San Francisco Giants at Washington Nationals, 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 WSH.
Game center
From the ESPN box score.
Top performers
Giants- Matt ChapmanBatting1-4, 1 HR, 3 RBI
- Logan WebbPitching5.2 IP, 1 ER, 4 K
Nationals- James WoodBatting1-3, 1 RBI
- Patrick CorbinPitching6.0 IP, 4 ER, 6 K
Scoring summary
- 6Wood singled to right, Ruiz scored.4–1
- 6Pitch 3 : Ball In Play4–1
- 6Pitch 2 : Ball 14–1
- 6Pitch 1 : Strike 1 Looking4–1
- 3Chapman homered to left (409 feet), Yastrzemski scored and Conforto scored.4–0
- 3Pitch 1 : Ball In Play4–0
- 1Fitzgerald homered to left center (416 feet).1–0
- 1Pitch 2 : Ball In Play1–0
- 1Pitch 1 : Strike 1 Looking1–0
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Giants 60%
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 60%
- ML SF -170 / WSH +140
- Pre-line forecast
- SF 60%
- Elo + market-implied
- Elo ratings
- SF 55%
- Ratings vs. market
- −5.4 pts
- SF: Elo 54.8%, market 60.2%
- Fair odds
- SF -151
- WSH +151 · the forecast as odds, no margin
- Pregame projection
- SF 4.7 – 3.8 WSH
- Margin from the forecast, posted total 8.5
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 | WSH | Why |
|---|---|---|---|
| Team rating | 1494 | 1469 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | +5 | −21 | SF: Logan Webb: team allows 0.27 fewer runs than with its usual starter (≈10 weighted starts) · WSH: Patrick Corbin: team allows 1.05 more runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | SF +33 Elo | SF 54.8% | |
| Market-implied ratings | SF 60.6% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 59.8% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | SF 60.2% | 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.
| SF | Stat | WSH |
|---|---|---|
| 15th of 304.4 | Runs scored | 4.216th of 30 |
| 19th of 304.5 | Runs allowed | 4.724th of 30 |
| 19th of 30−0.1 | Margin | −0.524th of 30 |
| 3rd of 307–3 | Last 10 | 4–621st of 30 |
| 25th of 3023–33 | Road vs home | 25–2825th 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 |  WSH |
|---|---|---|
| Run line | 54–57 | 63–49 |
| Last 10 | 5–5 | 7–3 |
| Favorite | 20–34 | 9–13 |
| Underdog | 34–23 | 54–36 |
| Overs–unders | 59–51–1 | 56–55–1 |
| Overs–unders, last 10 | 6–4 | 7–3 |
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 2–7 WSH in their last 9 meetings; the forecast called 2 of 9.