Statistics / Football / Austria. Regionalliga - Mitte / Wolfsberger AC II vs Wohnbau Dietach

Wolfsberger AC II vs Wohnbau Dietach Statistics & Analysis

May 23, 2026 - 14:00
6 1.45
1 1.25
xG Accuracy: 27%
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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 Over 2.5 (7 goals) ✖ Incorrect
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Wolfsberger AC II Wolfsberger AC II ✔ Correct
  • Correct Score Insights 1-0, 1-1, 0-0, 0-1, 2-0 6-1 ✖ Incorrect

AI match briefing

AI Match Summary

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

  • League: Regionalliga - Mitte
  • Fixture: Wolfsberger AC II vs Wohnbau Dietach
  • Kickoff: 2026-05-23 17:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): Wolfsberger AC II 1.45 — Wohnbau Dietach 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 71.2% · Implied: 42.4% · Probability edge: +28.8 pts · Est. EV: +55.9%
  • BTTS (model): Yes 28.8% · No 71.2%
  • Correct score (top bin): 1-0 (14.0%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

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

Best Bet + Reason

Primary angle highlighted on the page: BTTS No.

Model probability is compared to implied probability from odds to highlight a probability edge; EV uses the same model probability with the best decimal price tracked.

No pick is a guarantee; variance is especially large in scoreline markets.

FAQ

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.

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.

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.

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 - MitteStandings
# 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