MON 1-1 CLU · 43% GUA 2-0 ATL · 58% COL 1-2 CHI · 49% CLU 2-1 TOL · 54% YOK 1-2 KAW · 47% JEF 1-1 AVI · 42% V-V 1-0 TOK · 44% MAC 2-0 GAM · 62% AME 3-0 EYü · 71% PEC 1-1 ADO · 40% COM 2-0 VEN · 63% CER 1-2 ANT · 50% GET 0-1 SEV · 50% FAL 0-2 CEL · 62% MON 1-1 CLU · 43% GUA 2-0 ATL · 58% COL 1-2 CHI · 49% CLU 2-1 TOL · 54% YOK 1-2 KAW · 47% JEF 1-1 AVI · 42% V-V 1-0 TOK · 44% MAC 2-0 GAM · 62% AME 3-0 EYü · 71% PEC 1-1 ADO · 40% COM 2-0 VEN · 63% CER 1-2 ANT · 50% GET 0-1 SEV · 50% FAL 0-2 CEL · 62%
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Football results Thursday 1 October 2026: AI predictions review

Results

Football results Thursday 1 October 2026: AI predictions review

Football results Thursday 1 October 2026: the AI consensus called 3 of 8 Nations League matches right, as Azerbaiijan, Malta and Wales upset the models.

TuringStats Editorial Oct 2, 2026 4 min read

Thursday 1 October 2026 produced a night of UEFA Nations League football that the models will want to forget. Ten frontier AI systems were run against eight fixtures before kickoff, and when the full-time whistles had blown the consensus had landed just 3 of 8 correct — a below-par return for a slate dominated by heavy favourites and low-scoring expectations.

The biggest surprise came in Baku, where Azerbaijan and Liechtenstein played out a 0-0 draw. All ten models had backed Azerbaijan to win, with 2-0 the most common scoreline and an average confidence of 64%. It was the most one-sided call of the day and the one that went furthest wrong. Malta and Wales added to the damage later in the evening, but the Azerbaijan result set the tone.

Unbranded players walking off a floodlit pitch at full time after a goalless Nations League draw

Full time in the Nations League: a night when the consensus found only three of eight results.

Where the AI got it right

Germany vs Serbia prediction — the most straightforward call of the night and the models took it. A 100% consensus for a Germany win, with 2-0 the most common scoreline at 60% average confidence, was matched exactly by the final score in a controlled home display.

Denmark vs Portugal prediction — only 70% of the ten models backed Portugal, the lowest agreement of any correct call, and the most common scoreline of 1-2 was well short of the truth. Portugal's 4-2 win in Denmark rewarded the majority who ignored the draw risk.

Rep. Of Ireland vs Austria prediction — the draw was the pick here, backed by 80% of models with 1-1 the modal scoreline and 53% average confidence. The actual 2-2 was a higher-scoring version of the same outcome, and the second of only three correct calls on the day.

Where it got it wrong

Azerbaijan vs Liechtenstein prediction — a unanimous Azerbaijan win, modal score 2-0, 64% confidence. The match finished 0-0. No model saw a goalless draw coming, and the failure was total rather than marginal.

Greece vs Netherlands prediction — all ten models picked a Netherlands win, with 0-1 the most common scoreline and 58% average confidence. Greece held them to 2-2, a result that punished a consensus built on a narrow away win.

Wales vs Norway prediction — 70% of models expected a draw, 1-1 the modal score, 52% confidence. Wales won 2-1 instead, making this the slate's lowest-conviction miss and the one the models were least united on to begin with.

Israel vs Kosovo prediction — a 60% majority backed an Israel win at 1-0, with 53% average confidence. The game ended 0-0, so the models were right about the low score and wrong about who would find the net.

Malta vs Gibraltar prediction — another unanimous call, ten out of ten for a Malta win at 1-0, average confidence 59%. It finished 1-1. Alongside Azerbaijan, this was the second fixture where the entire panel agreed and the entire panel was wrong.

Models of the day

The best performers were GPT-5.6 Luna and DeepSeek V4 Pro, each with 4 of 8 correct — one clear of the field on a difficult day. Behind them sat a five-strong group on 3 of 8: Claude Sonnet 5, Mistral Medium 3.5, Qwen 3.8 Max, Gemini 3.8 Flash and Kimi K3.

The bottom of the table was shared by MiMo V2.5 Pro, Grok 4.6 and GLM 5.3, all on 2 of 8 correct. None of the ten models reached the 50% mark, which says as much about the night as it does about any individual system.

Full results

  • UEFA Nations League: Azerbaijan 0-0 Liechtenstein — consensus Azerbaijan win (100%) WRONG
  • UEFA Nations League: Germany 2-0 Serbia — consensus Germany win (100%) RIGHT
  • UEFA Nations League: Greece 2-2 Netherlands — consensus Netherlands win (100%) WRONG
  • UEFA Nations League: Denmark 2-4 Portugal — consensus Portugal win (70%) RIGHT
  • UEFA Nations League: Wales 2-1 Norway — consensus draw (70%) WRONG
  • UEFA Nations League: Rep. Of Ireland 2-2 Austria — consensus draw (80%) RIGHT
  • UEFA Nations League: Israel 0-0 Kosovo — consensus Israel win (60%) WRONG
  • UEFA Nations League: Malta 1-1 Gibraltar — consensus Malta win (100%) WRONG

The pattern is uncomfortable: three of the five misses came from unanimous or near-unanimous calls, and two goalless draws landed on fixtures where every model expected goals. Whether that reflects a genuine blind spot around low-scoring stalemates or simply a bad Thursday is a question the next slate will help answer. Today's fixtures and the full model-by-model output are already live on the today's predictions page.

Next up: today's football predictions from the same panel, and the results archive with every graded call. Forecasts are informational only.

— Journal

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