St. Louis Cardinals @ San Francisco Giants
SLCAwaySt. Louis Cardinals51%
@SFGHomeSan Francisco Giants49%
Model PickSt. Louis Cardinals 51%Market edge — disclosed after closing odds are collectedEvidence 12 structured
AI Summary grounded in real data · zero hallucination
We recommend St. Louis Cardinals with a 51% model probability, though the edge against the market is uncalculated. The primary drivers for this pick are 'Team SLG' and 'Starting Pitcher Matchup', while the main swing risk comes from the opponent's advantage in 'Home Advantage'. Please note that our model does not beat the market in the long run, requiring a cautious betting approach.
Logistic-regression statistical model — predicts St. Louis Cardinals vs San Francisco Giants by accumulating the log-odds contributions of 12 proven structured metrics. Only structured metrics enter the probability; qualitative and folklore factors get a label only. Predictions are sealed with SHA-256 before the game.
Model factor contribution How the 49% home win was derived
Home Advantage+2.5
Pythagorean Expectation-1.8
Season Win%-1.5
Home/Away Split-0.4
Team OBP-1.2
Team SLG+1.5
Team ERA-0.6
Team WHIP-0.2
Starting Pitcher Matchup+0.8
Baseline 50% → final home win49%
Each factor's log-odds contribution accumulated · only structured metrics reflected (qualitative/folklore excluded) · each %p converts log-odds to probability, so it's non-linear — a simple sum may not exactly equal (final − baseline)
Structured metric analysis 12 metrics · fully disclosed
| Metric | Analysis (home vs away) | Source |
|---|---|---|
| Home Advantage | San Francisco Giants at home — MLB historical home win rate ~.535 (ballpark familiarity, no travel) | MLB StatsAPI |
| Pythagorean Expectation | Home 44.8% (608 RS/682 RA) vs Away 49.3% (661/671) — strength from runs scored/allowed | MLB StatsAPI |
| Season Win% | Home 60-85 (.414) vs Away 72-73 (.497) | MLB StatsAPI |
| Last 10 Games Form | Home 5-5 vs Away 5-5 · Home W1 | MLB StatsAPI |
| Home/Away Split | Home team home 34-36 · away team away 38-35 | MLB StatsAPI |
| Team OBP | Home .309 vs Away .317 — foundation of scoring | MLB StatsAPI |
| Team SLG | Home .407 vs Away .387 (OPS .716/.704) | MLB StatsAPI |
| Team ERA | Home 4.37 vs Away 4.30 — lower is better | MLB StatsAPI |
| Team WHIP | Home 1.36 vs Away 1.35 — baserunners allowed per inning (lower is better) | MLB StatsAPI |
| Starting Pitcher Matchup | Home Landen Roupp (ERA 4.17) vs Away Quinn Mathews (ERA 4.38) | MLB StatsAPI |
| Hitting Detail (BABIP, K, BB) | Home BABIP .290 · K 1162 · BB 402 / Away BABIP .285 · K 1148 · BB 461 (BABIP is luck-driven → not factored into probability) | MLB StatsAPI |
| Pitching Detail (K/BB, HR9) | Home K/BB 2.03 · HR9 0.98 / Away K/BB 2.30 · HR9 1.00 | MLB StatsAPI |
Qualitative & folklore factors None
This game has no extracted qualitative factors — we don't invent factors without a basis.
12 source headlines (auto-collected · basis disclosed)
- St. Louis Cardinals vs San Francisco Giants Series Preview
- St. Louis Cardinals at San Francisco Giants Game Story, Scores/Highlights - 09/07/2026
- How to watch Cardinals vs. Giants: TV channel and streaming options for September 7
- How to watch the St. Louis Cardinals vs San Francisco Giants: Live stream info, schedule, preview
- St. Louis Cardinals at San Francisco Giants - Where to Watch, Stream Info, TV Channel, and Live Updates (September 07, 2026)
- St. Louis Cardinals vs. San Francisco Giants - Final Score - September 07, 2026
- St. Louis Cardinals vs San Francisco Giants Game Discussion Monday
- How to watch Cardinals vs. Giants: TV channel and streaming options for September 7
Frequently asked questions This game's prediction summary
St. Louis Cardinals vs San Francisco Giants — who's more likely to win?
SealedSlate's logistic-regression statistical model gives St. Louis Cardinals a 51% chance to win (Home 49% · Away 51%). MLB · 2026-09-09 10:45 KST.
How was the 49% home-win probability calculated?
Starting from a 50% baseline, we additively accumulate the log-odds contributions of 12 proven structured statistical metrics to reach the final 49%. Each factor's %p contribution is fully disclosed on the page; qualitative and folklore factors are not reflected in the probability.
Can this prediction be altered later?
No. Every prediction is sealed with a SHA-256 hash before the game starts and permanently recorded in the track record, making after-the-fact changes impossible. SealedSlate runs a transparent ledger that never inflates the hit rate and leaves missed predictions exactly as they were.
We don't compete on hit rate — every factor is fully disclosed and labeled. Only 📊 structured stats feed the probability (each factor's contribution shown in %p); ⚔️🔮 are context to weigh. Predictions are locked and sealed before the game — verify the hits directly on the track record.