ARCHIVE April 3, 2026
April 3, 2026 · NL Cent

Baltimore Orioles vs Pittsburgh Pirates

April 3, 2026PNC ParkCloudy 75°F · 16 mph, Out To LF
AWAY
Baltimore Orioles
3-4
4
vs
HOME
Pittsburgh Pirates
4-3
5

Starting pitchers

AWAY · BAL
Kyle Bradish
Kyle Bradish
IP 4
HOME · PIT
Mitch Keller
Mitch Keller
IP 6

Lineups

AWAY · BAL
  1. 1 Taylor Ward LF
  2. 2 Gunnar Henderson SS
  3. 3 Pete Alonso 1B
  4. 4 Adley Rutschman C
  5. 5 Samuel Basallo DH
  6. 6 Dylan Beavers RF
  7. 7 Jeremiah Jackson 2B
  8. 8 Colton Cowser CF
  9. 9 Blaze Alexander 3B
HOME · PIT
  1. 1 Oneil Cruz CF
  2. 2 Brandon Lowe 2B
  3. 3 Bryan Reynolds LF
  4. 4 Marcell Ozuna DH
  5. 5 Ryan O'Hearn RF
  6. 6 Spencer Horwitz 1B
  7. 7 Konnor Griffin SS
  8. 8 Jared Triolo 3B
  9. 9 Henry Davis C

Box score

  123456789 R
BAL 000020101 4
PIT 040010000 5

Manager comparison

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

AWAY · BAL
Craig Albernaz
C+ Lineup 1.2 R Bunts 0.3 R IBBs 1.8 R
HOME · PIT
Don Kelly
C- Lineup 2.3 R Bunts 0.3 R IBBs 0.8 R

Recent form

AWAY · BAL
3-7 L2 -25 run diff
LLWWLLLLWL
HOME · PIT
5-5 W2 +1 run diff
WWLWWWLLLL

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 · Baltimore Orioles
  • Manager lineup cost −0.05 R/G Optimal arrangement projects 3.63 vs actual lineup 3.68
  • Player execution +0.32 R/G Players exceeded the lineup's 3.68 projection by 0.32 (scored 4)
  • Game variance +0.37 R/G Total game outcome vs optimal expectation

Alonso 0-for-4 batting 3rd

HOME · Pittsburgh Pirates
  • Manager lineup cost +0.05 R/G Optimal arrangement projects 4.09 vs actual lineup 4.04
  • Player execution +0.96 R/G Players exceeded the lineup's 4.04 projection by 0.96 (scored 5)
  • Game variance +0.91 R/G Total game outcome vs optimal expectation

Ozuna 0-for-3 batting 4th

COUNTERFACTUAL

Optimal lineups projected 3.6 – 4.1 — actual was 4 – 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.