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

Texas Rangers vs Philadelphia Phillies

March 29, 2026Citizens Bank ParkSunny 54°F · 13 mph, Out To CF
AWAY
Texas Rangers
2-1
8
vs

Starting pitchers

AWAY · TEX
MacKenzie Gore
MacKenzie Gore
IP 5.1
HOME · PHI
Jesús Luzardo
Jesús Luzardo
IP 6

Lineups

AWAY · TEX
  1. 1 Brandon Nimmo RF
  2. 2 Wyatt Langford CF
  3. 3 Corey Seager SS
  4. 4 Jake Burger 1B
  5. 5 Andrew McCutchen DH
  6. 6 Kyle Higashioka C
  7. 7 Josh Jung 3B
  8. 8 Sam Haggerty LF
  9. 9 Ezequiel Duran 2B
HOME · PHI
  1. 1 Trea Turner SS
  2. 2 Kyle Schwarber DH
  3. 3 Bryce Harper 1B
  4. 4 Alec Bohm 3B
  5. 5 Adolis García RF
  6. 6 Edmundo Sosa 2B
  7. 7 J.T. Realmuto C
  8. 8 Otto Kemp LF
  9. 9 Justin Crawford CF

Box score

  123456789 R
TEX 002301200 8
PHI 000002010 3

Manager comparison

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

AWAY · TEX
Skip Schumaker
B- Lineup 1.0 R Bunts 0.3 R IBBs 0.9 R
HOME · PHI
Don Mattingly
C- Lineup 2.2 R Bunts 0.4 R IBBs 0.7 R Interim

Recent form

AWAY · TEX
3-7 L2 -20 run diff
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HOME · PHI
7-3 L2 +3 run diff
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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 · Texas Rangers
  • Manager lineup cost +0.03 R/G Optimal arrangement projects 4.75 vs actual lineup 4.72
  • Player execution +3.28 R/G Players exceeded the lineup's 4.72 projection by 3.28 (scored 8)
  • Game variance +3.25 R/G Total game outcome vs optimal expectation

Langford 0-for-5 batting 2nd

HOME · Philadelphia Phillies
  • Manager lineup cost +0.12 R/G Optimal arrangement projects 4.15 vs actual lineup 4.03
  • Player execution −1.03 R/G Players fell 1.03 short of the lineup's 4.03 projection (scored 3)
  • Game variance −1.15 R/G Total game outcome vs optimal expectation

Turner 0-for-4 batting 1st

COUNTERFACTUAL

Optimal lineups projected 4.8 – 4.2 — actual was 8 – 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.