ARCHIVE March 26, 2026
March 26, 2026 · NL East

Texas Rangers vs Philadelphia Phillies

March 26, 2026Citizens Bank ParkPartly Cloudy 76°F · 16 mph, Out To CF
AWAY
Texas Rangers
0-1
3
vs

Starting pitchers

AWAY · TEX
Nathan Eovaldi
Nathan Eovaldi
IP 4.2
HOME · PHI
Cristopher Sánchez
Cristopher Sánchez
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 Josh Jung 3B
  7. 7 Josh Smith 2B
  8. 8 Danny Jansen C
  9. 9 Sam Haggerty LF
HOME · PHI
  1. 1 Trea Turner SS
  2. 2 Kyle Schwarber DH
  3. 3 Bryce Harper 1B
  4. 4 Alec Bohm 3B
  5. 5 Bryson Stott 2B
  6. 6 Adolis García RF
  7. 7 Brandon Marsh LF
  8. 8 J.T. Realmuto C
  9. 9 Justin Crawford CF

Box score

  123456789 R
TEX 000000003 3
PHI 200030000 5

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
LLWLLLWWLL
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 3.16 vs actual lineup 3.13
  • Player execution −0.13 R/G Players fell 0.13 short of the lineup's 3.13 projection (scored 3)
  • Game variance −0.16 R/G Total game outcome vs optimal expectation

Nimmo 0-for-3 batting 1st

HOME · Philadelphia Phillies
  • Manager lineup cost −0.09 R/G Optimal arrangement projects 4.45 vs actual lineup 4.54
  • Player execution +0.46 R/G Players exceeded the lineup's 4.54 projection by 0.46 (scored 5)
  • Game variance +0.55 R/G Total game outcome vs optimal expectation

Harper 0-for-4 batting 3rd

COUNTERFACTUAL

Optimal lineups projected 3.2 – 4.5 — actual was 3 – 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.