San Francisco Giants @ Kansas City Royals
SFGAwaySan Francisco Giants55%
@KCRHomeKansas City Royals45%
Model PickSan Francisco Giants 55%Market edge — disclosed after closing odds are collectedEvidence 12 structured · 3 qualitative
The model favors San Francisco Giants at 55% — a slight edge. The main drivers are Team ERA, Team WHIP, offset by Home Advantage.
Logistic-regression statistical model — predicts San Francisco Giants vs Kansas City Royals 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 45% home win was derived
Home Advantage+2.5
Pythagorean Expectation-1.2
Season Win%-0.2
Home/Away Split+1.2
Team OBP+1.2
Team SLG-1.4
Team ERA-5
Team WHIP-2.5
Starting Pitcher Matchup+0.9
Baseline 50% → final home win45.4%
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 | Kansas City Royals at home — MLB historical home win rate ~.535 (ballpark familiarity, no travel) | MLB StatsAPI |
| Pythagorean Expectation | Home 40.7% (430 RS/528 RA) vs Away 43.6% (411/473) — strength from runs scored/allowed | MLB StatsAPI |
| Season Win% | Home 41-60 (.406) vs Away 42-58 (.420) | MLB StatsAPI |
| Last 10 Games Form | Home 4-6 vs Away 4-6 · Home W1 | MLB StatsAPI |
| Home/Away Split | Home team home 24-27 · away team away 20-33 | MLB StatsAPI |
| Team OBP | Home .316 vs Away .308 — foundation of scoring | MLB StatsAPI |
| Team SLG | Home .399 vs Away .418 (OPS .715/.726) | MLB StatsAPI |
| Team ERA | Home 4.97 vs Away 4.40 — lower is better | MLB StatsAPI |
| Team WHIP | Home 1.45 vs Away 1.35 — baserunners allowed per inning (lower is better) | MLB StatsAPI |
| Starting Pitcher Matchup | Home Luinder Avila (ERA 5.08) vs Away Tyler Mahle (ERA 5.31) | MLB StatsAPI |
| Hitting Detail (BABIP, K, BB) | Home BABIP .294 · K 813 · BB 321 / Away BABIP .297 · K 788 · BB 249 (BABIP is luck-driven → not factored into probability) | MLB StatsAPI |
| Pitching Detail (K/BB, HR9) | Home K/BB 1.98 · HR9 1.40 / Away K/BB 2.03 · HR9 1.04 | MLB StatsAPI |
Qualitative & folklore factors 3 factors · fully disclosed
Qualitative · Royals' Walk-Off Win
The Royals secured a dramatic 4-3 walk-off victory in the previous game with a ninth-inning squeeze bunt, which could significantly boost team morale.
Basis: LLM · news · Loftin's squeeze bunt in the ninth gives the Royal
Qualitative · Giants' Roster Move
The Giants made a roster move involving a former Royals player during the All-Star break, which could impact team dynamics and strategy.
Basis: LLM · news · San Francisco Giants Make Roster Move on Former Ro
Qualitative · Giants' Injury Report
The Giants have an injury report ahead of the game, which is a critical factor that could affect their lineup and on-field performance.
Basis: LLM · news · Giants-Royals Series Preview: How to Watch, Starti
12 source headlines (auto-collected · basis disclosed)
- How to watch San Francisco Giants vs. Kansas City Royals
- San Francisco Giants at Kansas City Royals Game Story, Scores/Highlights - 07/20/2026
- Giants vs. Royals (Jul 20, 2026) Pregame
- How to watch Giants vs. Royals: TV channel and streaming options for July 20
- Loftin's squeeze bunt in the ninth gives the Royals a 4-3 victory over the Giants
- Royals vs Giants July 20 Live Discussion
- Late-game heroics help Royals take down Giants
- Where to watch San Francisco Giants vs Kansas City Royals: TV channel, start time, streaming for July 20
Frequently asked questions This game's prediction summary
San Francisco Giants vs Kansas City Royals — who's more likely to win?
SealedSlate's logistic-regression statistical model gives San Francisco Giants a 55% chance to win (Home 45% · Away 55%). MLB · 2026-07-22 08:40 KST.
How was the 45.4% 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 45.4%. 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.