Pittsburgh Pirates at San Francisco Giants, 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 SF.
Game center
From the ESPN box score.
Top performers
Pirates- Marcell OzunaBatting2-3, 1 HR, 1 RBI
- Carmen MlodzinskiPitching6.0 IP, 2 ER, 1 K
Giants- Rafael DeversBatting2-4, 1 HR, 1 RBI
- Robbie RayPitching6.0 IP, 1 ER, 7 K
Scoring summary
- 9Horwitz singled to right, Cruz scored, Griffin to third.2–5
- 7Arraez singled to right, Gilbert scored and Ramos scored, J. Rodríguez to second.1–5
- 7Gilbert singled to right, Adames scored, Ramos to third.1–3
- 4Ramos singled to center, Devers scored, Chapman thrown out at third.1–2
- 2Devers homered to center (399 feet).1–1
- 2Ozuna homered to left (365 feet).1–0
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Giants 51%
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 51%
- ML PIT -105 / SF -115
- Pre-line forecast
- SF 52%
- Elo + market-implied
- Elo ratings
- SF 52%
- Ratings vs. market
- +1.3 pts
- SF: Elo 52.4%, market 51.1%
- Fair odds
- SF -104
- PIT +104 · the forecast as odds, no margin
- Pregame projection
- PIT 4.0 – 4.0 SF
- Margin from the forecast, posted total 8
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 | PIT | SF | Why |
|---|---|---|---|
| Team rating | 1497 | 1483 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | −4 | +9 | PIT: Carmen Mlodzinski: team allows 0.19 more runs than with its usual starter (≈9 weighted starts) · SF: Robbie Ray: team allows 0.45 fewer runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | SF +17 Elo | SF 52.4% | |
| Market-implied ratings | SF 51.9% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 52.0% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | SF 51.1% | 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.
| PIT | Stat | SF |
|---|---|---|
| 8th of 304.9 | Runs scored | 3.130th of 30 |
| 11th of 304.2 | Runs allowed | 4.212th of 30 |
| 6th of 30+0.7 | Margin | −1.130th of 30 |
| 13th of 305–5 | Last 10 | 2–828th of 30 |
| 8th of 3010–8 | Road vs home | 8–1126th of 30 |
| 15th of 301501 | Opponent Elo | 15076th of 30 |
| 17th of 301497 | Elo rating | 148323rd 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 |  PIT |  SF |
|---|---|---|
| Run line | 19–19 | 18–19 |
| Last 10 | 3–7 | 5–5 |
| Favorite | 10–11 | 5–6 |
| Underdog | 9–8 | 13–13 |
| Overs–unders | 20–17–1 | 15–19–3 |
| Overs–unders, last 10 | 5–4–1 | 3–7 |
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
PIT 8–10 SF in their last 18 meetings; the forecast called 7 of 18.