ARCHIVE April 8, 2026
April 8, 2026 · NL West

Philadelphia Phillies vs San Francisco Giants

April 8, 2026Oracle ParkPartly Cloudy 63°F · 11 mph, Varies
vs

Starting pitchers

AWAY · PHI
Aaron Nola
Aaron Nola
IP 6
HOME · SF
Tyler Mahle
Tyler Mahle
IP 5.2

Lineups

AWAY · PHI
  1. 1 Trea Turner SS
  2. 2 Kyle Schwarber DH
  3. 3 Bryce Harper 1B
  4. 4 Alec Bohm 3B
  5. 5 Bryson Stott 2B
  6. 6 Adolis García RF
  7. 7 Brandon Marsh LF
  8. 8 Rafael Marchán C
  9. 9 Justin Crawford CF
HOME · SF
  1. 1 Willy Adames SS
  2. 2 Luis Arraez DH
  3. 3 Matt Chapman 3B
  4. 4 Rafael Devers 1B
  5. 5 Jung Hoo Lee RF
  6. 6 Jerar Encarnacion LF
  7. 7 Harrison Bader CF
  8. 8 Patrick Bailey C
  9. 9 Christian Koss 2B

Box score

  123456789 R
PHI 000000000 0
SF 000003020 5

Manager comparison

Both managers grade C- / B- entering this matchup.

AWAY · PHI
Don Mattingly
C- Lineup 2.2 R Bunts 0.4 R IBBs 0.7 R Interim
HOME · SF
Tony Vitello
B- Lineup 0.8 R Bunts 0.7 R IBBs 1.4 R

Recent form

AWAY · PHI
7-3 L2 +3 run diff
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HOME · SF
1-8 L2 -25 run diff
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Season series: 3-1 with PHI listed first across 5 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 · Philadelphia Phillies
  • Manager lineup cost +0.21 R/G Optimal arrangement projects 4.95 vs actual lineup 4.74
  • Player execution −4.74 R/G Players fell 4.74 short of the lineup's 4.74 projection (scored 0)
  • Game variance −4.95 R/G Total game outcome vs optimal expectation

Turner 0-for-3 batting 1st

HOME · San Francisco Giants
  • Manager lineup cost +0.08 R/G Optimal arrangement projects 4.80 vs actual lineup 4.72
  • Player execution +0.28 R/G Players exceeded the lineup's 4.72 projection by 0.28 (scored 5)
  • Game variance +0.20 R/G Total game outcome vs optimal expectation

Lineup spots out of order vs season production

COUNTERFACTUAL

Optimal lineups projected 5.0 – 4.8 — actual was 0 – 5.

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.