Kansas City Royals vs Tampa Bay Rays Betting Odds & Game Analysis | July 22


By Claudio Fortuna | July 22, 2022 11:35 AM

The Tampa Bay Rays visit the Kansas City Royals at Kauffman Stadium, taking the field at 8:10pm ET on Friday July 22nd, 8:10pm ET. The Kansas City Royals are 1.5-run underdogs in the game, and the Over/Under is set at 9 runs.

Welcome to the BestOdds betting breakdown where we identify performance trends in order to analyze teams’ chances in the upcoming game.

Today, we are looking at the Major League Baseball game between the Tampa Bay Rays and Kansas City Royals.

Kansas City and Tampa Bay Betting Info

  • Each of the Rays’ last four games have gone OVER the total runs line.
  • The Rays have won each of their last eight night games against American League opponents.

Tampa Bay Rays Stats

Season Stats
Team Batting AVG .240
Team OBP .307
AVG Runs Scored 4.2
Team ERA 3.37
Team WHIP 1.14
Starters ERA 3.35
Starters WHIP 1.10

Key Players for Tampa Bay

  • Corey Kluber: 3.73 ERA, 7.85 K/9, 1.12 WHIP
  • Luke Bard: 2.70 ERA, 6.30 K/9, 1.00 WHIP
  • Taylor Walls: .178 Batting Avg, .257 OBP, .295 SLG, .552 OPS, 26 Runs
  • Francisco Mejía: .241 Batting Avg, .249 OBP, .412 SLG, .661 OPS, 21 Runs
  • Joshua Lowe: .199 Batting Avg, .258 OBP, .338 SLG, .596 OPS, 21 Runs
  • Randy Arozarena: .254 Batting Avg, .314 OBP, .431 SLG, .745 OPS, 42 Runs
  • Brett Phillips: .147 Batting Avg, .219 OBP, .259 SLG, .478 OPS, 19 Runs
  • Ji-Man Choi: .278 Batting Avg, .385 OBP, .449 SLG, .834 OPS, 26 Runs
  • Brandon Lowe: .246 Batting Avg, .324 OBP, .452 SLG, .776 OPS, 24 Runs
  • Isaac Paredes: .226 Batting Avg, .297 OBP, .506 SLG, .803 OPS, 27 Runs

Kansas City Royals Stats

Season Stats
Team Batting AVG .244
Team OBP .308
AVG Runs Scored 3.9
Team ERA 4.80
Team WHIP 1.48
Starters ERA 4.93
Starters WHIP 1.46

Key Players for Kansas City

  • Scott Barlow: 2.06 ERA, 9.07 K/9, 0.96 WHIP
  • Jackson Kowar: 8.80 ERA, 9.98 K/9, 2.22 WHIP
  • Kristofer Bubic: 5.87 ERA, 7.49 K/9, 1.73 WHIP
  • Mervyl Melendez: .217 Batting Avg, .309 OBP, .406 SLG, .715 OPS, 22 Runs
  • Whitley Merrifield: .240 Batting Avg, .292 OBP, .343 SLG, .635 OPS, 45 Runs
  • Edward Olivares: .303 Batting Avg, .358 OBP, .434 SLG, .792 OPS, 15 Runs
  • Robert Witt Jr.: .254 Batting Avg, .299 OBP, .450 SLG, .749 OPS, 48 Runs
  • Andrew Benintendi: .317 Batting Avg, .386 OBP, .401 SLG, .787 OPS, 37 Runs
  • Vincent Pasquantino: .208 Batting Avg, .313 OBP, .347 SLG, .660 OPS, 7 Runs
  • Michael A. Taylor: .264 Batting Avg, .340 OBP, .385 SLG, .725 OPS, 26 Runs
  • Emmanuel Rivera: .231 Batting Avg, .282 OBP, .407 SLG, .689 OPS, 22 Runs
  • Hunter Dozier: .265 Batting Avg, .327 OBP, .445 SLG, .772 OPS, 36 Runs

MLB Computer Picks For Betting Previews

MLB computer picks are betting recommendations made by an AI computer algorithm with a final check by sports betting analyst.

The AI algorithm considers various data points to come up with its betting prediction. Betting trends, game venue, line-ups, weather, injury, news updates, and a wide range of stats are the factors taken into account when making MLB betting preview computer picks.

A professional sports bettor performs the final check.

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