Minnesota Twins 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
Twins- Manuel MargotBatting2-4, 2 RBI
- Chris PaddackPitching5.0 IP, 1 ER, 6 K
Giants- Mike YastrzemskiBatting3-3
- Blake SnellPitching7.0 IP, 0 ER, 8 K
Scoring summary
- 9Yastrzemski tripled to right, Yastrzemski scored on throwing error by second baseman Lee.2–3
- 9Pitch 4 : Ball In Play2–3
- 9Pitch 3 : Ball 22–2
- 9Pitch 2 : Strike 1 Looking2–2
- 9Pitch 1 : Ball 12–2
- 9Margot doubled to center, Buxton scored and Castillo scored.2–2
- 9Pitch 5 : Ball In Play2–2
- 9Pitch 4 : Ball 10–2
- 9Pitch 3 : Strike 2 Foul0–2
- 9Pitch 2 : Strike 2 Foul0–2
- 9Pitch 1 : Strike 1 Looking0–2
- 3Bailey singled to center, Wade Jr. scored.0–2
- 3Pitch 1 : Ball In Play0–2
- 2Estrada singled to left, Chapman scored, Yastrzemski to second.0–1
- 2Pitch 1 : Ball In Play0–1
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Giants 59%
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 59%
- ML MIN +135 / SF -160
- Pre-line forecast
- SF 52%
- Elo + market-implied
- Elo ratings
- SF 47%
- Ratings vs. market
- −11.9 pts
- SF: Elo 47.2%, market 59.1%
- Fair odds
- SF -145
- MIN +145 · the forecast as odds, no margin
- Pregame projection
- MIN 3.3 – 4.2 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 | MIN | SF | Why |
|---|---|---|---|
| Team rating | 1530 | 1487 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | −8 | −4 | MIN: Chris Paddack: team allows 0.41 more runs than with its usual starter (≈8 weighted starts) · SF: Blake Snell: team allows 0.19 more runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | MIN +20 Elo | MIN 52.8% | |
| Market-implied ratings | SF 53.0% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 52.1% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | SF 59.1% | 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.
| MIN | Stat | SF |
|---|---|---|
| 7th of 304.9 | Runs scored | 4.415th of 30 |
| 17th of 304.4 | Runs allowed | 4.723rd of 30 |
| 10th of 30+0.5 | Margin | −0.321st of 30 |
| 8th of 306–4 | Last 10 | 4–618th of 30 |
| 6th of 3027–23 | Road vs home | 27–2212th 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 |  MIN |  SF |
|---|---|---|
| Run line | 44–51 | 48–47 |
| Last 10 | 3–7 | 5–5 |
| Favorite | 26–39 | 17–27 |
| Underdog | 18–12 | 31–20 |
| Overs–unders | 47–48 | 53–41–1 |
| Overs–unders, last 10 | 6–4 | 5–5 |
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
MIN 2–3 SF in their last 5 meetings; the forecast called 1 of 5.