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- Caleb DurbinBatting1-4, 1 HR, 2 RBI
- Quinn PriesterPitching4.0 IP, 2 ER, 3 K
Giants- Wilmer FloresBatting2-3, 1 HR, 1 RBI
- Robbie RayPitching5.0 IP, 2 ER, 4 K
Scoring summary
- 8Bailey sacrificed into double play, center to first to second, Wade Jr. scored, Flores thrown out at second.2–5
- 7Lee tripled to center, Adames scored.2–4
- 6Flores homered to left center (399 feet).2–3
- 5Adames grounded into fielder's choice to third, Fitzgerald scored on fielding error by first baseman Hoskins, Yastrzemski out at second.2–2
- 2Bailey singled to right, Ramos scored, Flores to second.2–1
- 2Durbin homered to left center (375 feet), Ortiz scored.2–0
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Giants 55%
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 55%
- ML MIL +115 / SF -135
- Pre-line forecast
- SF 55%
- Elo + market-implied
- Elo ratings
- SF 53%
- Ratings vs. market
- −2.8 pts
- SF: Elo 52.5%, market 55.3%
- Fair odds
- SF -124
- MIL +124 · the forecast as odds, no margin
- Pregame projection
- MIL 3.5 – 4.0 SF
- 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 | MIL | SF | Why |
|---|---|---|---|
| Team rating | 1529 | 1515 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | −8 | +6 | MIL: Quinn Priester: team allows 0.40 more runs than with its usual starter (≈8 weighted starts) · SF: Robbie Ray: team allows 0.32 fewer runs than with its usual starter (≈7 weighted starts) |
| Elo ratings | SF +17 Elo | SF 52.5% | |
| Market-implied ratings | SF 55.3% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 54.9% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | SF 55.3% | 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.
| MIL | Stat | SF |
|---|---|---|
| 5th of 305.1 | Runs scored | 5.06th of 30 |
| 20th of 304.6 | Runs allowed | 3.75th of 30 |
| 9th of 30+0.5 | Margin | +1.43rd of 30 |
| 13th of 305–5 | Last 10 | 5–513th of 30 |
| 20th of 303–6 | Road vs home | 4–210th of 30 |
| 21st of 301495 | Opponent Elo | 15096th of 30 |
| 7th of 301529 | 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 |  MIL |  SF |
|---|---|---|
| Run line | 10–12 | 13–9 |
| Last 10 | 6–4 | 5–5 |
| Favorite | 8–7 | 4–6 |
| Underdog | 2–5 | 9–3 |
| Overs–unders | 9–13 | 15–7 |
| Overs–unders, last 10 | 3–7 | 8–2 |
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 6–7 SF in their last 13 meetings; the forecast called 8 of 13.