San Francisco Giants vs St. Louis Cardinals — Prediction & Odds

September 15, 2026 · Blade Tidwell vs Andre Pallante · 92°F

6.0% edge · San Francisco Giants

San Francisco Giants win

44.6%

St. Louis Cardinals win

55.4%

Fair line (home)

-124

Proj. total

9.14

Score distribution

How often each team scores each run total across all simulations.

San Francisco Giants (mean 4.40)St. Louis Cardinals (mean 4.73)

Totals

O/U line

Proj. total

9.14

Over

51.2%

Under

40.9%

Model vs. market

Side	Model	Book	Fair
San Francisco Giants	44.6%	+154	+124
St. Louis Cardinals	55.4%	-168	-124

Projected starters

Starter	IP	K	H	BB	R
Blade Tidwell RHP · San Francisco Giants	2.9	2.0	3.3	1.3	1.5
Andre Pallante RHP · St. Louis Cardinals	5.1	3.6	5.9	1.7	2.4

Strikeout ladder

Blade Tidwell4+ 14%6+ 1%8+ 0%

Andre Pallante4+ 49%6+ 15%8+ 2%

Per-game averages across all simulations. IP is a decimal average of outs recorded, not baseball's 5.2 notation. R is runs allowed while the starter was still in the game; the simulation models no errors, so every run is earned by construction — which is why this says R and not ER.

San Francisco Giants — projected lines

Batter	PA	1B	2B	3B	HR	BB	K	AVG	OBP	SLG	OPS
Drew Gilbert	4.9	.791	.213	.035	.104	.442	.740	.263	.340	.400	.739
Bryce Eldridge	4.8	.767	.222	.005	.153	.511	1.147	.273	.356	.437	.793
Jonah Cox	4.6	.932	.160	.094	.070	.264	.961	.289	.334	.418	.752
Jung Hoo Lee	4.5	.899	.226	.050	.063	.303	.386	.296	.350	.420	.770
Osleivis Basabe	4.4	.802	.211	.013	.074	.258	.608	.267	.316	.378	.695
Turner Hill	4.3	.827	.201	.046	.043	.374	.480	.287	.356	.395	.751
Drew Cavanaugh	4.2	.686	.177	.009	.074	.402	1.040	.252	.333	.362	.695
Grant McCray	4.1	.612	.164	.038	.079	.360	1.035	.240	.312	.368	.681
Christian Koss	4.0	.721	.180	.013	.072	.202	.747	.264	.309	.377	.686

St. Louis Cardinals — projected lines

Batter	PA	1B	2B	3B	HR	BB	K	AVG	OBP	SLG	OPS
Bryan Torres	4.7	.927	.174	.032	.057	.562	.722	.288	.378	.387	.765
Iván Herrera	4.6	.785	.186	.009	.133	.566	.697	.284	.391	.437	.828
Alec Burleson	4.5	.822	.204	.012	.161	.411	.580	.296	.366	.471	.838
Jordan Walker	4.4	.719	.214	.008	.170	.374	.949	.279	.347	.466	.813
Leo Bernal	4.3	.725	.174	.014	.117	.357	.756	.265	.332	.407	.740
Thomas Saggese	4.2	.749	.188	.016	.099	.298	.865	.274	.333	.409	.742
Nathan Church	4.1	.760	.153	.023	.088	.282	.550	.273	.331	.397	.728
Masyn Winn	4.0	.689	.182	.015	.073	.346	.630	.269	.342	.391	.732
José Fermín	3.8	.631	.179	.005	.077	.413	.415	.264	.353	.389	.743

Data notes: game-time temp 92F: run environment adjusted · 20/20 lineup+starter talents from projections