Toronto Blue Jays vs Baltimore Orioles Betting Odds & Game Analysis | June 14
The Baltimore Orioles visit the Toronto Blue Jays at Rogers Centre, taking the field at 7:07pm ET on Tuesday June 14th, 7:07pm ET. The Baltimore Orioles 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 Baltimore Orioles and Toronto Blue Jays.
Toronto and Baltimore Betting Info
- Each of the Blue Jays’ last seven home games have gone OVER the total runs line.
- The Orioles have lost 14 of their last 15 road games against AL East Division opponents that held a winning record.
Baltimore Orioles Stats
| Season Stats | |
|---|---|
| Team Batting AVG | .230 |
| Team OBP | .301 |
| AVG Runs Scored | 4.0 |
| Team ERA | 4.34 |
| Team WHIP | 1.36 |
| Starters ERA | 5.27 |
| Starters WHIP | 1.45 |
Key Players for Baltimore
- Jorge López: 0.93 ERA, 8.38 K/9, 0.93 WHIP
- Austin Voth: 6.75 ERA, 10.13 K/9, 1.88 WHIP
- Joshua Garcia: 4.50 ERA, 4.50 K/9, 1.00 WHIP
- Joseph Mancini: .290 Batting Avg, .373 OBP, .424 SLG, .797 OPS, 25 Runs
- Rougned Odor: .209 Batting Avg, .273 OBP, .407 SLG, .680 OPS, 24 Runs
- Adley Rutschman: .183 Batting Avg, .256 OBP, .268 SLG, .524 OPS, 8 Runs
- Ryan Mountcastle: .254 Batting Avg, .294 OBP, .431 SLG, .725 OPS, 23 Runs
- Jorge Mateo: .212 Batting Avg, .244 OBP, .344 SLG, .588 OPS, 17 Runs
- Tyler Nevin: .217 Batting Avg, .313 OBP, .301 SLG, .614 OPS, 13 Runs
- Boyce Mullins: .245 Batting Avg, .306 OBP, .384 SLG, .690 OPS, 32 Runs
- Austin Hays: .293 Batting Avg, .354 OBP, .456 SLG, .810 OPS, 28 Runs
- Kyle Stowers: .333 Batting Avg, .500 OBP, .667 SLG, 1.167 OPS, 0 Runs
Toronto Blue Jays Stats
| Season Stats | |
|---|---|
| Team Batting AVG | .257 |
| Team OBP | .326 |
| AVG Runs Scored | 4.6 |
| Team ERA | 3.55 |
| Team WHIP | 1.19 |
| Starters ERA | 3.38 |
| Starters WHIP | 1.17 |
Key Players for Toronto
- Jordan Romano: 2.82 ERA, 10.48 K/9, 1.16 WHIP
- Yusei Kikuchi: 4.44 ERA, 10.03 K/9, 1.48 WHIP
- Timothy Mayza: 1.98 ERA, 8.56 K/9, 0.95 WHIP
- Bo Bichette: .270 Batting Avg, .316 OBP, .448 SLG, .764 OPS, 34 Runs
- Lourdes Gurriel Jr.: .278 Batting Avg, .336 OBP, .397 SLG, .733 OPS, 20 Runs
- Raimel Tapia: .250 Batting Avg, .279 OBP, .341 SLG, .620 OPS, 20 Runs
- Teoscar Hernández: .246 Batting Avg, .307 OBP, .391 SLG, .698 OPS, 15 Runs
- George Springer: .282 Batting Avg, .350 OBP, .526 SLG, .876 OPS, 39 Runs
- Alejandro Kirk: .315 Batting Avg, .396 OBP, .463 SLG, .859 OPS, 26 Runs
- Santiago Espinal: .290 Batting Avg, .345 OBP, .443 SLG, .788 OPS, 23 Runs
- Vladimir Guerrero Jr.: .258 Batting Avg, .341 OBP, .493 SLG, .834 OPS, 31 Runs
- Matt Chapman: .216 Batting Avg, .305 OBP, .371 SLG, .676 OPS, 27 Runs
In their first and only matchup this season on June 13, 2022, the Blue Jays won by a score of 11-1.
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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He has been involved in the sports betting industry for years as a producer and handicapper specifically focusing on the EPL and other football league...
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