Milwaukee Brewers @ San Francisco Giants
MBAwayMilwaukee Brewers79%
@SFGHomeSan Francisco Giants21%
Model PickMilwaukee Brewers 79%Market edge — disclosed after closing odds are collectedEvidence 12 structured
The model favors Milwaukee Brewers at 79% — a clear favorite. The main drivers are Pythagorean Expectation, Team ERA, offset by Home Advantage.
Logistic-regression statistical model — predicts Milwaukee Brewers 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 21% home win was derived
Home Advantage+2.5
Pythagorean Expectation-7.8
Season Win%-3.5
Last 10 Games Form-4.7
Home/Away Split-1.5
Team OBP-3.8
Team SLG+0.9
Team ERA-6.9
Team WHIP-3.4
Starting Pitcher Matchup-1.2
Baseline 50% → final home win20.5%
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 44.2% (441 RS/501 RA) vs Away 63.8% (543/398) — strength from runs scored/allowed | MLB StatsAPI |
| Season Win% | Home 45-62 (.421) vs Away 67-40 (.626) | MLB StatsAPI |
| Last 10 Games Form | Home 3-7 vs Away 7-3 · Home L1 | MLB StatsAPI |
| Home/Away Split | Home team home 25-27 · away team away 31-20 | MLB StatsAPI |
| Team OBP | Home .308 vs Away .337 — foundation of scoring | MLB StatsAPI |
| Team SLG | Home .415 vs Away .401 (OPS .723/.738) | MLB StatsAPI |
| Team ERA | Home 4.38 vs Away 3.41 — lower is better | MLB StatsAPI |
| Team WHIP | Home 1.35 vs Away 1.16 — baserunners allowed per inning (lower is better) | MLB StatsAPI |
| Starting Pitcher Matchup | Home Logan Webb (ERA 3.98) vs Away Shane Drohan (ERA 3.51) | MLB StatsAPI |
| Hitting Detail (BABIP, K, BB) | Home BABIP .294 · K 845 · BB 273 / Away BABIP .308 · K 869 · BB 439 (BABIP is luck-driven → not factored into probability) | MLB StatsAPI |
| Pitching Detail (K/BB, HR9) | Home K/BB 2.04 · HR9 1.02 / Away K/BB 3.11 · 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)
- Milwaukee Brewers at San Francisco Giants Game Story, Scores/Highlights - 07/28/2026
- How to watch San Francisco Giants vs. Milwaukee Brewers
- Brewers blanked by Giants, 3-0
- Giants 3, Brewers 0: Not a great way to open a West Coast trip
- How to watch San Francisco Giants vs. Milwaukee Brewers
- Milwaukee Brewers vs. San Francisco Giants: Game Highlights
- What we learned as Tyler Mahle is magical on mound in Giants' win vs. Brewers
- Milwaukee Brewers at San Francisco Giants Game Story, Scores/Highlights - 07/27/2026
Frequently asked questions This game's prediction summary
Milwaukee Brewers vs San Francisco Giants — who's more likely to win?
SealedSlate's logistic-regression statistical model gives Milwaukee Brewers a 79% chance to win (Home 21% · Away 79%). MLB · 2026-07-30 04:45 KST.
How was the 20.5% 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 20.5%. 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.