San Francisco Giants vs Chicago Cubs Betting Odds & Game Analysis | July 28


By Claudio Fortuna | July 28, 2022 12:31 PM

The Chicago Cubs visit the San Francisco Giants at Oracle Park, taking the field at 9:45pm ET on Thursday July 28th, 9:45pm ET. The Chicago Cubs are 1.5-run underdogs in the game, and the Over/Under is set at 8 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 Chicago Cubs and San Francisco Giants.

San Francisco and Chicago Betting Info

  • Four of the Cubs’ last five night games against National League opponents have gone OVER the total runs line.
  • The home team has won each of the Giants’ last 10 games.

Chicago Cubs Stats

Season Stats
Team Batting AVG .246
Team OBP .321
AVG Runs Scored 4.3
Team ERA 4.41
Team WHIP 1.33
Starters ERA 4.60
Starters WHIP 1.33

Key Players for Chicago

  • David Robertson: 1.83 ERA, 11.44 K/9, 0.99 WHIP
  • Justin Steele: 4.02 ERA, 8.34 K/9, 1.42 WHIP
  • Steven Brault: 0.00 ERA, 6.75 K/9, 0.50 WHIP
  • Rafael Ortega: .237 Batting Avg, .328 OBP, .362 SLG, .690 OPS, 25 Runs
  • Yan Gomes: .221 Batting Avg, .237 OBP, .349 SLG, .586 OPS, 13 Runs
  • Nicholas Hoerner: .306 Batting Avg, .345 OBP, .435 SLG, .780 OPS, 32 Runs
  • Willson Contreras: .258 Batting Avg, .373 OBP, .470 SLG, .843 OPS, 51 Runs
  • David Bote: .256 Batting Avg, .333 OBP, .395 SLG, .728 OPS, 8 Runs
  • Patrick Wisdom: .221 Batting Avg, .317 OBP, .438 SLG, .755 OPS, 48 Runs
  • Alfonso Rivas: .228 Batting Avg, .313 OBP, .316 SLG, .629 OPS, 19 Runs
  • Ian Happ: .282 Batting Avg, .366 OBP, .446 SLG, .812 OPS, 44 Runs
  • Seiya Suzuki: .272 Batting Avg, .350 OBP, .466 SLG, .816 OPS, 28 Runs

San Francisco Giants Stats

Season Stats
Team Batting AVG .234
Team OBP .317
AVG Runs Scored 4.7
Team ERA 3.91
Team WHIP 1.29
Starters ERA 3.57
Starters WHIP 1.20

Key Players for San Francisco

  • Alexander Cobb: 4.26 ERA, 8.77 K/9, 1.33 WHIP
  • Jakob Junis: 2.98 ERA, 7.29 K/9, 1.01 WHIP
  • Camilo Doval: 2.88 ERA, 10.85 K/9, 1.20 WHIP
  • LaMonte Wade Jr.: .182 Batting Avg, .297 OBP, .338 SLG, .635 OPS, 7 Runs
  • Robert Wynns: .208 Batting Avg, .266 OBP, .278 SLG, .544 OPS, 6 Runs
  • Joc Pederson: .244 Batting Avg, .319 OBP, .496 SLG, .815 OPS, 36 Runs
  • Thomas La Stella: .231 Batting Avg, .270 OBP, .359 SLG, .629 OPS, 13 Runs
  • Luis González: .289 Batting Avg, .355 OBP, .418 SLG, .773 OPS, 23 Runs
  • Thairo Estrada: .262 Batting Avg, .315 OBP, .411 SLG, .726 OPS, 49 Runs
  • Brandon Belt: .234 Batting Avg, .339 OBP, .401 SLG, .740 OPS, 22 Runs
  • Wilmer Flores: .245 Batting Avg, .326 OBP, .437 SLG, .763 OPS, 51 Runs
  • Austin Slater: .287 Batting Avg, .394 OBP, .439 SLG, .833 OPS, 34 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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