Ferencvarosi TC
PlzenMost likelyFerencvarosi TC win · 53%
Best price1.98 Betano
Market-anchored: the market's vig-free price (1 sharp book) + model lean (max ±3 pp)
These are calibrated probabilities. See how closely they've matched real outcomes
Prediction as of 15 Oct 2026
In this UEFA Europa League encounter, Ferencvárosi TC hosts Viktoria Plzeň, with the model’s calibrated probabilities pointing toward a lean for the home side. Ferencvárosi TC is assigned a 53% probability of securing a victory, compared to 24% for Viktoria Plzeň and a 23% probability of the match ending in a draw. This outlook positions the model slightly above the current market consensus regarding Ferencvárosi’s likelihood of winning. Several metrics drive this assessment. The model finds support for the Ferencvárosi lean in the team’s attacking expected goals (xG) form when playing at home. Simultaneously, the defensive xG form of Plzeň on the road has been a contributing factor favoring the host. Furthermore, when adjusting for team-tuned home advantage within the Elo ratings, the data indicates a favorable setup for Ferencvárosi. It is worth noting that while these statistical factors align with the model's lean, previous meetings between these two sides have been historically competitive and roughly even. Form heading into the fixture offers a distinct contrast between the two clubs. Ferencvárosi TC enters the match with strong recent momentum, recording four wins and one draw across their last five outings (W-W-W-D-W). Viktoria Plzeň’s recent trajectory has been more uneven, with a sequence of one win, two losses, and two draws in their most recent five matches (L-W-L-D-D). Regarding squad availability, there are no reported injuries for either team at this time. However, as confirmed lineups have yet to be finalized, these reports do not account for potential squad rotation or the resting of starters, and the absence of injury news should not be interpreted as a confirmation that either side will field a specific XI.
The AI writes the prose. It never produces or adjusts a probability — those come only from the model.
| Bookmaker | Ferencvarosi TCpays 2% more than the typical book | Drawpays 2% more than the typical book | Plzenpays 9% more than the typical book |
|---|---|---|---|
| Bet365 | 1.91 | 3.80 | 3.70 |
| Betano | 1.98best | 3.80 | 3.95best |
| Betfair | 1.95 | 3.80 | 3.60 |
| Marathonbet | 1.92 | 3.88best | 3.74 |
Bookmaker names shown for reference only. No affiliate links.
Two ways to size a hypothetical stake on the model's call — Ferencvarosi TC at 1.98 (Betano).
Stays in your browser — never sent to us.
Flat 1% of bankroll — the same rule as our public AI bankroll simulation.
Quarter-Kelly at the best listed price, with a hard 5%-of-bankroll cap.
Hypothetical sizing in currency-neutral units, not betting advice. Predictions are probabilities, not guarantees. 18+.
↑ stronger · = even · ↓ weaker opponent
↑ stronger · = even · ↓ weaker opponent
No reported absences.
No reported absences.
Recent form — context only, not a tip.
No line movement recorded yet
No line movement recorded yet
No line movement recorded yet
How the model sees this match — the drivers and, after full-time, how the prediction scored.
The model assigns a 53% probability to a Ferencvarosi TC victory, with a draw at 23% and a Plzen win at 24%, suggesting a lean toward the home side. This output is driven by Ferencvarosi TC’s strong attacking xG form at home, paired with Plzen’s defensive xG metrics in away fixtures. Furthermore, the model incorporates an Elo-based calculation that accounts for a team-tuned home advantage, contributing to the model's stance being slightly more bullish on Ferencvarosi TC than the broader market. While both teams enter the fixture with no reported injuries, the model emphasizes these structural performance indicators over their historically even head-to-head record and recent form trends.
The AI writes the prose. It never produces or adjusts a probability — those come only from the model.
How we make these predictionsThe driver chips attribute the gradient-boosted component of an ensemble whose headline is additionally anchored to the market where a consensus exists — they explain that part of the number, not all of it.