Match prediction·USA: MLS·Saturday 25 Jul, 23:30 UTC

Philadelphia Union vs Seattle Sounders 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 lands at 80% because Philadelphia's 1.65 xG and Seattle's 1.34 create a combined 2.99 expected-goal total that heavily favors multiple tallies.

📊 Win probability
42.0% home29.5% draw28.5% away
📈 xG chain — base → adjustments → final goal estimate
Philadelphia UnionstepSeattle Sounders FC
1.46Base xG · rolling 26-match1.42
× 1.13Home advantage · Home× 0.94
no injury adjustment — full squads available per FotMob
1.65Final goal estimate — what the model uses1.34

Philadelphia Union average 7.2 corners per game at home this season (27 competitive matches). Seattle Sounders average 5.3 corners per game away from home this season (26 competitive matches).

🎯 Scoreline distribution · chance of each scoremodel estimate
0
1
2
3
4
5
6
0
5
7
4
2
1
1
8
11
7
3
1
2
7
9
6
3
1
3
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5
3
2
1
4
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2
1
1
5
1
1
6
home windrawaway win
Most likely outcomes
Over 1.5 goals
80%
Over 3.5 goals
25%

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

More predictions for these teams

Philadelphia Union vs Seattle Sounders — Head-to-Head

This is the first meeting Bawler has on record between Philadelphia Union and Seattle Sounders — 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: Philadelphia Union 42% · draw 30% · Seattle Sounders 28%.

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

⚡ Full-time recap available
Philadelphia Union 10 Seattle Sounders 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.