AI FOOTBALLPREDICTION LAB
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All predictionsGroup · 2026-06-27
Pre-tournament snapshothigh model confidence

New Zealand vs Belgium AI prediction

The model’s strongest regulation-time outcome is Belgium win at 95%. Explore the complete probability picture and test alternative scoring assumptions below.

NENew ZealandHome
Most likely score0–313% probability
BEBelgiumAway
1%4%95%
New Zealand winDrawBelgium win
Both teams scoreNo73%
2.5 goalsOver80%
Expected goals0.32 · 4.22Home · away
Interactive scenario

Prediction playground

Change either scoring rate. Every probability below recalculates immediately with a Poisson scoreline model.

Win probability
1%3%96%
New ZealandDrawBelgium
Over 2.5 goals83%
BTTS: yes27%
Likely scores0–4 · 0–3 · 0–5

Play this fixture once with the probabilities above. Every run is different.

Scenario controls run locally and leave the published model snapshot unchanged.
Probability at a glance

What the score grid says

Aggregate markets below are calculated directly from the same exact score distribution—not produced as separate tips.

Match result

New Zealand 1% · Draw 4% · Belgium 95%

Both teams to score

Yes 27% · No 73%

Over / under 2.5

Over 80% · Under 20%

Most likely exact scores

Top five cells in the published score distribution.

010–313%020–413%030–511%040–210%050–68%
Complete exact-score matrix

Rows show New Zealand goals; columns show Belgium goals. All 256 published cells are included.

H \ A0123456789101112131415
01.7%5.6%10.2%12.9%12.8%10.6%7.7%5.0%3.0%1.7%0.9%0.5%0.2%0.1%<0.1%<0.1%
10.4%1.8%3.2%4.0%4.0%3.3%2.4%1.6%0.9%0.5%0.3%0.1%<0.1%<0.1%<0.1%<0.1%
2<0.1%0.3%0.6%0.7%0.7%0.6%0.4%0.3%0.2%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
3<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
4<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
5<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
6<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
7<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
8<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
9<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
10<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
11<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
12<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
13<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
14<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
15<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%<0.1%
How this was made

From team strength to a score distribution.

  1. 01
    Fit team strengths

    The upstream Bayesian model estimates attack, defence and home-advantage parameters from international results.

  2. 02
    Build match probabilities

    Expected scoring rates produce an exact-score probability grid; 1X2, BTTS and goal totals are derived from it.

  3. 03
    Simulate the tournament

    Repeated complete tournament paths produce progression and title probabilities for every team.

Forecast wc2026-2026-06-04-2026-100 · Data through 2026-06-04 · 100 tournament runs Source at pinned commit
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