ARCHIVE March 28, 2026
March 28, 2026 · NL West

New York Yankees vs San Francisco Giants

March 28, 2026Oracle ParkSunny 61°F · 13 mph, Varies
AWAY
New York Yankees
3-0
3
vs

Starting pitchers

AWAY · NYY
Will Warren
Will Warren
IP 4.1
HOME · SF
Tyler Mahle
Tyler Mahle
IP 4

Lineups

AWAY · NYY
  1. 1 Trent Grisham CF
  2. 2 Aaron Judge RF
  3. 3 Cody Bellinger LF
  4. 4 Ben Rice 1B
  5. 5 Giancarlo Stanton DH
  6. 6 Jazz Chisholm Jr. 2B
  7. 7 José Caballero SS
  8. 8 Ryan McMahon 3B
  9. 9 Austin Wells C
HOME · SF
  1. 1 Jung Hoo Lee RF
  2. 2 Matt Chapman 3B
  3. 3 Luis Arraez 2B
  4. 4 Rafael Devers DH
  5. 5 Heliot Ramos LF
  6. 6 Willy Adames SS
  7. 7 Harrison Bader CF
  8. 8 Patrick Bailey C
  9. 9 Casey Schmitt 1B

Box score

  123456789 R
NYY 002010000 3
SF 001000000 1

Manager comparison

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

AWAY · NYY
Aaron Boone
C+ Lineup 1.5 R Bunts 0.0 R IBBs 1.1 R
HOME · SF
Tony Vitello
B- Lineup 0.8 R Bunts 0.7 R IBBs 1.4 R

Recent form

AWAY · NYY
7-3 L1 +26 run diff
LWLWWWWWLW
HOME · SF
1-8 L2 -25 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 · New York Yankees
  • Manager lineup cost −0.05 R/G Optimal arrangement projects 5.04 vs actual lineup 5.09
  • Player execution −2.09 R/G Players fell 2.09 short of the lineup's 5.09 projection (scored 3)
  • Game variance −2.04 R/G Total game outcome vs optimal expectation

Lineup spots out of order vs season production

HOME · San Francisco Giants
  • Manager lineup cost +0.08 R/G Optimal arrangement projects 2.77 vs actual lineup 2.69
  • Player execution −1.69 R/G Players fell 1.69 short of the lineup's 2.69 projection (scored 1)
  • Game variance −1.77 R/G Total game outcome vs optimal expectation

Lineup spots out of order vs season production

COUNTERFACTUAL

Optimal lineups projected 5.0 – 2.8 — actual was 3 – 1.

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.