ARCHIVE April 13, 2026
April 13, 2026 · AL West

Texas Rangers vs Oakland Athletics

April 13, 2026Sutter Health ParkClear 66°F · 5 mph, Out To RF
AWAY
Texas Rangers
9-7
8
vs
HOME
Oakland Athletics
8-8
1

Starting pitchers

AWAY · TEX
Nathan Eovaldi
Nathan Eovaldi
IP 7
HOME · ATH
Luis Severino
Luis Severino
IP 6

Lineups

AWAY · TEX
  1. 1 Brandon Nimmo RF
  2. 2 Evan Carter CF
  3. 3 Corey Seager SS
  4. 4 Jake Burger 1B
  5. 5 Joc Pederson DH
  6. 6 Kyle Higashioka C
  7. 7 Josh Smith 2B
  8. 8 Josh Jung 3B
  9. 9 Ezequiel Duran LF
HOME · ATH
  1. 1 Lawrence Butler RF
  2. 2 Nick Kurtz 1B
  3. 3 Shea Langeliers C
  4. 4 Tyler Soderstrom LF
  5. 5 Jacob Wilson SS
  6. 6 Jeff McNeil 2B
  7. 7 Max Muncy 3B
  8. 8 Carlos Cortes DH
  9. 9 Denzel Clarke CF

Box score

  123456789 R
TEX 301000040 8
ATH 000000010 1

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 · ATH
Mark Kotsay
C- Lineup 2.6 R Bunts 1.1 R IBBs 1.1 R

Recent form

AWAY · TEX
3-7 L2 -20 run diff
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HOME · ATH
5-5 W2 -1 run diff
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Season series: 3-4 with TEX listed first across 7 prior meetings.

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 +0.04 R/G Optimal arrangement projects 4.02 vs actual lineup 3.99
  • Player execution +4.01 R/G Players exceeded the lineup's 3.99 projection by 4.01 (scored 8)
  • Game variance +3.98 R/G Total game outcome vs optimal expectation

Carter 0-for-4 batting 2nd

HOME · Oakland Athletics
  • Manager lineup cost +0.07 R/G Optimal arrangement projects 4.55 vs actual lineup 4.48
  • Player execution −3.48 R/G Players fell 3.48 short of the lineup's 4.48 projection (scored 1)
  • Game variance −3.55 R/G Total game outcome vs optimal expectation

Kurtz 0-for-3 batting 2nd

COUNTERFACTUAL

Optimal lineups projected 4.0 – 4.5 — actual was 8 – 1.

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.