San Francisco Giants at Tampa Bay Rays, 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 TB.
Game center
From the ESPN box score.
Top performers
Giants- Casey SchmittBatting2-4, 1 RBI
- Tyler MahlePitching5.1 IP, 0 ER, 5 K
Rays- Jonathan ArandaBatting4-5, 1 RBI
- Steven MatzPitching6.0 IP, 1 ER, 1 K
Scoring summary
- 10Aranda singled to right, Simpson scored, Caminero to third.1–2
- 8Vilade hit sacrifice bunt, Caminero scored, Aranda to second.1–1
- 1Schmitt singled to center, Devers scored.1–0
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Rays 54%
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 54%
- ML SF +107 / TB -128
- Pre-line forecast
- TB 55%
- Elo + market-implied
- Elo ratings
- TB 55%
- Ratings vs. market
- +1.4 pts
- TB: Elo 55.1%, market 53.7%
- Fair odds
- TB -116
- SF +116 · the forecast as odds, no margin
- Pregame projection
- SF 3.8 – 4.2 TB
- Margin from the forecast, posted total 8
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 | TB | Why |
|---|---|---|---|
| Team rating | 1487 | 1508 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | 0 | −3 | SF: Tyler Mahle: team allows 0.01 more runs than with its usual starter (≈10 weighted starts) · TB: Steven Matz: team allows 0.13 more runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | TB +36 Elo | TB 55.1% | |
| Market-implied ratings | TB 55.0% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | TB 55.0% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | TB 53.7% | 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 | TB |
|---|---|---|
| 30th of 303.2 | Runs scored | 4.513th of 30 |
| 9th of 304.2 | Runs allowed | 4.313th of 30 |
| 28th of 30−1.0 | Margin | +0.28th of 30 |
| 27th of 303–7 | Last 10 | 8–21st of 30 |
| 22nd of 306–11 | Road vs home | 10–43rd of 30 |
| 9th of 301505 | Opponent Elo | 150413th of 30 |
| 21st of 301487 | Elo rating | 150813th 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 |  TB |
|---|---|---|
| Run line | 16–17 | 21–11 |
| Last 10 | 5–5 | 8–2 |
| Favorite | 5–4 | 11–5 |
| Underdog | 11–13 | 10–6 |
| Overs–unders | 14–16–3 | 16–14–2 |
| Overs–unders, last 10 | 4–6 | 2–8 |
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 3–8 TB in their last 11 meetings; the forecast called 5 of 11.