Toronto Blue Jays @ Chicago Cubs
TBJAwayToronto Blue Jays39%
@CCHomeChicago Cubs61%
Model PickChicago Cubs 61%Market edge — disclosed after closing odds are collectedEvidence 12 structured
The model favors Chicago Cubs at 61% — a moderate favorite. The main drivers are Pythagorean Expectation, Team OBP, offset by Starting Pitcher Matchup.
Logistic-regression statistical model — predicts Toronto Blue Jays vs Chicago Cubs 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 61% home win was derived
Home Advantage+2.5
Pythagorean Expectation+5.5
Season Win%+1.8
Last 10 Games Form+1.2
Home/Away Split+1.4
Team OBP+5
Team SLG+2.6
Team ERA-0.1
Team WHIP+1.5
Starting Pitcher Matchup-10.4
Baseline 50% → final home win61%
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 | Chicago Cubs at home — MLB historical home win rate ~.535 (ballpark familiarity, no travel) | MLB StatsAPI |
| Pythagorean Expectation | Home 58.3% (592 RS/493 RA) vs Away 44.3% (449/509) — strength from runs scored/allowed | MLB StatsAPI |
| Season Win% | Home 66-49 (.574) vs Away 54-61 (.470) | MLB StatsAPI |
| Last 10 Games Form | Home 7-3 vs Away 6-4 · Home W3 | MLB StatsAPI |
| Home/Away Split | Home team home 34-24 · away team away 26-30 | MLB StatsAPI |
| Team OBP | Home .339 vs Away .302 — foundation of scoring | MLB StatsAPI |
| Team SLG | Home .417 vs Away .377 (OPS .756/.679) | MLB StatsAPI |
| Team ERA | Home 4.08 vs Away 4.06 — lower is better | MLB StatsAPI |
| Team WHIP | Home 1.25 vs Away 1.32 — baserunners allowed per inning (lower is better) | MLB StatsAPI |
| Starting Pitcher Matchup | Home David Peterson (ERA 5.52) vs Away Dylan Cease (ERA 2.41) | MLB StatsAPI |
| Hitting Detail (BABIP, K, BB) | Home BABIP .295 · K 987 · BB 494 / Away BABIP .278 · K 831 · BB 308 (BABIP is luck-driven → not factored into probability) | MLB StatsAPI |
| Pitching Detail (K/BB, HR9) | Home K/BB 2.63 · HR9 1.51 / Away K/BB 2.47 · HR9 1.06 | 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)
- MLB trade deadline: Chicago Cubs acquire RHP Kevin Gausman from the Toronto Blue Jays for 2 minor-leaguers
- Toronto Blue Jays Trade Fan Favorite Kevin Gausman to Chicago Cubs
- Chicago Cubs acquire right-hander Kevin Gausman in a trade with the Toronto Blue Jays
- Cubs trade for Blue Jays right-hander Gausman
- BREAKING: Chicago Cubs Acquire Kevin Gausman in Trade with Toronto Blue Jays
- Cubs acquire pitcher Kevin Gausman from Toronto Blue Jays
- Blue Jays-Cubs Make-Up Game Could Be Most Emotional of Season
- Cubs trade struggling Jameson Taillon to Blue Jays
Frequently asked questions This game's prediction summary
Toronto Blue Jays vs Chicago Cubs — who's more likely to win?
SealedSlate's logistic-regression statistical model gives Chicago Cubs a 61% chance to win (Home 61% · Away 39%). MLB · 2026-08-07 03:20 KST.
How was the 61% 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 61%. 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.