ARCHIVE April 5, 2026
April 5, 2026 · NL Cent

Baltimore Orioles vs Pittsburgh Pirates

April 5, 2026PNC ParkPartly Cloudy 45°F · 16 mph, Out To LF
AWAY
Baltimore Orioles
3-6
2
vs
HOME
Pittsburgh Pirates
6-3
8

Starting pitchers

AWAY · BAL
Cade Povich
Cade Povich
IP 5.2
HOME · PIT
Braxton Ashcraft
Braxton Ashcraft
IP 6

Lineups

AWAY · BAL
  1. 1 Taylor Ward LF
  2. 2 Gunnar Henderson SS
  3. 3 Pete Alonso 1B
  4. 4 Samuel Basallo C
  5. 5 Tyler O'Neill RF
  6. 6 Dylan Beavers DH
  7. 7 Leody Taveras CF
  8. 8 Jeremiah Jackson 2B
  9. 9 Blaze Alexander 3B
HOME · PIT
  1. 1 Oneil Cruz CF
  2. 2 Brandon Lowe 2B
  3. 3 Bryan Reynolds DH
  4. 4 Ryan O'Hearn RF
  5. 5 Nick Yorke 3B
  6. 6 Konnor Griffin SS
  7. 7 Spencer Horwitz 1B
  8. 8 Henry Davis C
  9. 9 Jake Mangum LF

Box score

  123456789 R
BAL 000100100 2
PIT 240002000 8

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 −0.01 R/G Optimal arrangement projects 3.95 vs actual lineup 3.96
  • Player execution −1.96 R/G Players fell 1.96 short of the lineup's 3.96 projection (scored 2)
  • Game variance −1.95 R/G Total game outcome vs optimal expectation

Henderson 0-for-4 batting 2nd

HOME · Pittsburgh Pirates
  • Manager lineup cost +0.05 R/G Optimal arrangement projects 2.84 vs actual lineup 2.79
  • Player execution +5.21 R/G Players exceeded the lineup's 2.79 projection by 5.21 (scored 8)
  • Game variance +5.16 R/G Total game outcome vs optimal expectation

Mangum 2-for-4 from the 9-hole

COUNTERFACTUAL

Optimal lineups projected 4.0 – 2.8 — actual was 2 – 8.

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.