Match prediction·World: World Cup·Wednesday 24 Jun, 02:00 UTC

Colombia vs Congo DR

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 76% is the play—both sides project 2.62 combined xG with Colombia's Luis Díaz and Jhon Durán accounting for over a third of their attacking threat.

📊 Win probability
37.0% home32.3% draw30.7% away
📈 xG chain — base → adjustments → final goal estimate
ColombiastepCongo DR
1.38Base xG · rolling 26-match1.24
no injury adjustment — full squads available per FotMob
1.38Final goal estimate — what the model uses1.24

Colombia average 4.3 corners per game at home this season (3 competitive matches). Congo DR average 3.5 corners per game away from home this season (2 competitive matches).

🎯 Scoreline distribution · chance of each scoremodel estimate
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home windrawaway win
Most likely outcomes
Over 1.5 goals
76%
Over 3.5 goals
23%

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

Most likely to score or assist

To score
Luis Díaz
Colombia · Bayern Munich
38%

Probabilities from a per-player model on recent form and minutes played.

More predictions for these teams

Colombia vs Congo DR — Head-to-Head

This is the first meeting Bawler has on record between Colombia and Congo DR — 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: Colombia 37% · draw 32% · Congo DR 31%.

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

⚡ Full-time recap available
Colombia 10 Congo DR
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.