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- Luke KeaschallBatting1-3, 1 HR, 2 RBI
- Connor PrielippPitching5.1 IP, 2 ER, 3 K
Giants- Shay WhitcombBatting2-4, 2 RBI
- Cesar PerdomoPitching5.1 IP, 2 ER, 2 K
Scoring summary
- 7Bell singled to center, Jenkins scored, Lee to third.4–2
- 7Jenkins singled to right, Clemens scored.3–2
- 5Keaschall hit sacrifice fly to center, Ross scored.2–2
- 4Whitcomb singled to right, Davidson scored and Knizner scored, Mayer to third.1–2
- 3Keaschall homered to left (381 feet).1–0
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Twins 58%
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
- MIN 58%
- ML MIN -155 / SF +129
- Pre-line forecast
- MIN 53%
- Elo + market-implied
- Elo ratings
- MIN 47%
- Ratings vs. market
- −11.2 pts
- MIN: Elo 47.0%, market 58.2%
- Fair odds
- MIN -139
- SF +139 · the forecast as odds, no margin
- Pregame projection
- MIN 4.1 – 3.4 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 | 1468 | 1471 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | −2 | −3 | MIN: Connor Prielipp: team allows 0.12 more runs than with its usual starter (≈9 weighted starts) · SF: Cesar Perdomo: team allows 0.13 more runs than with its usual starter (≈3 weighted starts) |
| Elo ratings | SF +21 Elo | SF 53.0% | |
| Market-implied ratings | MIN 53.8% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | MIN 52.8% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | MIN 58.2% | 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.
| MIN | Stat | SF |
|---|---|---|
| 11th of 304.5 | Runs scored | 4.224th of 30 |
| 26th of 305.0 | Runs allowed | 4.723rd of 30 |
| 24th of 30−0.4 | Margin | −0.525th of 30 |
| 17th of 304–6 | Last 10 | 3–726th of 30 |
| 22nd of 3034–46 | Road vs home | 37–4022nd of 30 |
| 15th of 301500 | Opponent Elo | 150111th of 30 |
| 26th of 301468 | Elo rating | 147125th 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 | 79–79 | 80–78 |
| Last 10 | 5–5 | 6–4 |
| Favorite | 20–41 | 20–30 |
| Underdog | 59–38 | 60–48 |
| Overs–unders | 84–62–12 | 75–70–13 |
| Overs–unders, last 10 | 6–3–1 | 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
MIN 6–5 SF in their last 11 meetings; the forecast called 4 of 11.