Match prediction·USA: MLS·Friday 31 Jul, 23:30 UTC

New York City FC vs Toronto FC

Bawler weighs each team's recent scoring and defending, then adjusts for home advantage and injuries to work out how this match is likely to go. This page shows the full chain — every number we used.

Why the model calls it this way

Over 1.5 Goals at 69% probability is the lock here—New York City's 0.41 xG advantage and Martínez leading their attack sets up a low-scoring but inevitable breakthrough.

📊 Win probability
43.4% home31.5% draw25.1% away
📈 xG chain — base → adjustments → final goal estimate
New York City FCstepToronto FC
1.35Base xG · rolling 26-match1.19
× 1.13Home advantage · Home× 0.94
no injury adjustment — full squads available per FotMob
1.52Final goal estimate — what the model uses1.11

New York City average 5.6 corners per game at home this season (25 competitive matches). Toronto average 4.2 corners per game away from home this season (22 competitive matches).

🎯 Scoreline distribution · chance of each scoremodel estimate
0
1
2
3
4
5
6
0
7
8
4
2
1
11
12
7
3
1
2
8
9
5
2
1
3
4
5
3
1
4
2
2
1
5
1
6
home windrawaway win
Most likely outcomes
Over 1.5 goals
69%
Not both teams to score
50%
Draw
19%

Model probabilities for this fixture, ordered by likelihood. Estimates from rolling expected goals — not guarantees.

More predictions for these teams

New York City vs Toronto — Head-to-Head

This is the first meeting Bawler has on record between New York City and Toronto — the model's ledger starts at model launch, so no earlier fixtures between these two sides have been logged and settled yet.

The model's verdict for this fixture: New York City 43% · draw 31% · Toronto 25%.

Model probabilities are edge estimates for entertainment — not betting advice, and past performance does not guarantee future results. 18+.

⚡ Full-time recap available
New York City FC 11 Toronto FC
See how the model called it · call-by-call verdict · xG vs actual →
More match predictions ▶

Model estimates from rolling expected goals — not guaranteed outcomes. Past accuracy does not guarantee future results.