ARCHIVE April 10, 2026
April 10, 2026 · AL East

San Francisco Giants vs Baltimore Orioles

April 10, 2026Oriole Park at Camden YardsPartly Cloudy 66°F · 7 mph, Out To LF
vs
HOME
Baltimore Orioles
6-7
3

Starting pitchers

AWAY · SF
Landen Roupp
Landen Roupp
IP 6
HOME · BAL
Shane Baz
Shane Baz
IP 5

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 Patrick Bailey C
  9. 9 Harrison Bader CF
HOME · BAL
  1. 1 Gunnar Henderson SS
  2. 2 Taylor Ward LF
  3. 3 Adley Rutschman C
  4. 4 Pete Alonso 1B
  5. 5 Samuel Basallo DH
  6. 6 Dylan Beavers RF
  7. 7 Leody Taveras CF
  8. 8 Jeremiah Jackson 2B
  9. 9 Blaze Alexander 3B

Box score

  123456789 R
SF 001200300 6
BAL 000100002 3

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 · BAL
Craig Albernaz
C+ Lineup 1.2 R Bunts 0.3 R IBBs 1.8 R

Recent form

AWAY · SF
1-8 L2 -25 run diff
LLWLLLLL?L
HOME · BAL
3-7 L2 -25 run diff
LLWWLLLLWL

Season series: 1-2 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 −0.05 R/G Optimal arrangement projects 4.32 vs actual lineup 4.37
  • Player execution +1.63 R/G Players exceeded the lineup's 4.37 projection by 1.63 (scored 6)
  • Game variance +1.68 R/G Total game outcome vs optimal expectation

Arraez 0-for-3 batting 2nd

HOME · Baltimore Orioles
  • Manager lineup cost +0.01 R/G Optimal arrangement projects 3.26 vs actual lineup 3.25
  • Player execution −0.25 R/G Players fell 0.25 short of the lineup's 3.25 projection (scored 3)
  • Game variance −0.26 R/G Total game outcome vs optimal expectation

Alonso 0-for-3 batting 4th

COUNTERFACTUAL

Optimal lineups projected 4.3 – 3.3 — actual was 6 – 3.

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.