ARCHIVE March 28, 2026
March 28, 2026 · NL East

Pittsburgh Pirates vs New York Mets

March 28, 2026Citi FieldSunny 42°F · 4 mph, L To R
AWAY
Pittsburgh Pirates
0-2
2
vs
HOME
New York Mets
2-0
4

Starting pitchers

AWAY · PIT
Mitch Keller
Mitch Keller
IP 6
HOME · NYM
David Peterson
David Peterson
IP 5.1

Lineups

AWAY · PIT
  1. 1 Jared Triolo SS
  2. 2 Ryan O'Hearn 1B
  3. 3 Bryan Reynolds LF
  4. 4 Marcell Ozuna DH
  5. 5 Nick Gonzales 3B
  6. 6 Brandon Lowe 2B
  7. 7 Nick Yorke RF
  8. 8 Joey Bart C
  9. 9 Jake Mangum CF
HOME · NYM
  1. 1 Francisco Lindor SS
  2. 2 Juan Soto LF
  3. 3 Bo Bichette 3B
  4. 4 Jorge Polanco 1B
  5. 5 Luis Robert CF
  6. 6 Brett Baty DH
  7. 7 Marcus Semien 2B
  8. 8 Carson Benge RF
  9. 9 Francisco Alvarez C

Box score

  1234567891011 R
PIT 00000000011 2
NYM 00000000013 4

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 +0.17 R/G Optimal arrangement projects 4.82 vs actual lineup 4.65
  • Player execution −2.65 R/G Players fell 2.65 short of the lineup's 4.65 projection (scored 2)
  • Game variance −2.82 R/G Total game outcome vs optimal expectation

Mangum 2-for-5 from the 9-hole

HOME · New York Mets
  • Manager lineup cost −0.02 R/G Optimal arrangement projects 3.60 vs actual lineup 3.61
  • Player execution +0.39 R/G Players exceeded the lineup's 3.61 projection by 0.39 (scored 4)
  • Game variance +0.40 R/G Total game outcome vs optimal expectation

Lindor 0-for-5 batting 1st

COUNTERFACTUAL

Optimal lineups projected 4.8 – 3.6 — actual was 2 – 4.

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.