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Columbus Crew vs. Orlando City Prediction, Odds, Picks, and MLS Season Pass Discount Code [7/25/2025]

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Written by Jason Bevilacqua

Our expert prediction for Friday's Columbus Crew vs Orlando City matchup.

Columbus Crew-Orlando City Predictions and Game Preview.
Lower.com Field sets the stage for the MLS matchup between Columbus Crew and Orlando City this Friday.

Columbus will face Orlando in MLS action at Lower.com Field in Columbus, Ohio on Friday, beginning at 7:30PM ET.

Based on updated simulations, Dimers' proven MLS model (see Dimers Pro for full access) predicts Columbus as the most likely winner of today's game.

DraftKings MLS Season Pass Promo Code.
This deal unlocks free MLS Season Pass for the entire season, a $99 value, when you make any $5 MLS bet on DraftKings.

For expanded analysis of Friday's matchup, including best bets and picks, visit our interactive Columbus vs. Orlando predictions page.

Columbus Crew vs. Orlando City Prediction: Who Will Win?

Using innovative machine learning and statistical analysis, we have simulated the outcome of Friday's MLS matchup between Columbus and Orlando 10,000 times as part of our MLS predictions coverage.

Our independent predictive model currently suggests a 47.3% chance of Columbus winning, a 30.1% chance for Orlando, and a 22.6% chance of a draw.

Additionally, the over/under total of 2.5 goals has a 64% chance of going over, according to our model.

 

Columbus Crew vs. Orlando City Odds

We have sourced the best MLS odds in America for this game, which are listed here:

Moneyline

Columbus Orlando Draw
+120 +200 +260

Total Goals

Over 2.5 Under 2.5
-175 +125

All odds are correct at the time of publication and are subject to change.

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Columbus Crew vs. Orlando City Picks and Best Bets

Our model's strongest edge in today's Columbus Crew vs. Orlando City matchup is on the moneyline.

Our expert predictions, matched against the latest odds, reveal the best MLS picks and MLS best bets for every game throughout the season.

Unlimited access to our full set of picks, including this one, is available via Dimers Pro.


Columbus Crew vs. Orlando City: Correct Score Predictions

Here are the top three most likely final scores according to our model, with a 1-1 draw being the most probable:

Final Score Probability
COL 1-1 ORL 9.9%
COL 2-1 ORL 9.2%
COL 1-2 ORL 7.1%

These predictions are based on each team's average score after 10,000 simulations, meaning the most likely correct score may differ from our predicted winner.

Columbus Crew vs. Orlando City Game-Day Updates and Essential Details

Friday's matchup between Columbus and Orlando in MLS at Lower.com Field is scheduled to begin at 7:30PM ET.

  • Who: Columbus Crew vs. Orlando City
  • Date: Friday, July 25, 2025
  • Time: 7:30PM ET/4:30PM PT
  • Venue: Lower.com Field (Columbus, Ohio)

Dimers.com's full preview of Friday's Columbus vs. Orlando matchup includes our prediction, picks and the latest betting odds.

Before making any Orlando vs. Columbus picks, be sure to check out the latest MLS predictions and betting advice from Dimers Pro.

Conclusion

According to our computer model, Columbus has a 47.3% win probability on Friday, Orlando has a 30.1% win probability, and there is a 22.6% chance that the game will end in a draw.

AI and automation have enhanced this article to quickly deliver accurate Columbus vs. Orlando insights, with human oversight ensuring high editorial quality. Our predictions are drawn from up-to-date data to help you make informed decisions. For additional resources and advice on responsible gambling, please call 1-800-GAMBLER.

Note: Clicking links to our partners may earn us a referral fee. Learn about how we review products and services.

More on MLS

Keep up with the latest MLS betting news and parlay picks throughout the season.

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Written by
Jason Bevilacqua
Head of Content and Communities

Jason Bevilacqua, an expert in MLB, NHL, NBA, MLS, and NFL, delivers game previews, best bets, and props. Since 2020, as Head of Social and Community at Dimers, he has contributed insightful articles utilizing data-driven models and simulations.

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