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Giants vs Royals Prediction and MLB Tips - 20 May 2025

The San Francisco Giants will face the Kansas City Royals in MLB action at Oracle Park on Tuesday, beginning at 11:45am AEST.

Robbie Ray (6-0, 3.04 ERA) will start for the Giants, up against Kris Bubic (4-2, 1.66 ERA) for the Royals.

This article features Stats Insider's prediction and tips for the Giants vs Royals game, plus the latest betting odds in Australia.

Who Will Win?

Utilising trusted computer power and data, Stats Insider has simulated the outcome of Tuesday's San Francisco vs Kansas City MLB game 10,000 times.

Our independent predictive analytics model gives the Giants a 54% chance of defeating the Royals at Oracle Park.

Giants vs Royals: Odds

The latest betting odds in Australia for Tuesday's MLB game at Oracle Park are listed below:

  • Head to Head: Giants $1.74, Royals $2.15
  • Line: Giants -1.5 ($2.60), Royals +1.5 ($1.53)
  • Total (Over/Under 7.5 Runs): Over $1.91, Under $1.91

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

Looking at the latest head-to-head odds, the bookmakers currently have the Giants at $1.74 and the Royals at $2.15.

The Giants are listed as 1.5-run favourites against the Royals, with odds of $2.60 available at TAB.

For the underdog Royals (+1.5) to cover the line, TAB offers odds of $1.53.

The over/under for total runs scored is set at 7.5 with TAB, which has odds of $1.91 for the over and $1.91 for the under.

According to Stats Insider's model, the Royals (+1.5) are predicted to cover the line 65% of the time, while the 7.5-run over/under is expected to stay under 56% of the time.

Giants vs Royals: Betting Tips

  • Head to Head: Kansas City at $2.15 with TAB
  • Line: Royals +1.5 at $1.53 with TAB
  • Total Runs: Under 7.5 at $1.91 with TAB

Today's Giants vs Royals betting tips are based on detailed simulations and gambling intelligence to help you place smarter bets with your chosen online bookie.

While the Giants have a higher chance of winning the game, betting on the Royals to win is our preferred option due to the 1.1% edge found when comparing our data-led probabilities to the odds currently available.

Making use of the edges published here at Stats Insider is crucial to achieving long-term success as a sports bettor.

Giants vs Royals: Prediction

Stats Insider provides full coverage of the San Francisco vs Kansas City game on Tuesday, including data-driven predictions and live win probabilitiestips.

Remember, our model updates regularly, so refresh this article for the latest betting analysis before the San Francisco vs Kansas City game.

As always, see Stats Insider's Best Bets for the best tips for every MLB game, plus predictions for a wide range of other sports.

Giants vs Royals: Essential Details

The game between the Giants and Royals at Oracle Park is scheduled to start at 11:45am AEST on Tuesday.

All dates and times mentioned in this article are in Australian Eastern Standard Time (AEST), unless otherwise noted.

Conclusion

Our San Francisco vs Kansas City predictions are based on 10,000 data-driven simulations of the game, all curated by our team of expert data scientists and analysts. We use cutting-edge technology and machine learning to ensure our MLB tips are accurate and reliable, so that you can make informed decisions with confidence.

If you decide to use our predictions for betting purposes, it's important that you gamble responsibly and know when to stop. For free and confidential support, call 1800 858 858 or visit gamblinghelponline.org.au.

More on MLB

Stats Insider is your home for betting on the MLB in Australia, with the latest MLB betting news, tips for every MLB game, and futures odds for the MLB.

Stats Insider

Stats Insider, Australia's leading predictive analytics website, offers Australian sports fans innovative tools and content to enhance their enjoyment of major sporting events both domestically and internationally. Our goal is to transform the sports fan experience by providing readily accessible, data-driven content for sports enthusiasts like us.

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