Bundesliga · Matchday 9
Prediction: VfB Stuttgart vs SV Werder Bremen
Saturday, 7 November 2026 17:30 UK time
Our AI makes VfB Stuttgart the favourite for VfB Stuttgart vs SV Werder Bremen, with a 40.1% win probability. Kick-off: Saturday, 7 November 2026 at 17:30 UK time.
Balanced fixture for VfB Stuttgart - SV Werder Bremen on Saturday, 7 November 2026. No clear AI favorite: 40.1% home, 26.5% draw, 33.4% away. Statistical details settle the duel on the margins.
For VfB Stuttgart (13), hosting SV Werder Bremen (8) is a chance to make a statement before the season ends. With VfB Stuttgart a slight favourite per our AI, the match looks tight and pivotal for both sides.
Key takeaways
- 🎯 Key scorer for VfB Stuttgart: Josha Vagnoman (2)
- 🎯 Key scorer for SV Werder Bremen: Niclas Füllkrug (6)
- ⚽ SV Werder Bremen scores heavily: 2 goals/match average over last 6
- 🗓️ Matchday 9, Bundesliga
AI Predictor Forecast
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League standings
Recent form details (last 6 matches)
VfB Stuttgart
Recent form details (last 6 matches)
- 2026-09-12
- 2026-09-19
- 2026-10-10
- 2026-10-14
- 2026-10-17
- 2026-10-20
⚽ Top scorer : Josha Vagnoman (2)
Across its last 6 outings, VfB Stuttgart has 2 wins, 1 draw(s), and 3 defeat(s). Offensive output sits at 1.17 goal(s)/match, defensive at 0.83. Both teams have scored in 33% of recent games.
SV Werder Bremen
Recent form details (last 6 matches)
- 2026-08-30
- 2026-09-05
- 2026-09-12
- 2026-09-19
- 2026-10-09
- 2026-10-17
⚽ Top scorer : Niclas Füllkrug (6)
Across its last 6 outings, SV Werder Bremen has 2 wins, 3 draw(s), and 1 defeat(s). Offensive output sits at 2.00 goal(s)/match, defensive at 2.00. Both teams have scored in 100% of recent games.
⚔️ Head-to-head (last 5 meetings)
| Date | Match | Competition |
|---|---|---|
| 2026-04-26 | VfB Stuttgart 1-1 SV Werder Bremen | Bundesliga |
| 2025-12-14 | SV Werder Bremen 0-4 VfB Stuttgart | Bundesliga |
| 2025-04-13 | VfB Stuttgart 1-2 SV Werder Bremen | Bundesliga |
| 2024-11-30 | SV Werder Bremen 2-2 VfB Stuttgart | Bundesliga |
| 2024-04-21 | SV Werder Bremen 2-1 VfB Stuttgart | Bundesliga |
Our analysis
Our analysis cross-references several indicators: standings (6 pts vs 9 pts), current dynamics (form – vs –), and computed xG (1.92 vs 1.74). The Dixon-Coles model, especially suited to asymmetric matches, returns a 40.1% probability of a VfB Stuttgart win.
How our AI reaches this prediction
Concretely, the Poisson model estimates goal distribution from adjusted xG averages, ELO recalibrates per recent performance, and Dixon-Coles corrects low scorelines (0-0, 1-0, 1-1). Triangulation produces the final forecast: 40.1% / 26.5% / 33.4%.
🎯 Key takeaways
- ▸ Over 2.5 goals has hit in 83% of SV Werder Bremen's recent matches.
- ▸ Both teams have scored in 100% of SV Werder Bremen's recent matches.
- ▸ VfB Stuttgart relies on Josha Vagnoman (2) as the Bundesliga top scorer.
- ▸ SV Werder Bremen relies on Niclas Füllkrug (6) as the Bundesliga top scorer.
Our verdict
In short, VfB Stuttgart stands as our algorithm's favourite at 40.1%. The modelled scoreline sits around 1-1, and the Over 2.5 (71%) and BTTS (71%) indicators round out the picture for value bettors.
Frequently asked questions
When is VfB Stuttgart vs SV Werder Bremen played? +
The VfB Stuttgart - SV Werder Bremen match is scheduled for Saturday, 7 November 2026 at 17:30 UK time in the Bundesliga.
Who is the favorite between VfB Stuttgart and SV Werder Bremen? +
Our AI Predictor picks VfB Stuttgart as the favorite with a 40.1% win probability. Full odds: 40.1% for Stuttgart, 26.5% draw, 33.4% for Bremen.
What is the most likely score for VfB Stuttgart vs SV Werder Bremen? +
Our Poisson model projects a final score of 1-1, with expected goals (xG) of 1.92 for VfB Stuttgart and 1.74 for SV Werder Bremen.
Will there be over 2.5 goals in this match? +
Our AI estimates the Over 2.5 goals probability at 71% for this VfB Stuttgart - SV Werder Bremen fixture.
How does Talacote compute this prediction? +
Our AI Predictor combines three algorithms: Poisson for goal distribution, ELO for relative team strength, and Dixon-Coles for low-score adjustment. The analysis cross-references form, standings, and historical data.
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