ARCHIVE May 1, 2026
May 1, 2026 · AL East

San Francisco Giants vs Tampa Bay Rays

May 1, 2026Tropicana FieldDome 72°F · 0 mph, None
AWAY
San Francisco Giants
13-19
0
vs
HOME
Tampa Bay Rays
19-12
3

Starting pitchers

AWAY · SF
Robbie Ray
Robbie Ray
IP 6.1
HOME · TB
Shane McClanahan
Shane McClanahan
IP 6

Lineups

AWAY · SF
  1. 1 Heliot Ramos LF
  2. 2 Matt Chapman 3B
  3. 3 Luis Arraez 2B
  4. 4 Casey Schmitt DH
  5. 5 Rafael Devers 1B
  6. 6 Willy Adames SS
  7. 7 Jung Hoo Lee CF
  8. 8 Jerar Encarnacion RF
  9. 9 Patrick Bailey C
HOME · TB
  1. 1 Chandler Simpson LF
  2. 2 Junior Caminero 3B
  3. 3 Ryan Vilade 1B
  4. 4 Yandy Díaz DH
  5. 5 Ben Williamson 2B
  6. 6 Jonny DeLuca CF
  7. 7 Jake Fraley RF
  8. 8 Nick Fortes C
  9. 9 Taylor Walls SS

Box score

  123456789 R
SF 000000000 0
TB 010101000 3

Manager comparison

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

AWAY · SF
Tony Vitello
B- Lineup 0.8 R Bunts 0.7 R IBBs 1.4 R
HOME · TB
Kevin Cash
B- Lineup 0.9 R Bunts 2.4 R IBBs 2.1 R

Recent form

AWAY · SF
1-8 L2 -25 run diff
LLWLLLLL?L
HOME · TB
8-2 L1 +17 run diff
LWWWWWWWLW

Season series: 0-3 with SF listed first across 3 prior meetings.

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 · San Francisco Giants
  • Manager lineup cost +0.02 R/G Optimal arrangement projects 3.55 vs actual lineup 3.52
  • Player execution −3.52 R/G Players fell 3.52 short of the lineup's 3.52 projection (scored 0)
  • Game variance −3.55 R/G Total game outcome vs optimal expectation

Ramos 0-for-4 batting 1st

HOME · Tampa Bay Rays
  • Manager lineup cost +0.10 R/G Optimal arrangement projects 3.14 vs actual lineup 3.05
  • Player execution −0.05 R/G Players fell 0.05 short of the lineup's 3.05 projection (scored 3)
  • Game variance −0.14 R/G Total game outcome vs optimal expectation

Vilade 0-for-3 batting 3rd

COUNTERFACTUAL

Optimal lineups projected 3.5 – 3.1 — 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.