SSV Jahn Regensburg vs Hoffenheim II Statistics & Analysis

May 02, 2026 - 12:00

2 2.39

1 1.50

xG Accuracy: 78%

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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 Más de 2.5 Más de 2.5 (3 goals) ✔ Correct
Ambos Equipos Marcarán BTTS Sí Sí ✔ Correct
1X2 SSV Jahn Regensburg SSV Jahn Regensburg ✔ Correct
Perspectivas de marcador exacto 2-1 2-1 ✔ Correct

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: 3. Liga
Fixture: SSV Jahn Regensburg vs Hoffenheim II
Kickoff: 2026-05-02 12:00:00
1X2 (model): Home 56.4% · Draw 21.1% · Away 22.4%
xG (showing): SSV Jahn Regensburg 2.39 — Hoffenheim II 1.5 (total xG ≈ 3.89)
Primary / headline line (Betting Primary Pick when shown): Over 2.5 goals
Model: 74.5% · Implied: 64.8% · Probability edge: +9.7 pts · Est. EV: +8.0%
BTTS (model): Yes 71.5% · No 28.5%
Correct score (top bin): 2-1 (8.8%)

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

Correct score remains high-variance even when a line is most likely on paper.

Mejor apuesta y razones

Primary pick from the decision engine: Over 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

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.

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.

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.

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.

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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3. Liga — Clasificación

#	EQUIPO	PJ	G	E	P	Pts
1	VfL Osnabrück	38	24	8	6	80
2	Energie Cottbus	38	21	9	8	72
3	Rot-Weiß Essen	38	20	10	8	70
4	MSV Duisburg	38	19	11	8	68
5	Hansa Rostock	38	18	13	7	67
6	Verl	38	18	10	10	64
7	Alemannia Aachen	38	19	7	12	64
8	TSV 1860 München	38	15	11	12	56
9	SV Wehen	38	15	8	15	53
10	Waldhof Mannheim	38	15	7	16	52
11	FC Viktoria Köln	38	15	6	17	51
12	FC Ingolstadt 04	38	13	10	15	49
13	SSV Jahn Regensburg	38	14	7	17	49
14	Stuttgart II	38	13	7	18	46
15	FC Saarbrücken	38	10	14	14	44
16	Hoffenheim II	38	12	7	19	43
17	Havelse	38	9	8	21	35
18	Erzgebirge Aue	38	7	13	18	34
19	SSV Ulm 1846	38	9	6	23	33
20	FC Schweinfurt 05	38	5	6	27	21

#	EQUIPO	PJ	GF	GC	+/-	Pts
1	Verl	38	82	48	+34	64
2	Rot-Weiß Essen	38	78	66	+12	70
3	Alemannia Aachen	38	76	57	+19	64
4	Hansa Rostock	38	74	49	+25	67
5	Energie Cottbus	38	72	51	+21	72
6	VfL Osnabrück	38	66	34	+32	80
7	MSV Duisburg	38	66	49	+17	68
8	FC Ingolstadt 04	38	65	56	+9	49
9	Hoffenheim II	38	65	71	-6	43
10	Waldhof Mannheim	38	59	72	-13	52
11	Stuttgart II	38	57	69	-12	46
12	Havelse	38	57	89	-32	35
13	SV Wehen	38	54	52	+2	53
14	TSV 1860 München	38	54	53	+1	56
15	SSV Jahn Regensburg	38	54	58	-4	49
16	FC Viktoria Köln	38	51	53	-2	51
17	FC Saarbrücken	38	51	57	-6	44
18	Erzgebirge Aue	38	51	70	-19	34
19	SSV Ulm 1846	38	49	78	-29	33
20	FC Schweinfurt 05	38	38	87	-49	21

#	EQUIPO	PJ	xG	xGC	+/-	Pts
1	Hansa Rostock	38	49.0	35.6	+13.4	67
2	Energie Cottbus	38	46.5	33.7	+12.8	72
3	Verl	38	44.0	31.6	+12.4	64
4	VfL Osnabrück	38	41.6	30.4	+11.2	80
5	MSV Duisburg	38	37.4	29.2	+8.2	68
6	FC Ingolstadt 04	38	45.5	38.9	+6.6	49
7	TSV 1860 München	38	45.8	42.6	+3.2	56
8	Rot-Weiß Essen	38	41.9	38.8	+3.1	70
9	Waldhof Mannheim	38	38.3	35.4	+2.9	52
10	SV Wehen	38	36.8	35.3	+1.5	53
11	FC Saarbrücken	38	41.1	40.6	+0.5	44
12	SSV Jahn Regensburg	38	40.8	40.6	+0.2	49
13	FC Viktoria Köln	38	33.4	34.1	-0.7	51
14	Stuttgart II	38	37.1	41.0	-3.9	46
15	SSV Ulm 1846	38	37.4	42.3	-4.9	33
16	Alemannia Aachen	38	37.1	42.9	-5.8	64
17	Hoffenheim II	38	44.5	51.1	-6.6	43
18	Erzgebirge Aue	38	32.1	45.3	-13.2	34
19	Havelse	38	31.9	50.5	-18.6	35
20	FC Schweinfurt 05	38	32.9	55.1	-22.2	21