Los Angeles Angels vs Toronto Blue Jays
Starting pitchers
Lineups
- 1 Zach Neto SS
- 2 Mike Trout CF
- 3 Nolan Schanuel 1B
- 4 Jorge Soler DH
- 5 Yoán Moncada 3B
- 6 Jo Adell RF
- 7 Josh Lowe LF
- 8 Sebastián Rivero C
- 9 Adam Frazier 2B
- 1 George Springer DH
- 2 Myles Straw RF
- 3 Vladimir Guerrero Jr. 1B
- 4 Kazuma Okamoto 3B
- 5 Daulton Varsho CF
- 6 Ernie Clement 2B
- 7 Davis Schneider LF
- 8 Andrés Giménez SS
- 9 Brandon Valenzuela C
Box score
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | R | |
|---|---|---|---|---|---|---|---|---|---|---|
| LAA | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| TOR | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
Manager comparison
Both managers grade C / B entering this matchup.
Recent form
Season series: 1-3 with LAA listed first across 4 prior meetings.
Tactical analysis
RunsLeft separates manager decisions from player execution from game variance. Each card below is the same three-number framework that drives the share cards on the SPA replay page.
- Manager lineup cost −0.11 R/G Optimal arrangement projects 3.06 vs actual lineup 3.17
- Player execution −3.17 R/G Players fell 3.17 short of the lineup's 3.17 projection (scored 0)
- Game variance −3.06 R/G Total game outcome vs optimal expectation
Soler 0-for-4 batting 4th
- Manager lineup cost −0.11 R/G Optimal arrangement projects 3.91 vs actual lineup 4.02
- Player execution −2.02 R/G Players fell 2.02 short of the lineup's 4.02 projection (scored 2)
- Game variance −1.91 R/G Total game outcome vs optimal expectation
Lineup spots out of order vs season production
Optimal lineups projected 3.1 – 3.9 — actual was 0 – 2.
-
Kurt Suzuki (LAA) has run 30 distinct starting lineups across 30 games this season — that's 100% turnover game-to-game. Most managers stay below 14 for the same span.
-
John Schneider (TOR) has run 30 distinct starting lineups across 30 games this season — that's 100% turnover game-to-game. Most managers stay below 14 for the same span.
Keep reading
How RunsLeft analyzes games
Standard content on this page comes from the MLB Stats API. Tactical analysis comes from a per-game Monte Carlo: 10,000 simulated games against the opposing starter's ERA, both for the actual lineup the manager wrote and for the optimal arrangement of those nine players. The three numbers — manager cost, player execution, game variance — separate which part of the result was the lineup, the players, or the dice.