ARCHIVE April 4, 2026
April 4, 2026 · AL Cent

Toronto Blue Jays vs Chicago White Sox

April 4, 2026Rate FieldCloudy 50°F · 16 mph, Out To LF
AWAY
Toronto Blue Jays
4-4
3
vs
HOME
Chicago White Sox
3-5
6

Starting pitchers

AWAY · TOR
Lazaro Estrada
Lazaro Estrada
IP 4
HOME · CWS
Anthony Kay
Anthony Kay
IP 4.1

Lineups

AWAY · TOR
  1. 1 George Springer DH
  2. 2 Davis Schneider LF
  3. 3 Vladimir Guerrero 1B
  4. 4 Kazuma Okamoto 3B
  5. 5 Daulton Varsho CF
  6. 6 Ernie Clement 2B
  7. 7 Myles Straw RF
  8. 8 Andrés Giménez SS
  9. 9 Tyler Heineman C
HOME · CWS
  1. 1 Chase Meidroth 2B
  2. 2 Lenyn Sosa DH
  3. 3 Miguel Vargas 3B
  4. 4 Munetaka Murakami 1B
  5. 5 Austin Hays LF
  6. 6 Colson Montgomery SS
  7. 7 Luisangel Acuña CF
  8. 8 Reese McGuire C
  9. 9 Tristan Peters RF

Box score

  123456789 R
TOR 000002100 3
CWS 100003020 6

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
LLLWLWWWWW

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 −0.01 R/G Optimal arrangement projects 4.67 vs actual lineup 4.68
  • Player execution −1.68 R/G Players fell 1.68 short of the lineup's 4.68 projection (scored 3)
  • Game variance −1.67 R/G Total game outcome vs optimal expectation

Springer 0-for-4 batting 1st

HOME · Chicago White Sox
  • Manager lineup cost +0.12 R/G Optimal arrangement projects 4.35 vs actual lineup 4.24
  • Player execution +1.76 R/G Players exceeded the lineup's 4.24 projection by 1.76 (scored 6)
  • Game variance +1.65 R/G Total game outcome vs optimal expectation

Meidroth 0-for-4 batting 1st

COUNTERFACTUAL

Optimal lineups projected 4.7 – 4.3 — actual was 3 – 6.

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.