Athletics 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
Athletics- Tyler SoderstromBatting1-4, 1 RBI
- JP SearsPitching4.0 IP, 4 ER, 2 K
Giants- Wilmer FloresBatting3-5, 3 HR, 8 RBI
- Logan WebbPitching8.0 IP, 1 ER, 4 K
Scoring summary
- 8Adames singled to left, Chapman scored.1–9
- 8Flores homered to left center (381 feet).1–8
- 8Soderstrom reached on infield single to second, Urías scored, Schuemann to second.1–7
- 6Flores homered to left center (373 feet), Bailey scored and Ramos scored.0–7
- 3Flores homered to left center (379 feet), Bailey scored, Fitzgerald scored and Ramos scored.0–4
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 ATH +170 / SF -205
- Pre-line forecast
- SF 62%
- Elo + market-implied
- Elo ratings
- SF 61%
- Ratings vs. market
- −3.2 pts
- SF: Elo 61.3%, market 64.5%
- Fair odds
- SF -181
- ATH +181 · the forecast as odds, no margin
- Pregame projection
- ATH 2.6 – 3.9 SF
- Margin from the forecast, posted total 6.5
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 | ATH | SF | Why |
|---|---|---|---|
| Team rating | 1460 | 1515 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | +4 | +10 | ATH: JP Sears: team allows 0.18 fewer runs than with its usual starter (≈10 weighted starts) · SF: Logan Webb: team allows 0.49 fewer runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | SF +80 Elo | SF 61.3% | |
| Market-implied ratings | SF 62.6% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 62.4% | 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.
| ATH | Stat | SF |
|---|---|---|
| 14th of 304.5 | Runs scored | 4.810th of 30 |
| 28th of 305.6 | Runs allowed | 3.910th of 30 |
| 24th of 30−1.2 | Margin | +0.88th of 30 |
| 18th of 304–6 | Last 10 | 4–618th of 30 |
| 1st of 3014–9 | Road vs home | 13–710th of 30 |
| 18th of 301497 | Opponent Elo | 15038th of 30 |
| 24th of 301460 | Elo rating | 151513th 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 |  ATH |  SF |
|---|---|---|
| Run line | 24–20 | 23–21 |
| Last 10 | 5–5 | 6–4 |
| Favorite | 5–7 | 9–14 |
| Underdog | 19–13 | 14–7 |
| Overs–unders | 26–18 | 26–18 |
| Overs–unders, last 10 | 8–2 | 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
ATH 4–4 SF in their last 8 meetings; the forecast called 4 of 8.
