FC Midtjylland vs Beşiktaş AI Predictions — UEFA Europa League

2nd Qualifying Round·30 Jul · 17:00 UTC·MCH Arena·✓ Completed
FC Midtjylland flagFC Midtjylland
02
Beşiktaş flagBeşiktaş

AI consensus

Consensus pick
FC Midtjylland
Model consensus · ✗ missed
Consensus score
1-1
No exact-score hits
How the field split
H 81% · D 6% · A 13%
Market odds (Pinnacle)
FC Midtjylland1.88
Draw3.75
Beşiktaş3.67

The consensus pick and the consensus score answer different questions. A result is one bucket holding many scorelines, while 1-1 is the most common score in football on its own. So the likeliest result and the likeliest exact score often point different ways, for a single model and for the field. Grading reads the result. How predictions are elicited →

Every model's prediction

16 of 17 locked models answered
ModelHome %Draw %Away %Predicted score90-min resultExact score
Claude Opus 5 Anthropic flag
42%26%32%1-1✗ miss
40%28%32%1-1✗ miss
32%26%42%1-2✓ hit
38%34%28%1-1✗ miss
41%28%31%2-1✗ miss
38%27%35%1-1✗ miss
MiniMax M3 MiniMax flag
30%38%32%1-1✗ miss
40%28%32%2-1✗ miss
42%27%31%1-1✗ miss
43%26%31%2-1✗ miss
40%35%25%1-1✗ miss
38%27%35%1-1✗ miss
38%28%34%1-1✗ miss
48%27%25%2-1✗ miss
MiMo v2.5-Pro Xiaomi flag
36%28%36%1-1✗ miss
32%28%40%1-2✓ hit
Claude Opus 5 Anthropic flagHOME1-1
H 42% · D 26% · A 32%✗ miss✗ exact
DeepSeek V4 Pro DeepSeek flagHOME1-1
H 40% · D 28% · A 32%✗ miss✗ exact
Gemini 3.1 Pro Google flagAWAY1-2
H 32% · D 26% · A 42%✓ hit✗ exact
Gemini 3.5 Flash Google flagHOME1-1
H 38% · D 34% · A 28%✗ miss✗ exact
Gemini 3.6 Flash Google flagHOME2-1
H 41% · D 28% · A 31%✗ miss✗ exact
Gemma 4 31B Google flagHOME1-1
H 38% · D 27% · A 35%✗ miss✗ exact
MiniMax M3 MiniMax flagDRAW1-1
H 30% · D 38% · A 32%✗ miss✗ exact
Mistral Large 3 Mistral flagHOME2-1
H 40% · D 28% · A 32%✗ miss✗ exact
Kimi K2.6 Moonshot flagHOME1-1
H 42% · D 27% · A 31%✗ miss✗ exact
Kimi K3 Moonshot flagHOME2-1
H 43% · D 26% · A 31%✗ miss✗ exact
Nemotron 3 Ultra NVIDIA flagHOME1-1
H 40% · D 35% · A 25%✗ miss✗ exact
GPT-5.6 Sol OpenAI flagHOME1-1
H 38% · D 27% · A 35%✗ miss✗ exact
Qwen3.7 Plus Alibaba flagHOME1-1
H 38% · D 28% · A 34%✗ miss✗ exact
Grok 4.5 xAI flagHOME2-1
H 48% · D 27% · A 25%✗ miss✗ exact
MiMo v2.5-Pro Xiaomi flagHOME1-1
H 36% · D 28% · A 36%✗ miss✗ exact
GLM-5.2 Z.ai flagAWAY1-2
H 32% · D 28% · A 40%✓ hit✗ exact

Locked before kickoff. Predictions contribute independently to 90-minute accuracy, exact score, RPS, and eligible ROI.Confidence is the model's self-reported level for this prediction.

Model explanation

Questions & answers

What are the AI predictions for FC Midtjylland vs Beşiktaş?
This page records every AI model's prediction for FC Midtjylland vs Beşiktaş in the UEFA Europa League (2nd Qualifying Round). Each model returned a home/draw/away probability distribution and its single most likely exact scoreline before kickoff. How the predictions are scored →
When and where was FC Midtjylland vs Beşiktaş played?
The match kicked off 30 Jul · 17:00 UTC at MCH Arena. It is part of the UEFA Europa League on footballarena.ai's UEFA Europa League hub.
Did AI models predict the correct result for FC Midtjylland vs Beşiktaş?
No. The AI consensus picked FC Midtjylland, but the match finished 0–2 — Beşiktaş. 81% of 16 models had backed the consensus pick. The full per-model breakdown is in the table above.
How did the AI models split on FC Midtjylland vs Beşiktaş?
Of 16 models: 81% picked FC Midtjylland, 6% a draw, and 13% Beşiktaş. The consensus pick was FC Midtjylland; the most-backed exact score was 1-1.
What were the betting odds for FC Midtjylland vs Beşiktaş?
Closing odds (Pinnacle): FC Midtjylland 1.88 · Draw 3.75 · Beşiktaş 3.67. Whichever price is shortest is the market favourite, and that is the baseline AI models are graded against on accuracy and betting ROI. How scoring works →
How many AI models predicted FC Midtjylland vs Beşiktaş?
17 models were locked into this fixture (16 answered — the rest had a provider call fail). Every model on footballarena.ai works from the same fixture set under the same scoring rules. See the model directory.

Research updates, published here

Findings, upsets and model behaviour, straight from the scored record.