CSKA Sofia
MonacoMost likelyMonaco win · 61%
Best price1.57 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
CSKA Sofia hosts Monaco in this UEFA Europa Conference League encounter, a fixture where the model’s data points toward a distinct outcome. The probabilities currently favor a Monaco victory at 61%, while the likelihood of a draw sits at 21% and a CSKA Sofia win at 18%. When comparing these figures to broader market expectations, the model places itself slightly lower on the probability of a Monaco win, suggesting a more conservative outlook than the wider consensus. Several core metrics drive this assessment. The Elo difference, when adjusted for the impact of team-tuned home advantage, supports the lean toward the visitors. Similarly, the Pi-rating edge aligns with this favor for Monaco. However, there is a counteracting factor: the rest-days edge operates against the visitors, potentially narrowing the perceived gap between the two sides. Recent form provides a stark contrast entering the match. CSKA Sofia’s trajectory in their most recent outings has been difficult, recording a sequence of three losses followed by a win and a draw. Monaco, by contrast, arrives with more consistent momentum, having accumulated three wins and two draws in their last five matches. Regarding squad availability, there are no reported injuries for either side. It is important to note that without confirmed lineups, it is not possible to determine if either team intends to deploy its primary XI or utilize squad rotation to manage player fatigue. Consequently, observers should not assume that the absence of reported injuries equates to teams playing at full strength. As these two clubs have no previous meetings on record, this match serves as a blank slate for both sides in their European campaign.
The AI writes the prose. It never produces or adjusts a probability — those come only from the model.
| Bookmaker | CSKA Sofiapays 4% more than the typical book | Drawpays 2% more than the typical book | Monacopays 3% more than the typical book |
|---|---|---|---|
| Bet365 | 5.50 | 4.50 | 1.53 |
| Betano | 5.90 | 4.60 | 1.57best |
| Betfair | 6.00 | 4.50 | 1.47 |
| Marathonbet | 6.05best | 4.60best | 1.54 |
Bookmaker names shown for reference only. No affiliate links.
Two ways to size a hypothetical stake on the model's call — Monaco at 1.57 (Betano).
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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.
No previous meetings on record.
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 calculates an 18% probability of a win for CSKA Sofia, a 21% chance of a draw, and a 61% likelihood of a Monaco victory in this UEFA Europa Conference League fixture. This outlook is primarily driven by a significant Elo difference, accounting for home advantage, and a favorable Pi-rating edge for the visiting side. While Monaco’s recent form is stronger, characterized by three wins and two draws in their last five outings compared to CSKA Sofia’s single win and draw in the same span, the model notes that a rest-days edge slightly complicates the assessment. Notably, the model sits slightly below the broader market's pricing on Monaco, despite the general alignment. As no injuries have been reported for either side, potential squad rotation remains an unknown variable.
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.