma City Thunder61%
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

Oklahoma City Thunder are clear favourites: 61% against 39% for the opponent.

The model expects a score around 112:116 — 228 points in total.

Over 228.5 points (incl. overtime) — 49%.

Why

  • Pace: Cleveland Cavaliers 98.2, Oklahoma City Thunder 99.4 possessions per 48 minutes.

Probabilities

Expected points (incl. overtime): Cleveland Cavaliers — Oklahoma City Thunder112.3–116.1
Total over 228.5 (incl. OT)49%
Total under 228.5 (incl. OT)51%

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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.

  • All handicaps
  • All totals
  • Cleveland Cavaliers points
  • Oklahoma City Thunder points
  • Regulation 1X2
  • Who may miss the game
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Form

Cleveland Cavaliers

  • 26.05New York Knicks93:130
  • 24.05New York Knicks108:121
  • 22.05away · New York Knicks93:109
  • 20.05away · New York Knicks104:115
  • 18.05away · Detroit Pistons125:94

Oklahoma City Thunder

  • 31.05San Antonio Spurs103:111
  • 29.05away · San Antonio Spurs91:118
  • 27.05San Antonio Spurs127:114
  • 25.05away · San Antonio Spurs82:103
  • 23.05away · San Antonio Spurs123:108

Head to head

  • 22.02.2026Oklahoma City Thunder — Cleveland Cavaliers121:113
  • 19.01.2026Cleveland Cavaliers — Oklahoma City Thunder104:136
  • 17.01.2025Oklahoma City Thunder — Cleveland Cavaliers134:114
  • 09.01.2025Cleveland Cavaliers — Oklahoma City Thunder129:122
  • 09.11.2023Oklahoma City Thunder — Cleveland Cavaliers128:120

Full record: 14 meetings →

NBA on the same day

This is the model’s statistical estimate, not a recommendation. An outcome at 61% will not happen in roughly 39 matches out of 100. How to read probabilities →