ARCHIVE April 18, 2026
April 18, 2026 · NL East

San Francisco Giants vs Washington Nationals

April 18, 2026Nationals ParkCloudy 76°F · 4 mph, R To L
AWAY
San Francisco Giants
9-12
7
vs
HOME
Washington Nationals
9-12
6

Starting pitchers

AWAY · SF
Adrian Houser
Adrian Houser
IP 5.2
HOME · WSH
Cade Cavalli
Cade Cavalli
IP 4

Lineups

AWAY · SF
  1. 1 Willy Adames SS
  2. 2 Luis Arraez 2B
  3. 3 Matt Chapman 3B
  4. 4 Rafael Devers 1B
  5. 5 Casey Schmitt DH
  6. 6 Jung Hoo Lee RF
  7. 7 Heliot Ramos LF
  8. 8 Drew Gilbert CF
  9. 9 Patrick Bailey C
HOME · WSH
  1. 1 James Wood RF
  2. 2 Luis García 1B
  3. 3 José Tena DH
  4. 4 CJ Abrams SS
  5. 5 Jacob Young CF
  6. 6 Daylen Lile LF
  7. 7 Nasim Nuñez 2B
  8. 8 Jorbit Vivas 3B
  9. 9 Drew Millas C

Box score

  123456789101112 R
SF 012002100001 7
WSH 140000001000 6

Manager comparison

Both managers grade B- / C entering this matchup.

AWAY · SF
Tony Vitello
B- Lineup 0.8 R Bunts 0.7 R IBBs 1.4 R
HOME · WSH
Blake Butera
C Lineup 1.6 R Bunts 1.5 R IBBs 1.4 R

Recent form

AWAY · SF
1-8 L2 -25 run diff
LLWLLLLL?L
HOME · WSH
6-4 W3 +6 run diff
WWWLWLLWWL

Season series: 2-1 with SF listed first across 3 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.

AWAY · San Francisco Giants
  • Manager lineup cost −0.02 R/G Optimal arrangement projects 3.74 vs actual lineup 3.76
  • Player execution +3.24 R/G Players exceeded the lineup's 3.76 projection by 3.24 (scored 7)
  • Game variance +3.26 R/G Total game outcome vs optimal expectation

Ramos HR from the 7-hole

HOME · Washington Nationals
  • Manager lineup cost +0.03 R/G Optimal arrangement projects 4.83 vs actual lineup 4.80
  • Player execution +1.20 R/G Players exceeded the lineup's 4.80 projection by 1.20 (scored 6)
  • Game variance +1.17 R/G Total game outcome vs optimal expectation

Mead 0-for-3 batting 2nd

COUNTERFACTUAL

Optimal lineups projected 3.7 – 4.8 — actual was 7 – 6.

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.