ARCHIVE March 31, 2026
March 31, 2026 · NL Cent

Los Angeles Angels vs Chicago Cubs

March 31, 2026Wrigley FieldCloudy 44°F · 14 mph, In From CF
AWAY
Los Angeles Angels
3-3
2
vs
HOME
Chicago Cubs
2-3
0

Starting pitchers

AWAY · LAA
José Soriano
José Soriano
IP 6
HOME · CHC
Jameson Taillon
Jameson Taillon
IP 4.2

Lineups

AWAY · LAA
  1. 1 Zach Neto SS
  2. 2 Mike Trout CF
  3. 3 Nolan Schanuel 1B
  4. 4 Jorge Soler DH
  5. 5 Jeimer Candelario 3B
  6. 6 Jo Adell RF
  7. 7 Josh Lowe LF
  8. 8 Logan O'Hoppe C
  9. 9 Oswald Peraza 2B
HOME · CHC
  1. 1 Michael Busch 1B
  2. 2 Alex Bregman 3B
  3. 3 Ian Happ LF
  4. 4 Pete Crow-Armstrong CF
  5. 5 Nico Hoerner 2B
  6. 6 Dansby Swanson SS
  7. 7 Moisés Ballesteros DH
  8. 8 Matt Shaw RF
  9. 9 Miguel Amaya C

Box score

  123456789 R
LAA 000002000 2
CHC 000000000 0

Manager comparison

Both managers grade C / C entering this matchup.

AWAY · LAA
Kurt Suzuki
C Lineup 1.4 R Bunts 2.0 R IBBs 2.1 R
HOME · CHC
Craig Counsell
C Lineup 1.7 R Bunts 0.4 R IBBs 0.3 R

Recent form

AWAY · LAA
3-7 L1 -10 run diff
LWWLLWLLLL
HOME · CHC
10-0 W10 +27 run diff
WWWWWWWWWW

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 · Los Angeles Angels
  • Manager lineup cost +0.02 R/G Optimal arrangement projects 3.96 vs actual lineup 3.94
  • Player execution −1.94 R/G Players fell 1.94 short of the lineup's 3.94 projection (scored 2)
  • Game variance −1.96 R/G Total game outcome vs optimal expectation

Neto 0-for-4 batting 1st

HOME · Chicago Cubs
  • Manager lineup cost +0.04 R/G Optimal arrangement projects 2.41 vs actual lineup 2.38
  • Player execution −2.38 R/G Players fell 2.38 short of the lineup's 2.38 projection (scored 0)
  • Game variance −2.41 R/G Total game outcome vs optimal expectation

Bregman 0-for-4 batting 2nd

COUNTERFACTUAL

Optimal lineups projected 4.0 – 2.4 — actual was 2 – 0.

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.