Milwaukee Brewers 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
Brewers- Brice TurangBatting3-5, 2 RBI
- Freddy PeraltaPitching5.0 IP, 3 ER, 3 K
Giants- Wilmer FloresBatting2-4, 2 RBI
- Logan WebbPitching6.1 IP, 0 ER, 6 K
Scoring summary
- 9Turang hit a ground rule double, Capra scored and Bauers scored, Durbin to third.2–4
- 6Koss reached on infield single to shortstop, Flores scored on throwing error by shortstop Ortiz, Wade Jr. safe at third on error.0–4
- 6Wade Jr. grounded into fielder's choice to second, Chapman scored on error, Flores safe at second on fielding error by second baseman Turang.0–3
- 6Flores singled to center, Adames scored and Lee scored, Chapman to third.0–2
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Giants 57%
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 57%
- ML MIL +120 / SF -145
- Pre-line forecast
- SF 54%
- Elo + market-implied
- Elo ratings
- SF 51%
- Ratings vs. market
- −5.9 pts
- SF: Elo 50.7%, market 56.6%
- Fair odds
- SF -130
- MIL +130 · the forecast as odds, no margin
- Pregame projection
- MIL 3.0 – 3.5 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 | MIL | SF | Why |
|---|---|---|---|
| Team rating | 1531 | 1513 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | +8 | +12 | MIL: Freddy Peralta: team allows 0.40 fewer runs than with its usual starter (≈10 weighted starts) · SF: Logan Webb: team allows 0.60 fewer runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | SF +5 Elo | SF 50.7% | |
| Market-implied ratings | SF 55.1% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 54.4% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | SF 56.6% | 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.
| MIL | Stat | SF |
|---|---|---|
| 4th of 305.2 | Runs scored | 5.06th of 30 |
| 19th of 304.5 | Runs allowed | 3.97th of 30 |
| 9th of 30+0.7 | Margin | +1.07th of 30 |
| 11th of 305–5 | Last 10 | 5–511th of 30 |
| 17th of 304–7 | Road vs home | 5–315th of 30 |
| 21st of 301497 | Opponent Elo | 15113rd of 30 |
| 7th of 301531 | Elo rating | 151313th 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 |  MIL |  SF |
|---|---|---|
| Run line | 11–13 | 14–10 |
| Last 10 | 6–4 | 5–5 |
| Favorite | 8–7 | 5–7 |
| Underdog | 3–6 | 9–3 |
| Overs–unders | 10–14 | 16–8 |
| Overs–unders, last 10 | 4–6 | 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
MIL 7–8 SF in their last 15 meetings; the forecast called 9 of 15.