ARCHIVE March 27, 2026
March 27, 2026 · AL East

Oakland Athletics vs Toronto Blue Jays

March 27, 2026Rogers CentreRoof Closed 68°F · 0 mph, None
AWAY
Oakland Athletics
0-1
2
vs
HOME
Toronto Blue Jays
1-0
3

Starting pitchers

AWAY · ATH
Luis Severino
Luis Severino
IP 5
HOME · TOR
Kevin Gausman
Kevin Gausman
IP 6

Lineups

AWAY · ATH
  1. 1 Nick Kurtz 1B
  2. 2 Shea Langeliers C
  3. 3 Tyler Soderstrom LF
  4. 4 Brent Rooker DH
  5. 5 Jacob Wilson SS
  6. 6 Lawrence Butler RF
  7. 7 Max Muncy 3B
  8. 8 Jeff McNeil 2B
  9. 9 Denzel Clarke CF
HOME · TOR
  1. 1 George Springer DH
  2. 2 Nathan Lukes LF
  3. 3 Vladimir Guerrero 1B
  4. 4 Addison Barger RF
  5. 5 Alejandro Kirk C
  6. 6 Daulton Varsho CF
  7. 7 Kazuma Okamoto 3B
  8. 8 Ernie Clement 2B
  9. 9 Andrés Giménez SS

Box score

  123456789 R
ATH 000100001 2
TOR 000020001 3

Manager comparison

Both managers grade C- / B entering this matchup.

AWAY · ATH
Mark Kotsay
C- Lineup 2.6 R Bunts 1.1 R IBBs 1.1 R
HOME · TOR
John Schneider
B Lineup 0.3 R Bunts 1.5 R IBBs 1.3 R

Recent form

AWAY · ATH
5-5 W2 -1 run diff
WWLLWLLWWL
HOME · TOR
5-5 W1 +8 run diff
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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.

AWAY · Oakland Athletics
  • Manager lineup cost +0.04 R/G Optimal arrangement projects 3.64 vs actual lineup 3.61
  • Player execution −1.61 R/G Players fell 1.61 short of the lineup's 3.61 projection (scored 2)
  • Game variance −1.64 R/G Total game outcome vs optimal expectation

Kurtz 0-for-4 batting 1st

HOME · Toronto Blue Jays
  • Manager lineup cost −0.10 R/G Optimal arrangement projects 3.87 vs actual lineup 3.97
  • Player execution −0.97 R/G Players fell 0.97 short of the lineup's 3.97 projection (scored 3)
  • Game variance −0.87 R/G Total game outcome vs optimal expectation

Springer 0-for-4 batting 1st

COUNTERFACTUAL

Optimal lineups projected 3.6 – 3.9 — actual was 2 – 3.

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.

Read the full methodology.