Timberwolves vs. Warriors Game 3 Results According to NBA 2K25

According to our NBA 2K25 simulation, the Minnesota Timberwolves will defeat the Golden State Warriors in Game 3, 115-103. The Timberwolves slowly built a steady lead throughout the contest. At one point they were up 17 points. Fortunately they didn’t need to look back as the Warriors were never close enough to make a comeback attempt.

Anthony Edwards scored 39 points while earning eight rebounds, and three assists. Naz Reid also played very well, scoring 20 points in just 28 minutes, along with five rebounds, one assist, and six steals. Overall, he accounted for half of the team’s steals in the win. Julius Randle scored 17 points while earning 10 rebounds and three assists.

Buddy Hield led the Warriors with 22 points. Additionally, he earned 4 rebounds, two assists, and one steal. Jimmy Butler scored 20 points while earning nine rebounds, six assists, and three steals in the loss. However, nobody else on the team recorded more than 16 points as the Warriors’ offense faltered. They’ll need to improve on defense as well moving forward.

Additionally, check out some of game stats:

With the win, the Timberwolves take a 2-1 lead in the series. The team rebounded from an ugly game 1 loss and responded with back-to-back wins. And with Curry out for some time, they certainly need to take advantage of the situation. They play one more game away before heading back home. We’ll see if they can end this series back there in Game 5.

Meanwhile, Warriors now trail 1-2 in this series. While they managed to get by in Game 1 without Steph Curry, it’ becoming clear that they can’t win the series without him. The offense isn’t as effective, and they can’t keep up with the Wolves. But they still have one more game at home. Perhaps they can tie it back up before heading back to Minnesota. We’ll see if they can do so in Game 4 and beyond.

That wraps up our Minnesota Timberwolves vs. Golden State Warriors Game 3 results according to NBA 2K25. We hope you enjoyed our simulation. These sims also provide a way for us to improve these predictions by experimenting with CPU sliders. We still want to improve a few things, but we’re getting more satisfied with each sim. We hope to create more accurate sims in the future!

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