San Francisco Giants @ Texas Rangers
SFGAwaySan Francisco Giants43%
@TRHomeTexas Rangers57%
Model PickTexas Rangers 57%Market edge — disclosed after closing odds are collectedEvidence 12 structured
The model favors Texas Rangers at 57% — a moderate favorite. The main drivers are Home Advantage, Home/Away Split, offset by Last 10 Games Form.
Logistic-regression statistical model — predicts San Francisco Giants vs Texas Rangers 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 57% home win was derived
Home Advantage+2.5
Pythagorean Expectation+0.4
Season Win%+1.2
Last 10 Games Form-1.2
Home/Away Split+2.1
Team OBP+1.3
Team SLG-1
Team ERA+0.3
Team WHIP+1.7
Baseline 50% → final home win57.3%
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 | Texas Rangers at home — MLB historical home win rate ~.535 (ballpark familiarity, no travel) | MLB StatsAPI |
| Pythagorean Expectation | Home 46.4% (471 RS/510 RA) vs Away 45.5% (479/529) — strength from runs scored/allowed | MLB StatsAPI |
| Season Win% | Home 56-58 (.491) vs Away 48-66 (.421) | MLB StatsAPI |
| Last 10 Games Form | Home 3-7 vs Away 4-6 · Home W1 | MLB StatsAPI |
| Home/Away Split | Home team home 29-26 · away team away 22-39 | MLB StatsAPI |
| Team OBP | Home .318 vs Away .309 — foundation of scoring | MLB StatsAPI |
| Team SLG | Home .401 vs Away .414 (OPS .719/.723) | MLB StatsAPI |
| Team ERA | Home 4.33 vs Away 4.37 — lower is better | MLB StatsAPI |
| Team WHIP | Home 1.29 vs Away 1.36 — baserunners allowed per inning (lower is better) | MLB StatsAPI |
| Starting Pitcher Matchup | Home Cody Bradford (ERA ?) vs Away Carson Whisenhunt (ERA 6.63) | MLB StatsAPI |
| Hitting Detail (BABIP, K, BB) | Home BABIP .294 · K 970 · BB 365 / Away BABIP .293 · K 891 · BB 300 (BABIP is luck-driven → not factored into probability) | MLB StatsAPI |
| Pitching Detail (K/BB, HR9) | Home K/BB 2.87 · HR9 1.27 / Away K/BB 2.06 · 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)
- San Francisco Giants at Texas Rangers Game Story, Scores/Highlights - 08/03/2026
- How to watch San Francisco Giants vs. Texas Rangers
- Giants vs. Rangers (Aug 5, 2026) Pregame
- How to watch Giants vs. Rangers: TV channel and streaming options for August 3
- Rangers Set Lineup as Texas Faces Giants Pitching Prospect Blade Tidwell
- San Francisco Giants vs Texas Rangers Live Stream: How to Watch MLB
- Where to watch San Francisco Giants vs Texas Rangers: TV channel, start time, streaming for Aug. 4
- Texas Rangers host the San Francisco Giants to begin a 3-game series
Frequently asked questions This game's prediction summary
San Francisco Giants vs Texas Rangers — who's more likely to win?
SealedSlate's logistic-regression statistical model gives Texas Rangers a 57% chance to win (Home 57% · Away 43%). MLB · 2026-08-06 03:35 KST.
How was the 57.3% 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 57.3%. 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.