HomebaseballKansas City Royals vs. Toronto Blue Jays Predictions & Odds – Jun...

Kansas City Royals vs. Toronto Blue Jays Predictions & Odds – Jun 6, 2022

The Kansas City Royals (17W-35L) will meet the Toronto Blue Jays (31W-22L) on Monday, June 6 at Kauffman Stadium at 7:10 pm CT.

Kansas City Royals vs. Toronto Blue Jays Odds

Kansas City Royals +144 | Toronto Blue Jays -172 (BET NOW)

Over/Under 9.5 total points (BET NOW)

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Kansas City Royals

This season’s overall batting average for the Royals is .239. As far as pitching goes, the team has an ERA of 5.34 and with regard to fielding, they have a .988 percentage. They defeated the Houston Astros 4-7 the last time they met on Sunday, and are currently number five in the American League Central. That said, do you think they can take home the win here?

The Kansas City Royals are without Donald Greinke (Flexor), Amir Garrett (Undisclosed), Gabriel Speier (Undisclosed), Cameron Gallagher (Hamstring), Raúl Mondesi (Knee), Jacob Brentz (Flexor), Tyler Zuber (Shoulder), Edward Olivares (Quad) and Matthew Peacock (Undisclosed).

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Toronto Blue Jays

The overall regular season batting average for the Blue Jays is .244 and in terms of pitching, the team has an ERA of 3.78. With regard to fielding, the team has a percentage of .987. They outplayed the Minnesota Twins 6-8 the last time they met on Sunday, and are currently number two in the American League East. Will the Blue Jays come out on top when all is said and done this time?

The Toronto Blue Jays are without Hyun Jin Ryu (Forearm), Nathan Pearson (Mono), Tayler Saucedo (Hip) and Timothy Mayza (Forearm).

Kansas City Royals vs. Toronto Blue Jays Predictions

Moneyline Pick: Toronto Blue Jays (-172)

Over/Under Pick: Under 9.5 total points (-114)

Runline Pick: Toronto Blue Jays -1.5 runs (-110)

(*Predictions based on our proprietary predictive algorithm software)

View today’s MLB betting lines.

BigOnSports Staff
BigOnSports Staff
Our predictions are based on our proprietary predictive algorithm software that runs each game simulation 10,000 times in order to determine the optimal betting value.
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