Statistics / Football / Austria. Regionalliga - Mitte / St. Anna vs SV Lafnitz

St. Anna vs SV Lafnitz Statistics & Analysis

St. Anna St. Anna
May 22, 2026 - 17:00
2 1.45
0 1.25
xG Accuracy: 61%
SV Lafnitz SV Lafnitz
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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 St. Anna Draw ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-2, 0-2, 1-3 0-0 ✖ Incorrect

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: Regionalliga - Mitte
  • Fixture: St. Anna vs SV Lafnitz
  • Kickoff: 2026-05-23 17:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): St. Anna 1.45 — SV Lafnitz 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 73.9% · Implied: 39.2% · Probability edge: +34.7 pts · Est. EV: +74.4%
  • BTTS (model): Yes 26.1% · No 73.9%
  • Correct score (top bin): 1-1 (10.7%)

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

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.

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.

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.

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

June 06, 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 - Mitte Regionalliga - Mitte — Standings
# TEAM MP W D L PTS
1 Voitsberg 30 26 2 2 80
2 Gurten 30 20 4 6 64
3 Oedt 30 15 10 5 55
4 LASK Juniors 30 15 6 9 51
5 Deutschlandsberger SC 30 14 9 7 51
6 Kalsdorf 30 15 4 11 49
7 Velden 30 13 7 10 46
8 SV Lafnitz 30 12 6 12 42
9 Wallern / Marienkirchen 30 12 4 14 40
10 Weiz 30 10 9 11 39
11 Wolfsberger AC II 30 9 7 14 34
12 Wohnbau Dietach 30 9 5 16 32
13 Gleisdorf 09 30 7 9 14 30
14 Treibach 30 7 3 20 24
15 Ried II 30 7 4 19 25
16 St. Anna 30 2 5 23 11
# TEAM MP GS GC +/- PTS
1 Voitsberg 30 113 21 +92 80
2 LASK Juniors 30 66 44 +22 51
3 Oedt 30 62 32 +30 55
4 Weiz 30 61 66 -5 39
5 Deutschlandsberger SC 30 60 52 +8 51
6 Gurten 30 59 28 +31 64
7 Kalsdorf 30 59 53 +6 49
8 SV Lafnitz 30 55 60 -5 42
9 Velden 30 50 47 +3 46
10 Wolfsberger AC II 30 45 46 -1 34
11 Wallern / Marienkirchen 30 44 51 -7 40
12 Gleisdorf 09 30 43 72 -29 30
13 Ried II 30 41 72 -31 25
14 Treibach 30 35 71 -36 24
15 Wohnbau Dietach 30 33 57 -24 32
16 St. Anna 30 22 76 -54 11
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