San Francisco Giants at Los Angeles Angels, 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 LAA.
Game center
From the ESPN box score.
Top performers
Giants- Sam HuffBatting2-3, 1 HR, 2 RBI
- Justin VerlanderPitching6.0 IP, 1 ER, 6 K
Angels- Zach NetoBatting1-3, 1 HR, 2 RBI
- Yusei KikuchiPitching5.1 IP, 0 ER, 6 K
Scoring summary
- 9Adell doubled to left, Neto scored, Soler scored and Newman scored.4–5
- 9Neto hit by pitch, Trout scored, Newman to second, Soler to third.4–2
- 8Adames singled to center, Fitzgerald scored, Ramos to second.4–1
- 6Huff homered to center (397 feet), Villar scored.3–1
- 5Neto homered to center (428 feet).1–1
- 5Adames singled to left, Ramos scored.1–0
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Angels 52%
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
- LAA 52%
- ML SF +100 / LAA -120
- Pre-line forecast
- LAA 48%
- Elo + market-implied
- Elo ratings
- LAA 45%
- Ratings vs. market
- −7.7 pts
- LAA: Elo 44.5%, market 52.2%
- Fair odds
- LAA -109
- SF +109 · the forecast as odds, no margin
- Pregame projection
- SF 4.2 – 4.3 LAA
- 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 | LAA | Why |
|---|---|---|---|
| Team rating | 1516 | 1451 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | −17 | −9 | SF: Justin Verlander: team allows 0.87 more runs than with its usual starter (≈10 weighted starts) · LAA: Yusei Kikuchi: team allows 0.43 more runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | SF +38 Elo | SF 55.5% | |
| Market-implied ratings | SF 50.9% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 51.6% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | LAA 52.2% | 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.
| SF | Stat | LAA |
|---|---|---|
| 5th of 305.1 | Runs scored | 4.219th of 30 |
| 4th of 303.6 | Runs allowed | 4.722nd of 30 |
| 3rd of 30+1.5 | Margin | −0.520th of 30 |
| 7th of 306–4 | Last 10 | 3–725th of 30 |
| 1st of 3010–5 | Road vs home | 3–216th of 30 |
| 5th of 301513 | Opponent Elo | 149025th of 30 |
| 13th of 301516 | Elo rating | 145128th 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 |  LAA |
|---|---|---|
| Run line | 12–9 | 10–10 |
| Last 10 | 5–5 | 5–5 |
| Favorite | 4–6 | 1–5 |
| Underdog | 8–3 | 9–5 |
| Overs–unders | 14–7 | 10–10 |
| Overs–unders, last 10 | 8–2 | 4–6 |
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 3–5 LAA in their last 8 meetings; the forecast called 4 of 8.