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

Tampa Bay Rays vs Milwaukee Brewers

March 31, 2026American Family FieldRoof Closed 65°F · 0 mph, None
AWAY
Tampa Bay Rays
2-3
2
vs
HOME
Milwaukee Brewers
4-1
6

Starting pitchers

AWAY · TB
Shane McClanahan
Shane McClanahan
IP 4.2
HOME · MIL
Brandon Woodruff
Brandon Woodruff
IP 5

Lineups

AWAY · TB
  1. 1 Yandy Díaz DH
  2. 2 Jonathan Aranda 1B
  3. 3 Junior Caminero 3B
  4. 4 Jake Fraley RF
  5. 5 Ben Williamson 2B
  6. 6 Cedric Mullins CF
  7. 7 Nick Fortes C
  8. 8 Chandler Simpson LF
  9. 9 Carson Williams SS
HOME · MIL
  1. 1 Brice Turang 2B
  2. 2 Luis Rengifo 3B
  3. 3 William Contreras C
  4. 4 Christian Yelich LF
  5. 5 Gary Sánchez DH
  6. 6 Jake Bauers 1B
  7. 7 Brandon Lockridge CF
  8. 8 Sal Frelick RF
  9. 9 Joey Ortiz SS

Box score

  123456789 R
TB 100010000 2
MIL 000032010 6

Manager comparison

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

AWAY · TB
Kevin Cash
B- Lineup 0.9 R Bunts 2.4 R IBBs 2.1 R
HOME · MIL
Pat Murphy
B- Lineup 0.6 R Bunts 1.4 R IBBs 3.1 R

Recent form

AWAY · TB
8-2 L1 +17 run diff
LWWWWWWWLW
HOME · MIL
6-3 W2 +33 run diff
WW?LLWWWLW

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 · Tampa Bay Rays
  • Manager lineup cost −0.04 R/G Optimal arrangement projects 3.76 vs actual lineup 3.80
  • Player execution −1.80 R/G Players fell 1.80 short of the lineup's 3.80 projection (scored 2)
  • Game variance −1.76 R/G Total game outcome vs optimal expectation

Fortes HR from the 7-hole

HOME · Milwaukee Brewers
  • Manager lineup cost −0.13 R/G Optimal arrangement projects 3.68 vs actual lineup 3.82
  • Player execution +2.18 R/G Players exceeded the lineup's 3.82 projection by 2.18 (scored 6)
  • Game variance +2.32 R/G Total game outcome vs optimal expectation

Rengifo 0-for-4 batting 2nd

COUNTERFACTUAL

Optimal lineups projected 3.8 – 3.7 — actual was 2 – 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.