ARCHIVE April 1, 2026
April 1, 2026 · NL Cent

New York Mets vs St. Louis Cardinals

April 1, 2026Busch StadiumOvercast 58°F · 7 mph, L To R
AWAY
New York Mets
3-3
1
vs
HOME
St. Louis Cardinals
4-2
2

Starting pitchers

AWAY · NYM
Freddy Peralta
Freddy Peralta
IP 5.1
HOME · STL
Matthew Liberatore
Matthew Liberatore
IP 6

Lineups

AWAY · NYM
  1. 1 Francisco Lindor SS
  2. 2 Juan Soto LF
  3. 3 Bo Bichette 3B
  4. 4 Jorge Polanco DH
  5. 5 Luis Robert CF
  6. 6 Mark Vientos 1B
  7. 7 Marcus Semien 2B
  8. 8 Francisco Alvarez C
  9. 9 Tyrone Taylor RF
HOME · STL
  1. 1 JJ Wetherholt 2B
  2. 2 Iván Herrera DH
  3. 3 Alec Burleson 1B
  4. 4 Masyn Winn SS
  5. 5 Nolan Gorman 3B
  6. 6 Thomas Saggese LF
  7. 7 Nathan Church RF
  8. 8 Pedro Pagés C
  9. 9 Victor Scott CF

Box score

  1234567891011 R
NYM 00000100000 1
STL 00000100001 2

Manager comparison

Both managers grade D+ / B- entering this matchup.

AWAY · NYM
Carlos Mendoza
D+ Lineup 2.9 R Bunts 1.4 R IBBs 0.9 R
HOME · STL
Oliver Marmol
B- Lineup 1.2 R Bunts 0.7 R IBBs 0.3 R

Recent form

AWAY · NYM
5-4 L1 +2 run diff
LW?WWLWLLW
HOME · STL
7-2 W1 +13 run diff
WL?WLWWWWW

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 · New York Mets
  • Manager lineup cost −0.09 R/G Optimal arrangement projects 4.51 vs actual lineup 4.60
  • Player execution −3.60 R/G Players fell 3.60 short of the lineup's 4.60 projection (scored 1)
  • Game variance −3.51 R/G Total game outcome vs optimal expectation

Lindor 0-for-4 batting 1st

HOME · St. Louis Cardinals
  • Manager lineup cost +0.00 R/G Optimal arrangement projects 3.83 vs actual lineup 3.83
  • Player execution −1.83 R/G Players fell 1.83 short of the lineup's 3.83 projection (scored 2)
  • Game variance −1.83 R/G Total game outcome vs optimal expectation

Burleson 0-for-5 batting 3rd

COUNTERFACTUAL

Optimal lineups projected 4.5 – 3.8 — actual was 1 – 2.

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.