ARCHIVE March 29, 2026
March 29, 2026 · NL East

Pittsburgh Pirates vs New York Mets

March 29, 2026Citi FieldSunny 49°F · 4 mph, Out To LF
AWAY
Pittsburgh Pirates
1-2
4
vs
HOME
New York Mets
2-1
3

Starting pitchers

AWAY · PIT
Carmen Mlodzinski
Carmen Mlodzinski
IP 4.1
HOME · NYM
Nolan McLean
Nolan McLean
IP 5

Lineups

AWAY · PIT
  1. 1 Oneil Cruz CF
  2. 2 Brandon Lowe 2B
  3. 3 Bryan Reynolds DH
  4. 4 Ryan O'Hearn RF
  5. 5 Jared Triolo SS
  6. 6 Spencer Horwitz 1B
  7. 7 Nick Gonzales 3B
  8. 8 Henry Davis C
  9. 9 Jake Mangum LF
HOME · NYM
  1. 1 Francisco Lindor SS
  2. 2 Juan Soto LF
  3. 3 Bo Bichette 3B
  4. 4 Jorge Polanco DH
  5. 5 Luis Robert Jr. CF
  6. 6 Brett Baty 1B
  7. 7 Marcus Semien 2B
  8. 8 Carson Benge RF
  9. 9 Luis Torrens C

Box score

  12345678910 R
PIT 1010000002 4
NYM 0100100001 3

Manager comparison

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

AWAY · PIT
Don Kelly
C- Lineup 2.3 R Bunts 0.3 R IBBs 0.8 R
HOME · NYM
Carlos Mendoza
D+ Lineup 2.9 R Bunts 1.4 R IBBs 0.9 R

Recent form

AWAY · PIT
5-5 W2 +1 run diff
WWLWWWLLLL
HOME · NYM
5-4 L1 +2 run diff
LW?WWLWLLW

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 · Pittsburgh Pirates
  • Manager lineup cost +0.14 R/G Optimal arrangement projects 3.15 vs actual lineup 3.01
  • Player execution +0.99 R/G Players exceeded the lineup's 3.01 projection by 0.99 (scored 4)
  • Game variance +0.85 R/G Total game outcome vs optimal expectation

Reynolds 0-for-5 batting 3rd

HOME · New York Mets
  • Manager lineup cost −0.07 R/G Optimal arrangement projects 4.15 vs actual lineup 4.22
  • Player execution −1.22 R/G Players fell 1.22 short of the lineup's 4.22 projection (scored 3)
  • Game variance −1.15 R/G Total game outcome vs optimal expectation

Bichette 0-for-5 batting 3rd

COUNTERFACTUAL

Optimal lineups projected 3.1 – 4.2 — actual was 4 – 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.