Toronto FC @ New York City FC
TFAwayToronto FC23%
@NYCFHomeNew York City FC51%
Model PickNew York City FC 51%Market edge — disclosed after closing odds are collectedEvidence 12 structured · 1 qualitative
AI Summary grounded in real data · zero hallucination
Our model projects New York City FC with a 51% win probability against Toronto FC, showing an advantage across several metrics. Notably, they hold a significant 9.8 percentage point edge in 'Season Form (record)' and benefit from 'Home Advantage'. The market edge for this pick is currently uncalculated.
Logistic-regression statistical model — predicts Toronto FC vs New York City FC 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 51% home win was derived
Home Advantage+3.7
Season Form (record)+9.8
Attack (goals/game)+2.4
Defense (goals against/game)+2.6
Shots on Target %+1
Baseline 50% → final home win69.4%
※ This is the head-to-head home-win probability (home vs away). After carving out the 26% draw share, the 3-way home probability shown above is 51%.
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 | New York City FC at home — MLS home-field edge applied | ESPN MLS |
| Season Form (record) | Home New York City FC 7-4-6 vs Away Toronto FC 3-7-7 | ESPN MLS |
| Home/Away Split | Home team's home record ? · away team's away record ? | ESPN MLS |
| Recent Form | Home WWLLD vs Away LDDLL (recent results) | ESPN MLS |
| Attack (goals/game) | Home 1.76 vs Away 1.35 — goals per game | ESPN MLS |
| Defense (goals against/game) | Home 1.35 vs Away 1.82 — goals conceded per game (lower is better) | ESPN MLS |
| Shots on Target % | Home 43.92% vs Away 36.5% — share of total shots on target (shot quality) | ESPN MLS |
| Finishing (conversion rate) | Home 16.5% vs Away 13% — shot-to-goal conversion (finishing efficiency) | ESPN MLS |
| Possession % | Home 55.26% vs Away 47.64% — ball control (game-control style) | ESPN MLS |
| Pass Accuracy % | Home 85.75% vs Away 81.25% — build-up stability | ESPN MLS |
| Tackle Success % | Home 67.75% vs Away 70.23% — pressing-defense efficiency | ESPN MLS |
| xG (Expected Goals) | Not available on ESPN's free tier — will be added when a paid xG source is connected. Currently proxied by shots on target and conversion rate | ESPN MLS |
Qualitative & folklore factors 1 factors · fully disclosed
Qualitative · GK Contract Extension
NYCFC's starting goalkeeper, Greg Ranjitsingh, has extended his contract through the 2027-28 season. This could positively impact team morale and stability.
Basis: LLM · news · NYCFC G Greg Ranjitsingh extended through 2027-28
12 source headlines (auto-collected · basis disclosed)
- Keys to the Match | Number Nine
- Highlights: Columbus Crew 1-2 New York City FC (MLS)
- MLS Predictions: Every Team Back in Action Post-World Cup for Matchday 17
- New York City FC vs Chicago Fire FC: Where to watch, live stream, TV channel & kick-off time | Goal.com US
- New Ballgame: Chicago Fire at New York City FC Preview
- Revolution II Preview: 7/23 vs New York City FC II
- New York City FC vs Toronto FC Odds - Friday July 31 2026
- MLS Player Status Report: Matchday 17 (Wednesday, July 22)
Frequently asked questions This game's prediction summary
Toronto FC vs New York City FC — who's more likely to win?
SealedSlate's logistic-regression statistical model gives New York City FC a 51% chance to win (Home 51% · Draw 26% · Away 23%). MLS · 2026-08-01 08:30 KST.
How was the 69.4% 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 69.4%. 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.