San Francisco Giants at Minnesota Twins, 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 MIN.
Game center
From the ESPN box score.
Top performers
Giants- Matt ChapmanBatting1-3, 1 HR, 1 RBI
- Jordan HicksPitching6.0 IP, 3 ER, 6 K
Twins- Carlos CorreaBatting2-4, 1 RBI
- Chris PaddackPitching7.1 IP, 1 ER, 6 K
Scoring summary
- 7Chapman homered to left center (418 feet).1–3
- 5Buxton singled to left, Bader scored on fielding error by left fielder Ramos, Clemens to second.0–3
- 4Correa singled to right, France scored, Correa out stretching at second.0–2
- 1Larnach singled to left, Buxton scored.0–1
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Giants 51%
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
- SF 51%
- ML SF -115 / MIN -105
- Pre-line forecast
- SF 48%
- Elo + market-implied
- Elo ratings
- SF 50%
- Ratings vs. market
- −1.4 pts
- SF: Elo 49.6%, market 51.1%
- Fair odds
- SF -104
- MIN +104 · the forecast as odds, no margin
- Pregame projection
- SF 4.3 – 4.2 MIN
- 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 | MIN | Why |
|---|---|---|---|
| Team rating | 1519 | 1498 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | −12 | −7 | SF: Jordan Hicks: team allows 0.60 more runs than with its usual starter (≈9 weighted starts) · MIN: Chris Paddack: team allows 0.34 more runs than with its usual starter (≈9 weighted starts) |
| Elo ratings | MIN +2 Elo | MIN 50.4% | |
| Market-implied ratings | MIN 51.9% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | MIN 51.6% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | SF 51.1% | 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 | MIN |
|---|---|---|
| 8th of 304.8 | Runs scored | 4.019th of 30 |
| 8th of 303.8 | Runs allowed | 3.66th of 30 |
| 6th of 30+1.0 | Margin | +0.414th of 30 |
| 8th of 306–4 | Last 10 | 6–48th of 30 |
| 4th of 3012–9 | Road vs home | 12–610th of 30 |
| 15th of 301501 | Opponent Elo | 149325th of 30 |
| 13th of 301519 | Elo rating | 149818th 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 |  MIN |
|---|---|---|
| Run line | 20–18 | 22–16 |
| Last 10 | 5–5 | 8–2 |
| Favorite | 9–12 | 13–8 |
| Underdog | 11–6 | 9–8 |
| Overs–unders | 23–15 | 14–24 |
| Overs–unders, last 10 | 6–4 | 3–7 |
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 4–2 MIN in their last 6 meetings; the forecast called 2 of 6.