ARCHIVE March 28, 2026
March 28, 2026 · NL Cent

Chicago White Sox vs Milwaukee Brewers

March 28, 2026American Family FieldRoof Closed 63°F · 0 mph, None
AWAY
Chicago White Sox
0-2
1
vs
HOME
Milwaukee Brewers
2-0
6

Starting pitchers

AWAY · CWS
Sean Burke
Sean Burke
IP 4
HOME · MIL
Chad Patrick
Chad Patrick
IP 4.1

Lineups

AWAY · CWS
  1. 1 Chase Meidroth 2B
  2. 2 Colson Montgomery 3B
  3. 3 Andrew Benintendi LF
  4. 4 Munetaka Murakami 1B
  5. 5 Lenyn Sosa DH
  6. 6 Tristan Peters CF
  7. 7 Everson Pereira RF
  8. 8 Reese McGuire C
  9. 9 Luisangel Acuña SS
HOME · MIL
  1. 1 Brice Turang 2B
  2. 2 William Contreras C
  3. 3 Christian Yelich DH
  4. 4 Jake Bauers 1B
  5. 5 Garrett Mitchell CF
  6. 6 Sal Frelick RF
  7. 7 Joey Ortiz SS
  8. 8 David Hamilton 3B
  9. 9 Brandon Lockridge LF

Box score

  123456789 R
CWS 000100000 1
MIL 310001100 6

Manager comparison

Both managers grade D- / B- entering this matchup.

AWAY · CWS
Will Venable
D- Lineup 3.2 R Bunts 2.2 R IBBs 1.1 R
HOME · MIL
Pat Murphy
B- Lineup 0.6 R Bunts 1.4 R IBBs 3.1 R

Recent form

AWAY · CWS
6-4 L3 +9 run diff
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HOME · MIL
6-3 W2 +33 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 White Sox
  • Manager lineup cost +0.12 R/G Optimal arrangement projects 3.57 vs actual lineup 3.45
  • Player execution −2.45 R/G Players fell 2.45 short of the lineup's 3.45 projection (scored 1)
  • Game variance −2.57 R/G Total game outcome vs optimal expectation

Lineup spots out of order vs season production

HOME · Milwaukee Brewers
  • Manager lineup cost −0.10 R/G Optimal arrangement projects 3.40 vs actual lineup 3.51
  • Player execution +2.49 R/G Players exceeded the lineup's 3.51 projection by 2.49 (scored 6)
  • Game variance +2.60 R/G Total game outcome vs optimal expectation

Contreras 0-for-4 batting 2nd

COUNTERFACTUAL

Optimal lineups projected 3.6 – 3.4 — actual was 1 – 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.