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- Spencer HorwitzBatting2-4, 1 RBI
- Mike BurrowsPitching6.0 IP, 1 ER, 7 K
Giants- Dominic SmithBatting2-4, 1 RBI
- Logan WebbPitching5.2 IP, 1 ER, 11 K
Scoring summary
- 10Davis grounded out to second, Cruz scored, Suwinski to second.2–1
- 5Horwitz doubled to center, Kiner-Falefa scored.1–1
- 4Smith singled to right, Ramos scored, Adames to third.0–1
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Giants 64%
Forecast Elo ratings alone
How often that comes true: MLB favorites the forecast gave 60–65% have won 61.6% of 1,194 graded games.
- Market
- SF 64%
- ML PIT +170 / SF -205
- Pre-line forecast
- SF 64%
- Elo + market-implied
- Elo ratings
- SF 57%
- Ratings vs. market
- −7.7 pts
- SF: Elo 56.8%, market 64.5%
- Fair odds
- SF -181
- PIT +181 · the forecast as odds, no margin
- Pregame projection
- PIT 3.1 – 4.4 SF
- 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 | PIT | SF | Why |
|---|---|---|---|
| Team rating | 1474 | 1494 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | −9 | 0 | PIT: Mike Burrows: team allows 0.47 more runs than with its usual starter (≈7 weighted starts) · SF: Logan Webb: team allows 0.01 more runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | SF +47 Elo | SF 56.8% | |
| Market-implied ratings | SF 65.3% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 64.0% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | SF 64.5% | 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 |
|---|---|---|
| 30th of 303.4 | Runs scored | 4.124th of 30 |
| 4th of 303.9 | Runs allowed | 4.08th of 30 |
| 24th of 30−0.5 | Margin | +0.116th of 30 |
| 1st of 307–3 | Last 10 | 2–828th of 30 |
| 29th of 3015–37 | Road vs home | 28–2518th of 30 |
| 1st of 301509 | Opponent Elo | 149920th of 30 |
| 25th of 301474 | Elo rating | 149421st 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 | 56–52 | 43–65 |
| Last 10 | 7–3 | 2–8 |
| Favorite | 10–23 | 16–47 |
| Underdog | 46–29 | 27–18 |
| Overs–unders | 43–65 | 51–57 |
| Overs–unders, last 10 | 3–7 | 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
PIT 6–8 SF in their last 14 meetings; the forecast called 5 of 14.