ARCHIVE April 5, 2026
April 5, 2026 · NL West

New York Mets vs San Francisco Giants

April 5, 2026Oracle ParkSunny 74°F · 11 mph, Varies
AWAY
New York Mets
6-4
5
vs

Starting pitchers

AWAY · NYM
Kodai Senga
Kodai Senga
IP 5.2
HOME · SF
Logan Webb
Logan Webb
IP 7

Lineups

AWAY · NYM
  1. 1 Francisco Lindor SS
  2. 2 Bo Bichette 3B
  3. 3 Jorge Polanco DH
  4. 4 Luis Robert Jr. CF
  5. 5 Jared Young LF
  6. 6 Mark Vientos 1B
  7. 7 Marcus Semien 2B
  8. 8 Carson Benge RF
  9. 9 Francisco Alvarez C
HOME · SF
  1. 1 Willy Adames SS
  2. 2 Luis Arraez 2B
  3. 3 Matt Chapman 3B
  4. 4 Rafael Devers 1B
  5. 5 Heliot Ramos LF
  6. 6 Jung Hoo Lee RF
  7. 7 Jerar Encarnacion DH
  8. 8 Harrison Bader CF
  9. 9 Patrick Bailey C

Box score

  123456789 R
NYM 010000040 5
SF 000002000 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 · SF
Tony Vitello
B- Lineup 0.8 R Bunts 0.7 R IBBs 1.4 R

Recent form

AWAY · NYM
5-4 L1 +2 run diff
LW?WWLWLLW
HOME · SF
1-8 L2 -25 run diff
LLWLLLLL?L

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 +0.31 R/G Optimal arrangement projects 4.58 vs actual lineup 4.26
  • Player execution +0.74 R/G Players exceeded the lineup's 4.26 projection by 0.74 (scored 5)
  • Game variance +0.42 R/G Total game outcome vs optimal expectation

Lindor 0-for-5 batting 1st

HOME · San Francisco Giants
  • Manager lineup cost +0.05 R/G Optimal arrangement projects 4.77 vs actual lineup 4.72
  • Player execution −2.72 R/G Players fell 2.72 short of the lineup's 4.72 projection (scored 2)
  • Game variance −2.77 R/G Total game outcome vs optimal expectation

Adames 0-for-4 batting 1st

COUNTERFACTUAL

Optimal lineups projected 4.6 – 4.8 — actual was 5 – 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.