Tampa Bay Rays 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
Rays- Yandy DiazBatting2-4, 1 RBI
- Adrian HouserPitching5.0 IP, 0 ER, 6 K
Giants- Christian KossBatting2-4, 1 RBI
- Justin VerlanderPitching7.0 IP, 0 ER, 8 K
Scoring summary
- 8B. Lowe singled to left, Simpson scored, Díaz to second.2–1
- 8Díaz singled to center, Gray scored, Simpson to third.1–1
- 6Koss singled to left, Adames scored, Smith to second.0–1
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Rays 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
- TB 51%
- ML TB -115 / SF -105
- Pre-line forecast
- TB 50%
- Elo + market-implied
- Elo ratings
- TB 53%
- Ratings vs. market
- +2.1 pts
- TB: Elo 53.2%, market 51.1%
- Fair odds
- TB -104
- SF +104 · the forecast as odds, no margin
- Pregame projection
- TB 3.8 – 3.7 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 | TB | SF | Why |
|---|---|---|---|
| Team rating | 1506 | 1486 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | +7 | −14 | TB: Adrian Houser: team allows 0.35 fewer runs than with its usual starter (≈10 weighted starts) · SF: Justin Verlander: team allows 0.69 more runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | TB +22 Elo | TB 53.2% | |
| Market-implied ratings | SF 50.9% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 50.3% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | TB 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.
| TB | Stat | SF |
|---|---|---|
| 12th of 304.5 | Runs scored | 4.124th of 30 |
| 10th of 304.1 | Runs allowed | 4.19th of 30 |
| 11th of 30+0.4 | Margin | −0.117th of 30 |
| 13th of 305–5 | Last 10 | 3–725th of 30 |
| 18th of 3028–33 | Road vs home | 29–3225th of 30 |
| 9th of 301503 | Opponent Elo | 149918th of 30 |
| 15th of 301506 | Elo rating | 148621st 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 |  TB |  SF |
|---|---|---|
| Run line | 62–61 | 48–74 |
| Last 10 | 5–5 | 3–7 |
| Favorite | 22–39 | 19–54 |
| Underdog | 40–22 | 29–20 |
| Overs–unders | 52–71 | 57–65 |
| Overs–unders, last 10 | 6–4 | 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
TB 5–2 SF in their last 7 meetings; the forecast called 2 of 7.