Bournemouth
Sturm GrazMost likelyBournemouth win · 80%
Best price1.23 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 upcoming UEFA Europa League fixture, AFC Bournemouth prepares to host Sturm Graz, with statistical modeling indicating a significant disparity in expected outcomes for the two sides. The model assigns Bournemouth an 80% probability of victory, while a draw is calculated at 13% and an away win for Sturm Graz at 7%. The model’s strong lean toward the hosts is driven by several analytical factors. Central to this assessment is the team-tuned home advantage, which accounts for Bournemouth’s performance metrics on their own turf, alongside a favorable Pi-rating edge. Additionally, the model incorporates defensive expected goals (xG) data, which suggests that the current defensive form of the traveling side provides further support for the host’s position. It is worth noting that while the model favors Bournemouth, its internal calculation sits slightly below the current market pricing for an outright home win. Recent form offers a mixed picture for both clubs. Bournemouth enters this encounter with a sequence of loss, loss, win, draw, draw. Conversely, Sturm Graz’s recent run reads draw, loss, loss, win, win. As these two teams have no previous competitive history against one another, this will be their first head-to-head meeting. Regarding squad availability, no injuries have been reported for either side. However, as confirmed lineups have not yet been finalized, these reports do not account for potential squad rotation or the resting of starters, and therefore should not be interpreted as an indication of full-strength lineups for either club. Given the probabilities and the underlying factors, the data points toward a challenging evening for the visitors, though the nature of European competition often introduces variables that models are designed to measure, rather than guarantee.
The AI writes the prose. It never produces or adjusts a probability — those come only from the model.
| Bookmaker | Bournemouthpays 3% more than the typical book | Drawpays 1% more than the typical book | Sturm Grazpays 8% more than the typical book |
|---|---|---|---|
| Bet365 | 1.20 | 7.00 | 13.00 |
| Betano | 1.23best | 7.60 | 13.00 |
| Betfair | 1.17 | 7.50 | 14.00best |
| Marathonbet | 1.19 | 7.60best | 13.25 |
Bookmaker names shown for reference only. No affiliate links.
Two ways to size a hypothetical stake on the model's call — Bournemouth at 1.23 (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 assigns Bournemouth an 80% probability of victory, while a draw is calculated at 13% and a win for Sturm Graz at 7%. This distribution is driven by a combination of factors, including a superior Elo rating that accounts for home advantage and a strong underlying defensive expected goals (xG) profile for Bournemouth. Additionally, the model’s Pi-rating analysis further supports this outlook on the match, although the model’s valuation of Bournemouth currently sits slightly below market pricing. While neither side has reported injuries, it remains important to note that these figures do not account for potential squad rotation, and the teams hold no historical head-to-head record to influence these projections.
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.