NBA (National Basketball Association) · Saturday, 31 October, MSK

Minnesota Timberwolves — Los Angeles Clippers

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Model prediction for 31 October

Minnesota Timberwolves52%
Los Angeles Clippers48%
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: Minnesota Timberwolves 52%, Los Angeles Clippers 48%.

The model expects a score around 116:115 — 231 point in total.

Over 230.5 points (incl. overtime) — 50%.

Why

  • Minnesota Timberwolves without Donte DiVincenzo: that costs the team about 2.1 points a game.
  • Los Angeles Clippers without Brandon Ingram, Jordan Miller, Max Strus: that costs the team about 5.8 points a game.

Probabilities

Expected points (incl. overtime): Minnesota Timberwolves — Los Angeles Clippers115.8–115.1
Total over 230.5 (incl. OT)50%
Total under 230.5 (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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Form

Minnesota Timberwolves

  • 16.05San Antonio Spurs109:139
  • 13.05away · San Antonio Spurs97:126
  • 11.05San Antonio Spurs114:109
  • 09.05San Antonio Spurs108:115
  • 07.05away · San Antonio Spurs95:133

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

Head to head

  • 12.03.2026Los Angeles Clippers — Minnesota Timberwolves153:128
  • 27.02.2026Los Angeles Clippers — Minnesota Timberwolves88:94
  • 08.02.2026Minnesota Timberwolves — Los Angeles Clippers96:115
  • 07.12.2025Minnesota Timberwolves — Los Angeles Clippers109:106
  • 07.01.2025Minnesota Timberwolves — Los Angeles Clippers108:106

Full record: 25 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 →