ARCHIVE April 5, 2026
April 5, 2026 · AL Cent

Chicago Cubs vs Cleveland Guardians

April 5, 2026Progressive FieldCloudy 44°F · 15 mph, L To R
AWAY
Chicago Cubs
4-4
1
vs
HOME
Cleveland Guardians
5-4
0

Starting pitchers

AWAY · CHC
Edward Cabrera
Edward Cabrera
IP 5.2
HOME · CLE
Slade Cecconi
Slade Cecconi
IP 6

Lineups

AWAY · CHC
  1. 1 Michael Busch 1B
  2. 2 Alex Bregman DH
  3. 3 Ian Happ LF
  4. 4 Pete Crow-Armstrong CF
  5. 5 Nico Hoerner 2B
  6. 6 Dansby Swanson SS
  7. 7 Michael Conforto RF
  8. 8 Matt Shaw 3B
  9. 9 Miguel Amaya C
HOME · CLE
  1. 1 Steven Kwan CF
  2. 2 Chase DeLauter RF
  3. 3 José Ramírez DH
  4. 4 Kyle Manzardo 1B
  5. 5 Bo Naylor C
  6. 6 Daniel Schneemann 3B
  7. 7 Brayan Rocchio 2B
  8. 8 Gabriel Arias SS
  9. 9 CJ Kayfus LF

Box score

  123456789 R
CHC 000000010 1
CLE 000000000 0

Manager comparison

Both managers grade C / C+ entering this matchup.

AWAY · CHC
Craig Counsell
C Lineup 1.7 R Bunts 0.4 R IBBs 0.3 R
HOME · CLE
Stephen Vogt
C+ Lineup 1.5 R Bunts 0.7 R IBBs 0.4 R

Recent form

AWAY · CHC
10-0 W10 +27 run diff
WWWWWWWWWW
HOME · CLE
6-4 W3 +7 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 · Chicago Cubs
  • Manager lineup cost +0.11 R/G Optimal arrangement projects 4.87 vs actual lineup 4.76
  • Player execution −3.76 R/G Players fell 3.76 short of the lineup's 4.76 projection (scored 1)
  • Game variance −3.87 R/G Total game outcome vs optimal expectation

Busch 0-for-4 batting 1st

HOME · Cleveland Guardians
  • Manager lineup cost +0.08 R/G Optimal arrangement projects 3.47 vs actual lineup 3.39
  • Player execution −3.39 R/G Players fell 3.39 short of the lineup's 3.39 projection (scored 0)
  • Game variance −3.47 R/G Total game outcome vs optimal expectation

DeLauter 0-for-3 batting 2nd

COUNTERFACTUAL

Optimal lineups projected 4.9 – 3.5 — actual was 1 – 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.