FC Schalke 04 vs Fortuna Düsseldorf Statistics & Analysis

May 02, 2026 - 18:30

1 1.96

0 0.83

xG Accuracy: 61%

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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 Menos de 2.5 (1 goals) ✔ Correct
Ambos Equipos Marcarán BTTS No No ✔ Correct
1X2 FC Schalke 04 FC Schalke 04 ✔ Correct
Perspectivas de marcador exacto 1-0 1-0 ✔ Correct

Informe IA del partido

Resumen del partido IA

Pre-match snapshot for this fixture.

League: 2. Bundesliga
Fixture: FC Schalke 04 vs Fortuna Düsseldorf
Kickoff: 2026-05-02 11:30:00
1X2 (model): Home 62.5% · Draw 23.6% · Away 13.8%
xG (showing): FC Schalke 04 1.96 — Fortuna Düsseldorf 0.83 (total xG ≈ 2.79)
Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
Model: 47.2% · Implied: 39.2% · Probability edge: +8.0 pts · Est. EV: +18.5%
BTTS (model): Yes 49.8% · No 50.2%
Correct score (top bin): 1-0 (12.0%)

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

1X2 can look balanced even when side markets show clearer structure.

Mejor apuesta y razones

Primary angle highlighted on the page: Under 2.5 goals.

We separate probability edge (model minus implied, in points of probability) from estimated EV (economic edge at the best price shown on the page).

When several markets sit near +EV, keep stakes small — correlation means edges do not add cleanly.

FAQ

What changes first if odds move?

Implied probabilities and EV move immediately with price; model probabilities in this snapshot do not update until the pipeline is re-run. Refresh after material line moves.

Is the most likely correct score a good bet?

Usually no as a standalone bet: the “most likely” scoreline is still a low absolute probability tail event (often single digits, sometimes low teens). Use it as context; keep any correct-score stake in the “fun / small” bucket.

Safer market than correct score?

Markets with more liquidity and smoother prices (often 1X2 or O/U 2.5 from many books) are usually easier to reason about than long-tail correct-score prices; still read EV on each leg.

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.

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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2. Bundesliga — Clasificación

#	EQUIPO	PJ	G	E	P	Pts
1	FC Schalke 04	33	20	7	6	67
2	SV Elversberg	33	17	8	8	59
3	Hannover 96	33	16	11	6	59
4	SC Paderborn 07	33	17	8	8	59
5	SV Darmstadt 98	33	13	13	7	52
6	Hertha BSC	33	14	9	10	51
7	1. FC Kaiserslautern	33	15	4	14	49
8	1. FC Nürnberg	33	12	9	12	45
9	Karlsruher SC	33	12	8	13	44
10	VfL Bochum	33	10	11	12	41
11	Holstein Kiel	33	11	8	14	41
12	1. FC Magdeburg	33	12	3	18	39
13	Dynamo Dresden	33	10	8	15	38
14	Eintracht Braunschweig	33	10	7	16	37
15	Fortuna Düsseldorf	33	11	4	18	37
16	Arminia Bielefeld	33	9	9	15	36
17	SpVgg Greuther Fürth	33	9	7	17	34
18	Preußen Münster	33	6	12	15	30

#	EQUIPO	PJ	GF	GC	+/-	Pts
1	SV Elversberg	33	61	39	+22	59
2	Hannover 96	33	57	41	+16	59
3	SV Darmstadt 98	33	57	43	+14	52
4	SC Paderborn 07	33	57	45	+12	59
5	Dynamo Dresden	33	52	52	0	38
6	1. FC Magdeburg	33	52	57	-5	39
7	Karlsruher SC	33	52	62	-10	44
8	1. FC Kaiserslautern	33	51	47	+4	49
9	FC Schalke 04	33	49	31	+18	67
10	VfL Bochum	33	47	46	+1	41
11	Arminia Bielefeld	33	47	50	-3	36
12	Hertha BSC	33	46	38	+8	51
13	SpVgg Greuther Fürth	33	46	68	-22	34
14	1. FC Nürnberg	33	44	42	+2	45
15	Holstein Kiel	33	43	46	-3	41
16	Preußen Münster	33	38	58	-20	30
17	Eintracht Braunschweig	33	36	53	-17	37
18	Fortuna Düsseldorf	33	33	50	-17	37

#	EQUIPO	PJ	xG	xGC	+/-	Pts
1	SC Paderborn 07	33	56.3	36.5	+19.8	59
2	FC Schalke 04	33	49.1	30.0	+19.1	67
3	Hannover 96	33	52.2	36.8	+15.4	59
4	SV Elversberg	33	49.5	37.0	+12.5	59
5	1. FC Magdeburg	33	51.5	44.5	+7.0	39
6	VfL Bochum	33	50.7	45.7	+5.0	41
7	1. FC Nürnberg	33	44.6	41.1	+3.5	45
8	1. FC Kaiserslautern	33	44.9	43.0	+1.9	49
9	SV Darmstadt 98	33	50.5	50.0	+0.5	52
10	Arminia Bielefeld	33	45.2	44.8	+0.4	36
11	Dynamo Dresden	33	42.4	42.9	-0.5	38
12	Hertha BSC	33	43.4	46.3	-2.9	51
13	Fortuna Düsseldorf	33	39.6	47.4	-7.8	37
14	Eintracht Braunschweig	33	36.4	46.3	-9.9	37
15	Holstein Kiel	33	40.0	52.2	-12.2	41
16	SpVgg Greuther Fürth	33	37.4	50.6	-13.2	34
17	Preußen Münster	33	36.4	53.8	-17.4	30
18	Karlsruher SC	33	39.5	60.6	-21.1	44