Wiener SC vs Oberwart Statistics & Analysis

Pre-match snapshot for this fixture.

• League: Regionalliga - Ost
• Fixture: Wiener SC vs Oberwart
• Kickoff: 2026-05-15 17:30:00
• 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
• xG (showing): Wiener SC 1.45 — Oberwart 1.25 (total xG ≈ 2.7)
• Primary / headline line (Betting Primary Pick when shown): BTTS No
• Model: 65.6% · Implied: 36.0% · Probability edge: +29.6 pts · Est. EV: +71.9%
• BTTS (model): Yes 34.4% · No 65.6%
• Correct score (top bin): 0-1 (13.5%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

Early match state can move realised goals away from pre-kick projections.

Primary pick from the decision engine: 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.

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.

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.

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.

• 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%).

• 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.

May 17, 2026 (UTC)