Kansas City Royals 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
Royals- Vinnie PasquantinoBatting2-4, 1 HR, 2 RBI
- Kris BubicPitching7.0 IP, 0 ER, 5 K
Giants- Jung Hoo LeeBatting1-4, 1 RBI
- Robbie RayPitching7.0 IP, 0 ER, 7 K
Scoring summary
- 9Isbel singled to center, Garcia scored, Renfroe thrown out at third.3–1
- 8Lee doubled to right, Huff scored, Ramos to third.2–1
- 8Pasquantino homered to right center (399 feet), Biggio scored.2–0
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Giants 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
- SF 54%
- ML KC +110 / SF -130
- Pre-line forecast
- SF 54%
- Elo + market-implied
- Elo ratings
- SF 56%
- Ratings vs. market
- +1.8 pts
- SF: Elo 56.0%, market 54.3%
- Fair odds
- SF -119
- KC +119 · the forecast as odds, no margin
- Pregame projection
- KC 3.6 – 3.9 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 | KC | SF | Why |
|---|---|---|---|
| Team rating | 1504 | 1520 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | +5 | +13 | KC: Kris Bubic: team allows 0.26 fewer runs than with its usual starter (≈7 weighted starts) · SF: Robbie Ray: team allows 0.66 fewer runs than with its usual starter (≈8 weighted starts) |
| Elo ratings | SF +42 Elo | SF 56.0% | |
| Market-implied ratings | SF 53.1% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | SF 53.5% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | SF 54.3% | 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.
| KC | Stat | SF |
|---|---|---|
| 27th of 303.3 | Runs scored | 4.710th of 30 |
| 2nd of 303.3 | Runs allowed | 3.78th of 30 |
| 18th of 300.0 | Margin | +1.06th of 30 |
| 19th of 304–6 | Last 10 | 5–513th of 30 |
| 22nd of 309–13 | Road vs home | 16–76th of 30 |
| 23rd of 301496 | Opponent Elo | 150211th of 30 |
| 17th of 301504 | Elo rating | 152012th 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 |  KC |  SF |
|---|---|---|
| Run line | 22–26 | 24–23 |
| Last 10 | 4–6 | 5–5 |
| Favorite | 8–17 | 10–16 |
| Underdog | 14–9 | 14–7 |
| Overs–unders | 17–31 | 27–20 |
| Overs–unders, last 10 | 4–6 | 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
KC 2–4 SF in their last 6 meetings; the forecast called 1 of 6.