San Francisco Giants at Tampa Bay Rays: Final Score & Recap
Line Score
| Team | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | R | H | E |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SF | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 7 | 1 |
| TB | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 1 | - | 5 | 9 | 0 |
The Story
The Tampa Bay Rays handed the San Francisco Giants a 5-1 defeat at Tropicana Field on May 2, 2026, a result the DiamondIQ model's estimate anticipated from the outset, assigning the Rays a 75 percent pre-game home win probability that climbed to 100 percent by the final out. The Giants managed seven hits and committed one error against a Tampa Bay club that posted nine hits and played clean defense. San Francisco's lone run came in the sixth inning, but by then the outcome had long been shaped by events in the fourth and fifth frames.
The pivotal sequence came against Giants starter Landen Roupp, whose grip on the game slipped through consecutive innings. Jake Fraley opened the damage with a single in the bottom of the fourth that shifted win probability 7.7 percent toward Tampa Bay. The fifth inning proved decisive, as Jonathan Aranda added a single worth 8.2 percent in win-probability swing, and Cedric Mullins drew a walk that moved the needle another 7.6 percent, all off Roupp. The Rays plated three runs in that fifth inning to push their lead to four. Roupp was also at the center of the two most negative plays for Tampa Bay, including Richie Palacios striking out in the second, which cost the Rays 7.0 percent in win probability, and Aranda being caught stealing second in the first, a 6.8 percent swing against the home side.
On the pitching side, Jesse Scholtens was the model's top-valued arm on the night, generating 12.1 percent in win-probability added, followed by Kevin Kelly at 5.9 percent and Garrett Cleavinger at 4.5 percent, reflecting a collective bullpen performance that shut the Giants down across the late innings. Among Tampa Bay batters, Fraley finished with a WPA of plus-6.5 percent and an RE24 of plus-0.6, while Mullins posted the strongest run-expectancy figure of the group at plus-1.1 alongside a 5.2 percent WPA. Heliot Ramos contributed 5.6 percent in win-probability added despite a slightly negative RE24 of minus-0.1. The DiamondIQ model leaned toward Tampa Bay before the first pitch, and the Rays delivered a methodical, low-error victory that matched that assessment throughout.