San Francisco Giants at Milwaukee Brewers, 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 MIL.
Game center
From the ESPN box score.
Top performers
Giants- Casey SchmittBatting2-4, 1 HR, 4 RBI
- Logan WebbPitching6.0 IP, 1 ER, 5 K
Brewers- Christian YelichBatting2-4
- Freddy PeraltaPitching5.0 IP, 0 ER, 6 K
Scoring summary
- 7Bailey singled to center, Chapman scored.7–1
- 7Schmitt homered to left center (382 feet), Devers scored and Smith scored.6–1
- 6Matos grounded into fielder's choice to third, Smith scored and Schmitt scored on fielding error by third baseman Seigler.3–1
- 6Schmitt doubled to left, Adames scored, Smith to third.1–1
- 2Durbin doubled to right, Bauers scored.0–1
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Brewers 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
- MIL 57%
- ML SF +120 / MIL -145
- Pre-line forecast
- MIL 58%
- Elo + market-implied
- Elo ratings
- MIL 65%
- Ratings vs. market
- +8.1 pts
- MIL: Elo 64.7%, market 56.6%
- Fair odds
- MIL -130
- SF +130 · the forecast as odds, no margin
- Pregame projection
- SF 3.5 – 4.0 MIL
- Margin from the forecast, posted total 7.5
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 | MIL | Why |
|---|---|---|---|
| Team rating | 1482 | 1577 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | +13 | +5 | SF: Logan Webb: team allows 0.63 fewer runs than with its usual starter (≈10 weighted starts) · MIL: Freddy Peralta: team allows 0.27 fewer runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | MIL +105 Elo | MIL 64.7% | |
| Market-implied ratings | MIL 56.4% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | MIL 57.6% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | MIL 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.
| SF | Stat | MIL |
|---|---|---|
| 25th of 304.0 | Runs scored | 5.12nd of 30 |
| 11th of 304.2 | Runs allowed | 3.83rd of 30 |
| 19th of 30−0.1 | Margin | +1.31st of 30 |
| 28th of 302–8 | Last 10 | 6–43rd of 30 |
| 14th of 3031–35 | Road vs home | 43–201st of 30 |
| 11th of 301502 | Opponent Elo | 149626th of 30 |
| 22nd of 301482 | Elo rating | 15771st 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 |  MIL |
|---|---|---|
| Run line | 51–78 | 74–55 |
| Last 10 | 3–7 | 5–5 |
| Favorite | 20–55 | 35–36 |
| Underdog | 31–23 | 39–19 |
| Overs–unders | 61–68 | 62–67 |
| Overs–unders, last 10 | 6–4 | 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
SF 10–8 MIL in their last 18 meetings; the forecast called 12 of 18.