SV Lafnitz vs Voitsberg Prediction, Odds & AI Betting Tips

May 15, 2026 - 17:00
1 1.45
3 1.25
xG Accuracy: 55%
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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 Under 2.5 Under 2.5 (0 goals) ✔ Correct
  • Both Teams To Score BTTS No No ✔ Correct
  • 1X2 SV Lafnitz Draw ✖ Incorrect
  • Correct Score Insights 1-2, 0-2, 1-1, 0-1, 1-3 0-0 ✖ Incorrect

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: Regionalliga - Mitte
  • Fixture: SV Lafnitz vs Voitsberg
  • Kickoff: 2026-05-15 17:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): SV Lafnitz 1.45 — Voitsberg 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 46.6% · Implied: 30.3% · Probability edge: +16.3 pts · Est. EV: +58.4%
  • BTTS (model): Yes 53.4% · No 46.6%
  • Correct score (top bin): 1-2 (9.8%)

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

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

Best Bet + Reason

The engine’s headline primary is: BTTS No.

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

Edges shrink quickly if prices move; always re-check the number on your book.

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.

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.

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.

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 23, 2026 (UTC)

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Back to Predictions
Regionalliga - Mitte Regionalliga - MitteStandings
# TEAM MP W D L PTS
1 Voitsberg 28 25 1 2 76
2 Gurten 28 18 4 6 58
3 Deutschlandsberger SC 28 14 8 6 50
4 Kalsdorf 28 15 4 9 49
5 Oedt 27 13 9 5 48
6 LASK Juniors 28 14 6 8 48
7 Velden 28 12 6 10 42
8 SV Lafnitz 28 11 6 11 39
9 Weiz 28 10 8 10 38
10 Wallern / Marienkirchen 27 11 4 12 37
11 Wolfsberger AC II 27 7 7 13 28
12 Wohnbau Dietach 27 8 4 15 28
13 Gleisdorf 09 28 6 9 13 27
14 Ried II 28 6 4 18 22
15 Treibach 28 6 3 19 21
16 St. Anna 28 2 5 21 11
# TEAM MP GS GC +/- PTS
1 Voitsberg 28 110 19 +91 76
2 LASK Juniors 28 63 41 +22 48
3 Weiz 28 60 64 -4 38
4 Deutschlandsberger SC 28 57 46 +11 50
5 Gurten 28 55 28 +27 58
6 Kalsdorf 28 54 45 +9 49
7 Oedt 27 52 28 +24 48
8 SV Lafnitz 28 50 56 -6 39
9 Velden 28 47 46 +1 42
10 Gleisdorf 09 28 42 70 -28 27
11 Wallern / Marienkirchen 27 40 42 -2 37
12 Ried II 28 39 70 -31 22
13 Wolfsberger AC II 27 33 40 -7 28
14 Treibach 28 31 66 -35 21
15 Wohnbau Dietach 27 28 49 -21 28
16 St. Anna 28 20 71 -51 11