Switzerland vs Bosnia and Herzegovina AI prediction

The model’s strongest regulation-time outcome is Switzerland win at 79%. Explore the complete probability picture and test alternative scoring assumptions below.

SWSwitzerlandHome

Most likely score2–013% probability

BOBosnia and HerzegovinaAway

79%15%7%

Switzerland winDrawBosnia and Herzegovina win

Both teams scoreNo58%

2.5 goalsOver62%

Expected goals2.69 · 0.63Home · away

Interactive scenario

Prediction playground

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

Switzerland2.69Expected goals · model says 2.69Bosnia and Herzegovina0.63Expected goals · model says 0.63

Win probability

81%13%6%

SwitzerlandDrawBosnia and Herzegovina

Over 2.5 goals64%

BTTS: yes44%

Likely scores2–0 · 3–0 · 1–0

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

Switzerland 79% · Draw 15% · Bosnia and Herzegovina 7%

Both teams to score

Yes 42% · No 58%

Over / under 2.5

Over 62% · Under 38%

Most likely exact scores

Top five cells in the published score distribution.

012–013%023–011%031–011%042–17%054–07%

Complete exact-score matrix

Rows show Switzerland goals; columns show Bosnia and Herzegovina goals. All 256 published cells are included.

H \ A	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15
0	5.2%	2.4%	0.8%	0.2%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%
1	10.6%	6.4%	1.9%	0.5%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%
2	12.8%	7.3%	2.4%	0.6%	0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%
3	10.7%	6.3%	2.1%	0.5%	0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%
4	7.2%	4.3%	1.5%	0.4%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%	<0.1%
5	4.1%	2.6%	0.9%	0.2%	<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	2.1%	1.3%	0.5%	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%
7	1.0%	0.6%	0.2%	<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	0.4%	0.3%	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%
9	0.2%	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.

01
Fit team strengths
The upstream Bayesian model estimates attack, defence and home-advantage parameters from international results.
02
Build match probabilities
Expected scoring rates produce an exact-score probability grid; 1X2, BTTS and goal totals are derived from it.
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

Continue exploring

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