San Francisco Giants at Baltimore Orioles, MLB forecast
Win probability
Starts from the pregame forecast, then moves with the score and the time left after each inning. Above the line favors BAL.
Game center
From the ESPN box score.
Top performers
Giants- Casey SchmittBatting3-4, 1 HR, 1 RBI
- Adrian HouserPitching4.2 IP, 4 ER, 3 K
Orioles- Samuel BasalloBatting1-3, 1 HR, 2 RBI
- Cade PovichPitching6.2 IP, 1 ER, 5 K
Scoring summary
- 9Schmitt homered to left (385 feet).2–6
- 7Cowser reached on infield single to shortstop, Ward scored, Rodríguez to second, Alonso to third.1–6
- 6Mayo singled to center, Taveras scored.1–5
- 5Alonso doubled to left, Henderson scored and Ward scored.1–4
- 5Susac singled to center, Schmitt scored.1–2
- 1Basallo homered to left center (396 feet), Alonso scored.0–2
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Orioles 53%
Forecast Elo ratings alone
How often that comes true: MLB favorites the forecast gave 50–55% have won 52.7% of 2,871 graded games.
- Market
- BAL 53%
- ML SF +104 / BAL -126
- Pre-line forecast
- BAL 52%
- Elo + market-implied
- Elo ratings
- BAL 49%
- Ratings vs. market
- −4.6 pts
- BAL: Elo 48.6%, market 53.2%
- Fair odds
- BAL -114
- SF +114 · the forecast as odds, no margin
- Pregame projection
- SF 4.1 – 4.4 BAL
- Margin from the forecast, posted total 8.5
How the number is built
Elo inputs in rating points (higher favors that team; 25–28 Elo is about a point of spread in football and basketball), then how the pieces combine.
| Factor | SF | BAL | Why |
|---|---|---|---|
| Team rating | 1495 | 1487 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | −1 | −20 | SF: Adrian Houser: team allows 0.04 more runs than with its usual starter (≈10 weighted starts) · BAL: Cade Povich: team allows 1.02 more runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | SF +9 Elo | SF 51.4% | |
| Market-implied ratings | BAL 52.4% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | BAL 51.8% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | BAL 53.2% | Follows the market (vig removed): in testing, adding the ratings made it less accurate | |
Tale of the tape
This season coming into the game, regular season, each number with its league rank (the longer the bar, the higher). Home and road: the host's record at home against the visitor's on the road. Opponent Elo: how strong the teams each has played are, 1st the toughest.
| SF | Stat | BAL |
|---|---|---|
| 27th of 303.3 | Runs scored | 3.921st of 30 |
| 19th of 304.4 | Runs allowed | 4.114th of 30 |
| 28th of 30−1.1 | Margin | −0.218th of 30 |
| 18th of 304–6 | Last 10 | 5–512th of 30 |
| 7th of 303–2 | Road vs home | 4–419th of 30 |
| 4th of 301519 | Opponent Elo | 148324th of 30 |
| 20th of 301495 | Elo rating | 148723rd of 30 |
Rating history
Each team's Elo over the last two seasons. Hover or drag to compare on any date.
Recent form
Last five results, and whether the forecast hit.
Against the line
How each team has done against the closing spread and total, coming into this game.
| This season |  SF |  BAL |
|---|---|---|
| Run line | 6–9 | 6–8 |
| Last 10 | 4–6 | 5–5 |
| Favorite | 2–2 | 5–6 |
| Underdog | 4–7 | 1–2 |
| Overs–unders | 7–5–3 | 8–6 |
| Overs–unders, last 10 | 6–2–2 | 7–3 |
Against each game's closing line. Books set every line knowing these records: across 3,901 past games, the team with the better record against the spread so far that season covered 51.2%, short of the 52.4% a standard −110 bet needs, and over/under streaks held 48.0% of the time. They describe the past.
Head to head
SF 6–5 BAL in their last 11 meetings; the forecast called 6 of 11.