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- Heliot RamosBatting2-4, 2 RBI
- Logan WebbPitching6.0 IP, 4 ER, 6 K
Orioles- Jeremiah JacksonBatting3-4, 1 HR, 2 RBI
- Chris BassittPitching4.2 IP, 1 ER, 2 K
Scoring summary
- 8Mayo singled to left, Beavers scored.2–6
- 7Jackson homered to left center (384 feet).2–5
- 4Jackson doubled to right, Mayo scored.2–4
- 4Mayo grounded into fielder's choice to second, Taveras scored, Cowser out at second.2–3
- 4Ramos grounded out to first, Devers scored, Lee to second, Schmitt to third.2–2
- 3Henderson homered to right (361 feet).1–2
- 2Cowser grounded out to pitcher, Beavers scored.1–1
- 2Ramos singled to center, Devers scored, Ramos to second.1–0
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Giants 52%
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
- SF 52%
- ML SF -118 / BAL -102
- Pre-line forecast
- SF 52%
- Elo + market-implied
- Elo ratings
- SF 51%
- Ratings vs. market
- −1.1 pts
- SF: Elo 50.6%, market 51.7%
- Fair odds
- SF -107
- BAL +107 · the forecast as odds, no margin
- Pregame projection
- SF 3.8 – 3.7 BAL
- Margin from the forecast, posted total 7.5
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 | 1497 | 1485 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | −3 | −12 | SF: Logan Webb: team allows 0.13 more runs than with its usual starter (≈10 weighted starts) · BAL: Chris Bassitt: team allows 0.59 more runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | SF +4 Elo | SF 50.6% | |
| Market-implied ratings | SF 52.1% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 51.9% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | SF 51.7% | 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 303.4 | Runs scored | 3.722nd of 30 |
| 18th of 304.3 | Runs allowed | 4.216th of 30 |
| 27th of 30−0.9 | Margin | −0.522nd of 30 |
| 12th of 305–5 | Last 10 | 4–619th of 30 |
| 2nd of 303–1 | Road vs home | 3–426th of 30 |
| 4th of 301521 | Opponent Elo | 148225th of 30 |
| 19th of 301497 | Elo rating | 148523rd 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 | 6–8 | 5–8 |
| Last 10 | 5–5 | 4–6 |
| Favorite | 2–2 | 4–6 |
| Underdog | 4–6 | 1–2 |
| Overs–unders | 6–5–3 | 7–6 |
| Overs–unders, last 10 | 6–2–2 | 6–4 |
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 6–4 BAL in their last 10 meetings; the forecast called 6 of 10.