- August 28, 2025
- Views 146
MLB Prediction: Baltimore Orioles vs San Francisco Giants (Friday, August 29 at 10:15 PM ET)
Introduction
Market / Trend | BAL | SF |
---|---|---|
Moneyline | +140 | -167 |
Total (O/U) | 7.5 | |
Run Line | +1.5 (-165) | -1.5 (142) |
Last 5 RPG | 2.0 | 6.4 |
Record | 60–73 | 65–68 |
Lines: BetMGM, BetOnline.ag, BetRivers, BetUS +6 more |
More MLB picks: Baltimore Orioles · San Francisco Giants
The Orioles enter this interleague matchup against the Giants on a 1-4 skid across their last five games, averaging just 2.0 runs per contest, while San Francisco has surged with a perfect 5-0 stretch at 6.4 RPG. This contrast in recent form shapes a decisive MLB prediction: the Giants’ balanced offense and sharper run prevention create a clear edge. With Baltimore Orioles’ road inconsistency and San Francisco Giants’ home stability, the betting value tilts firmly toward the National League side, and the scoring profiles point to an Over play on the total.
Game Time
First pitch is set for Friday, August 29 at 10:15 PM ET at Oracle Park, marine air knocks down carry.
Odds & Spread Line
- Baltimore Orioles: +140
- San Francisco Giants: -167
Total: 7.5
- Run Line — Baltimore Orioles: +1.5 (-165)
- Run Line — San Francisco Giants: -1.5 (+142)
Latest Team Records
Baltimore Orioles: 60-73 (Win %: 0.451)
San Francisco Giants: 65-68 (Win %: 0.489)
Injury Report
Baltimore Orioles are missing Scott Blewett (Elbow), listed as 60-Day-IL; Jorge Mateo (Hamstring), listed as 60-Day-IL.
The San Francisco Giants are currently healthy with no major injury concerns.
Key Player Stats
Baltimore Orioles
- Gunnar Henderson: 0.278 AVG, 16 HR, 59 RBI
- Jordan Westburg: 0.276 AVG, 15 HR, 34 RBI
- Jackson Holliday: 0.24 AVG, 15 HR, 49 RBI
San Francisco Giants
- Rafael Devers: 0.258 AVG, 27 HR, 89 RBI
- Heliot Ramos: 0.266 AVG, 16 HR, 57 RBI
- Willy Adames: 0.222 AVG, 22 HR, 66 RBI
Team Analysis
Baltimore Orioles
The Orioles’ season record reflects inconsistency, and their last 5 games at 1-4 with just 2.0 RPG highlight a slump that weakens confidence in their road performance. Gunnar Henderson has been a steady contributor, but the lack of collective production has left the lineup unable to sustain pressure against stronger pitching staffs. Their 29-37 road record underlines a persistent inability to generate momentum away from home.
Jordan Westburg and Jackson Holliday bring upside, yet their contributions have not been enough to offset the team’s inconsistency, particularly against opponents with higher offensive efficiency. The Orioles’ 3-7 stretch in their last 10 games confirms a lack of rhythm, especially when paired with below-average scoring outputs. With a pitching staff vulnerable to lapses, Baltimore faces an uphill battle to keep pace against San Francisco Giants’ more balanced attack.
- Batting Average: 0.24
- Total Runs Scored: 572
- Home Runs: 159
- OBP: 0.305
- SLG: 0.402
- OPS: 0.707
- ERA: 4.68
- WHIP: 1.37
Away Record: 29-37 • Home Record: 31-37
Last 5 Games: 1-4 (2.0 RPG)
Last 10 Games: 3-7 (3.7 RPG)
San Francisco Giants
The Giants’ 5-0 run in their last 5 games with 6.4 RPG speaks to a team hitting stride at the right time, fueled by Rafael Devers’ power production. Their 33-33 home record indicates stability at this venue, and that consistency supports their ability to protect leads. With sharper run prevention and a deeper lineup, San Francisco has built a profile that bettors can trust against an opponent struggling on the road.
Heliot Ramos and Willy Adames add depth to the order, ensuring that pressure is applied throughout the lineup rather than relying on one bat. Their 6-4 record across the last 10 games proves they are sustaining rhythm beyond just a short burst, averaging 4.6 RPG in that stretch. With a pitching staff keeping runs in check and an offense trending upward, the Giants are positioned to capitalize on Baltimore Orioles’ slump.
- Batting Average: 0.233
- Total Runs Scored: 547
- Home Runs: 134
- OBP: 0.309
- SLG: 0.38
- OPS: 0.689
- ERA: 3.72
- WHIP: 1.28
Away Record: 33-35 • Home Record: 33-33
Last 5 Games: 5-0 (6.4 RPG)
Last 10 Games: 6-4 (4.6 RPG)
Head-to-Head History
No recent matchups between these teams in 2025.
Over/Under Trends
Baltimore Orioles’ last 10 games have averaged 8.6 total runs, with 4 games that would have cleared today’s total of 7.5.
San Francisco Giants’ last 10 games have averaged 8.7 combined runs, with 5 games clearing the same number of 7.5.
Moneyline Betting Prediction
San Francisco Giants’ 5-0 surge at 6.4 RPG, paired with balanced contributions from Rafael Devers, Heliot Ramos, and Willy Adames, makes them the superior side against a Baltimore team stuck in a 1-4 rut. The Giants’ ability to pair home stability with consistent scoring ensures they are the sharper moneyline play in this interleague spot.
Confidence sits with the San Francisco Giants based on recent profiles.
Over/Under Prediction
In their last five, the San Francisco Giants have produced 6.4 RPG and the Baltimore Orioles 2.0. That output frames how this total sets up.
These teams are combining for 8.4 runs per game recently — above the posted total of 7.5. That points toward the Over 7.5.
Bookmakers
You’ll find these markets at: BetOnline.ag, LowVig.ag, FanDuel, Caesars, DraftKings, MyBookie.ag, Bovada, BetUS, BetMGM, BetRivers.
Parlamaz may earn affiliate commissions from links in this article.
MLB Predictions FAQ
What do moneyline, run line, and total mean?
Moneyline is who wins the game. Run line is a spread, usually ±1.5 runs. The total (over/under) is combined runs by both teams.
How does Parlamaz make Baltimore Orioles vs San Francisco Giants MLB predictions?
We use trusted data feeds and real-time odds to model each matchup. We weight the numbers that move lines—team form, matchup history, injuries, park factors, totals trends, and betting momentum—then compare our price to the market to find value. All signal, no noise. No paywalls.
How should I size my bets?
Use a consistent unit (about 1–2% of bankroll). Singles should be most of your volume. We like parlays—smart ones. Keep legs tight (2–3), cap risk to 0.25–0.5u, and pass when the price isn’t there.

John TamburinoVerified
Lead Analyst — data-first, former college baseball.
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