Statistics / Football / Germany. Regionalliga - Nord / SV Drochtersen/Assel vs SV Meppen

SV Drochtersen/Assel vs SV Meppen Statistics & Analysis

May 08, 2026 - 17:30
1 1.45
2 1.25
xG Accuracy: 72%
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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
  • Over / Under 2.5 Over 2.5 Over 2.5 (3 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 SV Drochtersen/Assel SV Meppen ✖ Incorrect
  • Correct Score Insights 1-2 1-2 ✔ Correct

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Regionalliga - Nord
  • Fixture: SV Drochtersen/Assel vs SV Meppen
  • Kickoff: 2026-05-10 13:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): SV Drochtersen/Assel 1.45 — SV Meppen 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS Yes
  • Model: 84.8% · Implied: 65.7% · Probability edge: +19.1 pts · Est. EV: +18.7%
  • BTTS (model): Yes 84.8% · No 15.2%
  • Correct score (top bin): 1-2 (8.2%)

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.

Best Bet + Reason

Primary pick from the decision engine: BTTS Yes.

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

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.

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.

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.

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.

Risk Factors

  • 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%).

Methodology

  • Inputs: Same structured facts bundle as the public prediction page (xG / Poisson snapshot, market EV where available, decision engine v2).
  • Compliance: Educational framing only; not personalised advice.

Last Updated

May 18, 2026 (UTC)

How to use this
  • Focus on the Primary line when you want one actionable idea.
  • Do not parlay many thin-edge picks together; edges do not add reliably.
  • Treat longshots as optional, high-stake-sizing plays only.

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Back to Statistics
Regionalliga - Nord Regionalliga - NordStandings
# TEAM MP W D L PTS
1 SV Meppen 34 26 5 3 83
2 SV Drochtersen/Assel 34 22 4 8 70
3 VfB Oldenburg 34 21 6 7 69
4 SSV Jeddeloh 34 19 7 8 64
5 Phönix Lübeck 34 16 8 10 56
6 Hannover 96 II 34 16 5 13 53
7 Bremer SV 34 14 10 10 52
8 Weiche Flensburg 34 14 7 13 49
9 Kickers Emden 34 14 9 11 51
10 Hamburger SV II 34 13 8 13 47
11 VfB Lübeck 34 12 9 13 45
12 Werder Bremen II 34 10 10 14 40
13 HSC Hannover 34 10 7 17 37
14 Schöningen 34 10 4 20 34
15 Eintracht Norderstedt 34 7 9 18 30
16 St. Pauli II 34 4 13 17 25
17 BW Lohne 34 5 8 21 23
18 Altona 93 34 6 5 23 23
# TEAM MP GS GC +/- PTS
1 SV Meppen 34 103 35 +68 83
2 VfB Oldenburg 34 87 45 +42 69
3 SV Drochtersen/Assel 34 83 48 +35 70
4 SSV Jeddeloh 34 81 50 +31 64
5 Weiche Flensburg 34 69 63 +6 49
6 Kickers Emden 34 64 54 +10 51
7 Hannover 96 II 34 63 49 +14 53
8 Hamburger SV II 34 57 50 +7 47
9 Werder Bremen II 34 57 71 -14 40
10 Schöningen 34 56 84 -28 34
11 VfB Lübeck 34 54 61 -7 45
12 Phönix Lübeck 34 53 43 +10 56
13 Bremer SV 34 52 41 +11 52
14 Eintracht Norderstedt 34 51 79 -28 30
15 HSC Hannover 34 49 84 -35 37
16 Altona 93 34 44 92 -48 23
17 St. Pauli II 34 38 72 -34 25
18 BW Lohne 34 38 78 -40 23