New York Mets 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
Mets- Luis Robert Jr.Batting3-5
- Kodai SengaPitching5.2 IP, 2 ER, 7 K
Giants- Matt ChapmanBatting2-3, 1 RBI
- Logan WebbPitching7.0 IP, 1 ER, 3 K
Scoring summary
- 8Semien doubled to left, Vientos scored.5–2
- 8Vientos reached on infield single to third, Torrens scored on throwing error by third baseman Chapman, Vientos to second.4–2
- 8Torrens doubled to right, Robert Jr. scored and Taylor scored.3–2
- 6Devers singled to center, Chapman scored.1–2
- 6Chapman doubled to left, Bailey scored.1–1
- 2Vientos singled to left, Robert Jr. scored, Young to second.1–0
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Giants 54%
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 54%
- ML NYM +107 / SF -129
- Pre-line forecast
- SF 53%
- Elo + market-implied
- Elo ratings
- SF 48%
- Ratings vs. market
- −6.2 pts
- SF: Elo 47.6%, market 53.8%
- Fair odds
- SF -117
- NYM +117 · the forecast as odds, no margin
- Pregame projection
- NYM 3.3 – 3.7 SF
- Margin from the forecast, posted total 7
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 | NYM | SF | Why |
|---|---|---|---|
| Team rating | 1515 | 1493 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | +10 | −2 | NYM: Kodai Senga: team allows 0.52 fewer runs than with its usual starter (≈10 weighted starts) · SF: Logan Webb: team allows 0.10 more runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | NYM +16 Elo | NYM 52.4% | |
| Market-implied ratings | SF 53.9% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 52.9% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | SF 53.8% | 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.
| NYM | Stat | SF |
|---|---|---|
| 9th of 304.9 | Runs scored | 2.730th of 30 |
| 4th of 303.3 | Runs allowed | 5.124th of 30 |
| 6th of 30+1.6 | Margin | −2.429th of 30 |
| 11th of 303–3 | Road vs home | 1–527th of 29 |
| 24th of 301487 | Opponent Elo | 15283rd of 30 |
| 10th of 301515 | Elo rating | 149320th 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 |  NYM |  SF |
|---|---|---|
| Run line | 5–4 | 3–6 |
| Last 10 | 5–4 | 3–6 |
| Favorite | 4–3 | 2–1 |
| Underdog | 1–1 | 1–5 |
| Overs–unders | 4–5 | 4–3–2 |
| Overs–unders, last 10 | 4–5 | 4–3–2 |
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
NYM 12–10 SF in their last 22 meetings; the forecast called 10 of 22.