Toronto Blue Jays 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
Blue Jays- Vladimir Guerrero Jr.Batting3-4, 1 HR, 2 RBI
- Dylan CeasePitching5.0 IP, 2 ER, 12 K
Angels- Nolan SchanuelBatting1-3, 1 RBI
- Reid DetmersPitching6.0 IP, 4 ER, 5 K
Scoring summary
- 9Lukes grounded out to pitcher, Straw scored.5–2
- 7Lukes singled to left, Straw scored.4–2
- 6Sosa hit sacrifice fly to left, Guerrero Jr. scored.3–2
- 3Schanuel hit sacrifice fly to center, Neto scored.2–2
- 3Guerrero Jr. homered to center (430 feet), Schneider scored.2–1
- 1Soler singled to left, Schanuel scored.0–1
The pick
Reconstructed from what was known before the game: the ratings at that point and the closing line.
Blue Jays 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
- TOR 51%
- ML TOR -115 / LAA -105
- Pre-line forecast
- TOR 56%
- Elo + market-implied
- Elo ratings
- TOR 57%
- Ratings vs. market
- +5.5 pts
- TOR: Elo 56.6%, market 51.1%
- Fair odds
- TOR -104
- LAA +104 · the forecast as odds, no margin
- Pregame projection
- TOR 3.8 – 3.7 LAA
- 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 | TOR | LAA | Why |
|---|---|---|---|
| Team rating | 1516 | 1464 | Elo entering the game; 1500 is league average |
| Home field | — | +18 | Worth 18 Elo in MLB |
| Starting pitchers | +10 | −3 | TOR: Dylan Cease: team allows 0.48 fewer runs than with its usual starter (≈10 weighted starts) · LAA: Reid Detmers: team allows 0.13 more runs than with its usual starter (≈10 weighted starts) |
| Elo ratings | TOR +46 Elo | TOR 56.6% | |
| Market-implied ratings | TOR 55.4% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | TOR 55.6% | 15% Elo, 85% market-implied (log-odds blend) | |
| Forecast | TOR 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.
| TOR | Stat | LAA |
|---|---|---|
| 23rd of 304.0 | Runs scored | 5.09th of 30 |
| 25th of 305.2 | Runs allowed | 4.516th of 30 |
| 27th of 30−1.2 | Margin | +0.510th of 30 |
| 21st of 304–6 | Last 10 | 5–513th of 30 |
| 26th of 302–7 | Road vs home | 4–525th of 30 |
| 25th of 301491 | Opponent Elo | 15221st of 30 |
| 8th of 301516 | Elo rating | 146427th 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 |  TOR |  LAA |
|---|---|---|
| Run line | 7–14 | 14–9 |
| Last 10 | 5–5 | 8–2 |
| Favorite | 3–10 | 1–1 |
| Underdog | 4–4 | 13–8 |
| Overs–unders | 11–10 | 12–11 |
| Overs–unders, last 10 | 6–4 | 5–5 |
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
TOR 15–4 LAA in their last 19 meetings; the forecast called 12 of 19.