Washington Nationals 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
Nationals- CJ AbramsBatting2-4, 2 RBI
- Miles MikolasPitching4.2 IP, 0 ER, 2 K
Giants- Jung Hoo LeeBatting4-5
- Logan WebbPitching8.0 IP, 1 ER, 7 K
Scoring summary
- 9Lile singled to center, Abrams scored.4–3
- 9Abrams singled to center, García Jr. scored and Tena scored.3–3
- 8Cox hit sacrifice bunt to first, Eldridge scored, Chapman to third.1–3
- 8Eldridge doubled to left, Lee scored.1–2
- 6Chapman singled to left, Lee scored, Eldridge to second.1–1
- 6García Jr. singled to right, Wood scored, García Jr. to second.1–0
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Giants 58%
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
- SF 58%
- ML WSH +129 / SF -156
- Pre-line forecast
- SF 59%
- Elo + market-implied
- Elo ratings
- SF 55%
- Ratings vs. market
- −3.4 pts
- SF: Elo 54.8%, market 58.3%
- Fair odds
- SF -140
- WSH +140 · the forecast as odds, no margin
- Pregame projection
- WSH 3.6 – 4.4 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 | WSH | SF | Why |
|---|---|---|---|
| Team rating | 1470 | 1484 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | −4 | −1 | WSH: Richard Lovelady: team allows 0.19 more runs than with its usual starter (≈3 weighted starts) · SF: Logan Webb: team allows 0.07 more runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | SF +34 Elo | SF 54.8% | |
| Market-implied ratings | SF 59.2% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 58.6% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | SF 58.3% | 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.
| WSH | Stat | SF |
|---|---|---|
| 1st of 305.3 | Runs scored | 4.121st of 30 |
| 29th of 305.3 | Runs allowed | 4.822nd of 30 |
| 10th of 30+0.1 | Margin | −0.726th of 30 |
| 18th of 304–6 | Last 10 | 5–511th of 30 |
| 4th of 3021–13 | Road vs home | 12–1625th of 30 |
| 2nd of 301510 | Opponent Elo | 15093rd of 30 |
| 27th of 301470 | Elo rating | 148422nd 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 |  WSH |  SF |
|---|---|---|
| Run line | 39–27 | 31–35 |
| Last 10 | 5–5 | 6–4 |
| Favorite | 4–8 | 8–12 |
| Underdog | 35–19 | 23–23 |
| Overs–unders | 40–22–4 | 32–29–5 |
| Overs–unders, last 10 | 5–5 | 6–3–1 |
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
WSH 12–10 SF in their last 22 meetings; the forecast called 9 of 22.