SV Elversberg vs SC Paderborn 07 Statistics & Analysis

May 03, 2026 - 11:30

5 1.59

1 1.13

xG Accuracy: 38%

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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 SV Elversberg SV Elversberg ✔ Correct
Perspectivas de marcador exacto 1-1 5-1 ✖ Incorrect

Informe IA del partido

Resumen del partido IA

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

League: 2. Bundesliga
Fixture: SV Elversberg vs SC Paderborn 07
Kickoff: 2026-05-02 11:30:00
1X2 (model): Home 46.5% · Draw 28.0% · Away 25.5%
xG (showing): SV Elversberg 1.59 — SC Paderborn 07 1.13 (total xG ≈ 2.72)
Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
Model: 48.9% · Implied: 34.6% · Probability edge: +14.2 pts · Est. EV: +38.4%
BTTS (model): Yes 55.4% · No 44.6%
Correct score (top bin): 1-1 (11.8%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

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

Mejor apuesta y razones

Primary pick from the decision engine: Under 2.5 goals.

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

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.

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.

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.

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