Los Angeles Dodgers 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
Dodgers- Hyeseong KimBatting2-4, 1 RBI
- Tyler GlasnowPitching8.0 IP, 0 ER, 9 K
Giants- Luis ArraezBatting1-2
- Logan WebbPitching7.0 IP, 3 ER, 5 K
Scoring summary
- 4Kim singled to left, Muncy scored, Kim to second.3–0
- 4Muncy doubled to center, Tucker scored on throwing error by center fielder Gilbert.2–0
- 2Rushing singled to center, Muncy scored, Rushing to second.1–0
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Dodgers 59%
Forecast Elo ratings alone
How often that comes true: MLB favorites the forecast gave 55–60% have won 55.5% of 2,596 graded games.
- Market
- LAD 59%
- ML LAD -163 / SF +135
- Pre-line forecast
- LAD 58%
- Elo + market-implied
- Elo ratings
- LAD 59%
- Ratings vs. market
- −0.4 pts
- LAD: Elo 58.9%, market 59.3%
- Fair odds
- LAD -146
- SF +146 · the forecast as odds, no margin
- Pregame projection
- LAD 4.2 – 3.3 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 | LAD | SF | Why |
|---|---|---|---|
| Team rating | 1563 | 1497 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | +9 | −6 | LAD: Tyler Glasnow: team allows 0.46 fewer runs than with its usual starter (≈10 weighted starts) · SF: Logan Webb: team allows 0.30 more runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | LAD +63 Elo | LAD 58.9% | |
| Market-implied ratings | LAD 57.9% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | LAD 58.0% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | LAD 59.3% | 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.
| LAD | Stat | SF |
|---|---|---|
| 2nd of 305.6 | Runs scored | 3.429th of 30 |
| 2nd of 303.4 | Runs allowed | 4.010th of 30 |
| 2nd of 30+2.2 | Margin | −0.723rd of 30 |
| 10th of 305–5 | Last 10 | 5–510th of 30 |
| 6th of 307–5 | Road vs home | 5–724th of 30 |
| 28th of 301483 | Opponent Elo | 15087th of 30 |
| 1st of 301563 | Elo rating | 149716th 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 |  LAD |  SF |
|---|---|---|
| Run line | 12–12 | 12–12 |
| Last 10 | 4–6 | 6–4 |
| Favorite | 12–12 | 3–3 |
| Underdog | — | 9–9 |
| Overs–unders | 10–13–1 | 10–11–3 |
| Overs–unders, last 10 | 3–7 | 4–6 |
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
LAD 25–16 SF in their last 41 meetings; the forecast called 25 of 41.