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- Luis MatosBatting2-4, 1 HR, 2 RBI
- Robbie RayPitching5.0 IP, 3 ER, 0 K
Brewers- Caleb DurbinBatting2-4, 1 HR, 1 RBI
- Chad PatrickPitching5.1 IP, 2 ER, 7 K
Scoring summary
- 9Ramos singled to center, Chapman scored and Matos scored, Ramos to second, Lee to third.4–3
- 5Durbin homered to left center (381 feet).2–3
- 3Yelich singled to right, Durbin scored, Contreras to second.2–2
- 2Lockridge singled to left, Yelich scored, Jansen to second.2–1
- 2Matos homered to left center (391 feet), Flores scored.2–0
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Brewers 54%
Forecast Elo ratings alone
How often that comes true: MLB favorites the forecast gave 50–55% have won 52.7% of 2,871 graded games.
- Market
- MIL 54%
- ML SF +110 / MIL -130
- Pre-line forecast
- MIL 56%
- Elo + market-implied
- Elo ratings
- MIL 61%
- Ratings vs. market
- +7.0 pts
- MIL: Elo 61.3%, market 54.3%
- Fair odds
- MIL -119
- SF +119 · the forecast as odds, no margin
- Pregame projection
- SF 4.1 – 4.4 MIL
- 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 | MIL | Why |
|---|---|---|---|
| Team rating | 1486 | 1573 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | +13 | −12 | SF: Robbie Ray: team allows 0.63 fewer runs than with its usual starter (≈10 weighted starts) · MIL: Chad Patrick: team allows 0.61 more runs than with its usual starter (≈9 weighted starts) |
| Elo ratings | MIL +80 Elo | MIL 61.3% | |
| Market-implied ratings | MIL 54.9% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | MIL 55.9% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | MIL 54.3% | 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.
| SF | Stat | MIL |
|---|---|---|
| 25th of 304.0 | Runs scored | 5.13rd of 30 |
| 10th of 304.1 | Runs allowed | 3.93rd of 30 |
| 18th of 30−0.1 | Margin | +1.21st of 30 |
| 24th of 303–7 | Last 10 | 5–514th of 30 |
| 10th of 3032–35 | Road vs home | 43–211st of 30 |
| 11th of 301502 | Opponent Elo | 149624th of 30 |
| 21st of 301486 | Elo rating | 15731st 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 | 52–78 | 74–56 |
| Last 10 | 4–6 | 4–6 |
| Favorite | 20–55 | 35–37 |
| Underdog | 32–23 | 39–19 |
| Overs–unders | 62–68 | 63–67 |
| Overs–unders, last 10 | 7–3 | 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 11–8 MIL in their last 19 meetings; the forecast called 12 of 19.