Estadísticas / Fútbol / Germany. Bundesliga / 1899 Hoffenheim vs VfB Stuttgart

1899 Hoffenheim vs VfB Stuttgart Statistics & Analysis

1899 Hoffenheim 1899 Hoffenheim
May 02, 2026 - 13:30
3 1.83
3 1.60
xG Accuracy: 49%
VfB Stuttgart VfB Stuttgart
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Tracked markets vs full-time result

Each row compares the model’s highlighted side (or lean) to what happened at full time.

  • Market Prediction Result Outcome
  • Más / Menos de 2.5 Menos de 2.5 Más de 2.5 (6 goals) ✖ Incorrect
  • Ambos Equipos Marcarán BTTS No Sí ✖ Incorrect
  • 1X2 1899 Hoffenheim Dibujar ✖ Incorrect
  • Perspectivas de marcador exacto 1-1 3-3 ✖ Incorrect

Informe IA del partido

Resumen del partido IA

Pre-match snapshot for this fixture.

  • League: Bundesliga
  • Fixture: 1899 Hoffenheim vs VfB Stuttgart
  • Kickoff: 2026-05-02 13:30:00
  • 1X2 (model): Home 42.4% · Draw 24.9% · Away 32.8%
  • xG (showing): 1899 Hoffenheim 1.83 — VfB Stuttgart 1.6 (total xG ≈ 3.43)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Under 2.5 goals
  • Model: 33.4% · Implied: 31.1% · Probability edge: +2.3 pts · Est. EV: +6.9%
  • BTTS (model): Yes 68.2% · No 31.8%
  • Correct score (top bin): 1-1 (9.5%)

Totals and BTTS are evaluated against current market prices where available.

Early match state can move realised goals away from pre-kick projections.

Mejor apuesta y razones

Strongest +EV line among tracked markets (not shown as a full Primary under current engine thresholds): Under 2.5 goals.

If 1X2 looks tight, the engine may still find clearer structure in totals or BTTS — that is intentional.

No pick is a guarantee; variance is especially large in scoreline markets.

FAQ

How should I read EV versus a probability gap?

Probability edge = model probability minus implied probability (reported here in percentage points). EV ≈ model probability × best tracked decimal odds − 1, shown as return per unit stake. They are related but not interchangeable labels.

Who has the edge in the match-winner market?

Use the 1X2 model percentages in the summary and the 1X2 market card: the side with the highest model % is the model lean, but check EV — a lean can still be -EV after prices.

Why might 1X2 look unattractive while totals do not?

Tight 1X2 prices often embed a fair three-way split, so EV on match-winner can sit negative even when Over/Under or BTTS still diverges from the model — compare the 1X2 row on the market cards to O/U and BTTS.

What is the best-supported line in this snapshot?

Match the hero card above: if it says “Betting Primary Pick”, that leg cleared primary rules; if it says “Best +EV (tracked markets)”, it is the strongest +EV line that did not meet stricter Primary thresholds. The bullets below repeat the same model %, implied %, edge (pts), and EV % as that card.

Factores de riesgo

  • Price movement: implied probabilities and EV move with odds.
  • Sample / data gaps: low-information leagues widen forecast bands.
  • In-play state: goals and red cards are not modelled here.
  • Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

Metodología

  • Inputs: Same structured facts bundle as the public prediction page (xG / Poisson snapshot, market EV where available, decision engine v2).
  • Narrative: Template sentence library with fixture-stable selection (no per-request LLM for this block).
  • Compliance: Educational framing only; not personalised advice.

Última actualización

May 01, 2026 (UTC)

¿Cómo usar esto?
  • Concéntrese en la línea principal cuando desee una idea viable.
  • No combine muchas púas de punta fina;Los bordes no se suman de manera confiable.
  • Trate las apuestas arriesgadas como jugadas opcionales y de alto riesgo únicamente.

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Bundesliga Bundesliga — Clasificación
# EQUIPO PJ G E P Pts
1 Bayern München 33 27 5 1 86
2 Borussia Dortmund 33 21 7 5 70
3 RB Leipzig 33 20 5 8 65
4 VfB Stuttgart 33 18 7 8 61
5 1899 Hoffenheim 33 18 7 8 61
6 Bayer Leverkusen 33 17 7 9 58
7 SC Freiburg 33 12 8 13 44
8 Eintracht Frankfurt 33 11 10 12 43
9 FC Augsburg 33 12 7 14 43
10 FSV Mainz 05 33 9 10 14 37
11 Hamburger SV 33 9 10 14 37
12 Union Berlin 33 9 9 15 36
13 Borussia Mönchengladbach 33 8 11 14 35
14 1. FC Köln 33 7 11 15 32
15 Werder Bremen 33 8 8 17 32
16 VfL Wolfsburg 33 6 8 19 26
17 1. FC Heidenheim 33 6 8 19 26
18 FC St. Pauli 33 6 8 19 26
# EQUIPO PJ GF GC +/- Pts
1 Bayern München 33 117 35 +82 86
2 VfB Stuttgart 33 69 47 +22 61
3 Borussia Dortmund 33 68 34 +34 70
4 Bayer Leverkusen 33 67 46 +21 58
5 RB Leipzig 33 65 43 +22 65
6 1899 Hoffenheim 33 65 48 +17 61
7 Eintracht Frankfurt 33 59 63 -4 43
8 1. FC Köln 33 48 58 -10 32
9 SC Freiburg 33 47 56 -9 44
10 FC Augsburg 33 45 57 -12 43
11 FSV Mainz 05 33 42 53 -11 37
12 VfL Wolfsburg 33 42 68 -26 26
13 1. FC Heidenheim 33 41 70 -29 26
14 Union Berlin 33 40 58 -18 36
15 Hamburger SV 33 39 53 -14 37
16 Borussia Mönchengladbach 33 38 53 -15 35
17 Werder Bremen 33 37 58 -21 32
18 FC St. Pauli 33 28 57 -29 26
# EQUIPO PJ xG xGC +/- Pts
1 Bayern München 33 94.5 37.0 +57.5 86
2 Borussia Dortmund 33 60.5 38.5 +22.0 70
3 Bayer Leverkusen 33 60.9 43.0 +17.9 58
4 RB Leipzig 33 65.2 48.7 +16.5 65
5 VfB Stuttgart 33 59.0 47.2 +11.8 61
6 1899 Hoffenheim 33 53.4 50.0 +3.4 61
7 SC Freiburg 33 47.0 46.7 +0.3 44
8 1. FC Köln 33 50.0 52.1 -2.1 32
9 FSV Mainz 05 33 49.4 52.0 -2.6 37
10 Eintracht Frankfurt 33 42.8 49.0 -6.2 43
11 Borussia Mönchengladbach 33 41.3 50.8 -9.5 35
12 Union Berlin 33 41.7 51.7 -10.0 36
13 Werder Bremen 33 40.0 51.5 -11.5 32
14 FC Augsburg 33 44.7 59.4 -14.7 43
15 1. FC Heidenheim 33 44.9 59.9 -15.0 26
16 VfL Wolfsburg 33 43.6 60.3 -16.7 26
17 Hamburger SV 33 36.5 53.8 -17.3 37
18 FC St. Pauli 33 29.0 52.8 -23.8 26
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