Ferencvaros vs Plzen Prediction & AI Analysis

Prediction Against Result

Ferencvaros 2–1 Plzen, UEFA Europa League. Below is what this page published before kickoff, set next to what actually happened.

• Final score — Ferencvaros 2–1 Plzen
• Model's leading outcome before kickoff — Ferencvaros win, roughly 51%
• Ferencvaros win — the simulation gives roughly 51%
• Draw — the simulation gives roughly 23%
• Plzen win — the simulation gives roughly 26%
• Verdict — hit: the leading outcome matched the result

The model's leading outcome was Ferencvaros win at roughly 51%, and the match finished 2–1. Called correctly.

Reading the Split

The model puts real weight behind one side: Ferencvaros win at 51%, 25 points clear of the next outcome, Plzen win at 26%. On a three-way market that is a clear lean rather than a close call.

Across the 320 match pages published on this site, the median favourite carries 51%. This one's 51% sits right around it — an ordinary split by our own standard.

The simulated goal averages are Ferencvaros 1.90 and Plzen 1.32, 3.22 between them, with the scoring expectation tilted towards Ferencvaros. That total is close to the 3.29 median across our published pages.

One thing 51% is not: a statement that this will happen. The remaining 49% belongs to the same distribution and describes matches that get played too. A 51% call that came in every single time would mean the number had been written wrong, not that the model is strong.

Where the Result Landed in the Distribution

The outcome that landed was Ferencvaros win — the top line of the pre-match distribution, at 51%. Landing does not make that 51% anything close to a certainty: the other 49% described matches that were just as available from the same three numbers.

On goals: the simulation totalled 3.22 across the two sides, and the match produced 3.

Ferencvaros and Plzen on Earlier Pages

Ferencvaros or Plzen has appeared on 2 earlier pages of ours. Each is linked below with the probability split we published at the time and, where the fixture has settled, what the match actually produced.

• 2026-09-17 — Celtic vs Ferencvaros · Celtic 58% / Draw 21% / Ferencvaros 21% · finished 1–3, graded a miss
• 2026-09-17 — Plzen vs Royale Union Saint-Gilloise · Plzen 39% / Draw 27% / Royale Union Saint-Gilloise 34% · finished 0–3, graded a miss

Where This Fixture Sits in Our UEFA Europa League Record

We have published 54 UEFA Europa League match pages, this one included. 44 of them have settled: 26 graded a hit, 18 graded a miss, 0 void. Counts, not a rate — if you would rather count them yourself, they are all at Predictions.

What One Match Proves

A single fixture settles nothing about a model, in either direction. A side with less than an even chance that wins was never a foregone conclusion, and one that loses was never a blunder — the number was a statement about frequency, and frequency only becomes visible over a run of matches. The honest test is the accumulated ledger, which is why every published signal is settled in public instead of the good ones being quoted twice.

Timestamps

The simulation was observed at 2026-10-05 01:53 UTC; kickoff was 2026-10-15 19:00 UTC. The prediction was published before kickoff and the timestamp is verifiable — which is the only reason this comparison is worth printing.

Check the Rest of the Record

Live signals from the same system are published on Telegram through @Oddsflowteam_bot, each timestamped before its match. The weekly ledger on this site lists them line by line — timestamp, market, price, final score, result — with the losses in the same type as the wins.

Verify This Page Yourself

Both ends of this page are now fixed: the file was written 1 day 8 hours before kickoff (generated 2026-10-14 10:10 UTC, kickoff 2026-10-15 19:00 UTC), and the result was appended only afterwards. An unedited copy of the pre-match numbers sits in the public mirror as record/data/ferencvaros-vs-plzen-1636260.json — browse the public record. The commit history is the more interesting half of that repository: it shows when each number was written down, which is the one part of a record that cannot be reconstructed later. The grading rules behind the verdict above are set out in How We Count Our Record.