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

Toronto Blue Jays vs Chicago White Sox

April 5, 2026Rate FieldPartly Cloudy 50°F · 4 mph, Out To LF
AWAY
Toronto Blue Jays
4-5
0
vs
HOME
Chicago White Sox
4-5
3

Starting pitchers

AWAY · TOR
Austin Voth
Austin Voth
IP 2.2
HOME · CWS
Davis Martin
Davis Martin
IP 6

Lineups

AWAY · TOR
  1. 1 George Springer DH
  2. 2 Nathan Lukes LF
  3. 3 Vladimir Guerrero Jr. 1B
  4. 4 Addison Barger RF
  5. 5 Kazuma Okamoto 3B
  6. 6 Daulton Varsho CF
  7. 7 Ernie Clement 2B
  8. 8 Andrés Giménez SS
  9. 9 Brandon Valenzuela C
HOME · CWS
  1. 1 Chase Meidroth 2B
  2. 2 Austin Hays LF
  3. 3 Munetaka Murakami 1B
  4. 4 Miguel Vargas 3B
  5. 5 Edgar Quero C
  6. 6 Lenyn Sosa DH
  7. 7 Tanner Murray SS
  8. 8 Luisangel Acuña CF
  9. 9 Derek Hill RF

Box score

  123456789 R
TOR 000000000 0
CWS 101100000 3

Manager comparison

Both managers grade B / D- entering this matchup.

AWAY · TOR
John Schneider
B Lineup 0.3 R Bunts 1.5 R IBBs 1.3 R
HOME · CWS
Will Venable
D- Lineup 3.2 R Bunts 2.2 R IBBs 1.1 R

Recent form

AWAY · TOR
5-5 W1 +8 run diff
WLLLLWWLWW
HOME · CWS
6-4 L3 +9 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 · Toronto Blue Jays
  • Manager lineup cost −0.03 R/G Optimal arrangement projects 2.34 vs actual lineup 2.37
  • Player execution −2.37 R/G Players fell 2.37 short of the lineup's 2.37 projection (scored 0)
  • Game variance −2.34 R/G Total game outcome vs optimal expectation

Lukes 0-for-4 batting 2nd

HOME · Chicago White Sox
  • Manager lineup cost +0.15 R/G Optimal arrangement projects 3.60 vs actual lineup 3.45
  • Player execution −0.45 R/G Players fell 0.45 short of the lineup's 3.45 projection (scored 3)
  • Game variance −0.60 R/G Total game outcome vs optimal expectation

Murakami 0-for-3 batting 3rd

COUNTERFACTUAL

Optimal lineups projected 2.3 – 3.6 — actual was 0 – 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.