Match prediction·Europe: Champions League - Qualification·Tuesday 04 Aug, 18:00 UTC

Union St.-Gilloise vs Bodo/Glimt

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 71% because both sides project efficient finishing with a combined 2.35 xG in a fixture where the win-probability gap (Bodo/Glimt 40% vs Union 26%) suggests attacking intensity from the visitor.

📊 Win probability
26.2% home34.1% draw39.8% away
📈 xG chain — base → adjustments → final goal estimate
Union St.-GilloisestepBodo/Glimt
0.91Base xG · rolling 26-match1.40
× 1.13Home advantage · Home× 0.94
no injury adjustment — full squads available per FotMob
1.03Final goal estimate — what the model uses1.32

Union St.-Gilloise average 4.0 corners per game at home this season (3 competitive matches). Bodo/Glimt average 3.3 corners per game away from home this season (8 competitive matches).

🎯 Scoreline distribution · chance of each scoremodel estimate
0
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10
13
8
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home windrawaway win
Most likely outcomes
Over 1.5 goals
71%
Union St.-Gilloise or draw
55%
Draw
23%

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

More predictions for these teams

Union St.-Gilloise vs Bodo/Glimt — Head-to-Head

This is the first meeting Bawler has on record between Union St.-Gilloise and Bodo/Glimt — 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: Union St.-Gilloise 26% · draw 34% · Bodo/Glimt 40%.

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

⚡ Full-time recap available
Union St.-Gilloise 33 Bodo/Glimt
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.