Los Angeles Angels @ San Francisco Giants
LAAAwayLos Angeles Angels33%
@SFGHomeSan Francisco Giants67%
Model PickSan Francisco Giants 67%Market edge — disclosed after closing odds are collectedEvidence 12 structured · 3 qualitative
AI Summary grounded in real data · zero hallucination
Our model projects a 67% win probability for the San Francisco Giants, primarily driven by the Starting Pitcher Matchup (deltaPct 9.8) and Home Advantage (deltaPct 2.5). A key swing risk is the Angels' edge in Team OBP (deltaPct -1.2). The market edge for this pick is currently uncalculated.
Logistic-regression statistical model — predicts Los Angeles Angels 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 67% home win was derived
Home Advantage+2.5
Pythagorean Expectation-0.3
Season Win%+0.4
Home/Away Split+1.9
Team OBP-1.2
Team SLG+2.1
Team ERA+1.1
Team WHIP+0.5
Starting Pitcher Matchup+9.8
Baseline 50% → final home win66.8%
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 43.7% (424 RS/487 RA) vs Away 44.4% (448/507) — strength from runs scored/allowed | MLB StatsAPI |
| Season Win% | Home 43-60 (.417) vs Away 41-63 (.394) | MLB StatsAPI |
| Last 10 Games Form | Home 4-6 vs Away 4-6 · Home W1 | MLB StatsAPI |
| Home/Away Split | Home team home 23-25 · away team away 17-35 | MLB StatsAPI |
| Team OBP | Home .307 vs Away .315 — foundation of scoring | MLB StatsAPI |
| Team SLG | Home .416 vs Away .388 (OPS .723/.703) | MLB StatsAPI |
| Team ERA | Home 4.41 vs Away 4.54 — lower is better | MLB StatsAPI |
| Team WHIP | Home 1.35 vs Away 1.37 — baserunners allowed per inning (lower is better) | MLB StatsAPI |
| Starting Pitcher Matchup | Home Robbie Ray (ERA 3.33) vs Away Ryan Johnson (ERA 6.10) | MLB StatsAPI |
| Hitting Detail (BABIP, K, BB) | Home BABIP .295 · K 812 · BB 259 / Away BABIP .300 · K 987 · BB 335 (BABIP is luck-driven → not factored into probability) | MLB StatsAPI |
| Pitching Detail (K/BB, HR9) | Home K/BB 2.06 · HR9 1.04 / Away K/BB 2.09 · HR9 1.10 | MLB StatsAPI |
Qualitative & folklore factors 3 factors · fully disclosed
Qualitative · Giants Snap Skid
The San Francisco Giants snapped their losing streak yesterday with a walk-off hit by Rafael Devers in the 10th inning against the Angels. This win could significantly boost team morale and carry positive momentum into the next game.
Basis: LLM · news · SF Giants’ Devers delivers walk-off in 10th inning
Qualitative · Angels Walk-Off Loss
The Los Angeles Angels suffered a tough walk-off loss in the 10th inning yesterday. This kind of defeat can negatively impact team morale and potentially lead to a lack of focus in the subsequent game.
Basis: LLM · news · SF Giants’ Devers delivers walk-off in 10th inning
Qualitative · Giants Pitcher Signing
The San Francisco Giants signed a pitcher for $3.2 million just before the Angels series. This move could be aimed at bolstering their bullpen or reinforcing the starting rotation, potentially impacting their pitching strength.
Basis: LLM · news · San Francisco Giants Sign Pitcher For $3.2 Million
12 source headlines (auto-collected · basis disclosed)
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Frequently asked questions This game's prediction summary
Los Angeles Angels vs San Francisco Giants — who's more likely to win?
SealedSlate's logistic-regression statistical model gives San Francisco Giants a 67% chance to win (Home 67% · Away 33%). MLB · 2026-07-26 05:05 KST.
How was the 66.8% 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 66.8%. 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.