Carl Zeiss Jena W vs FC Koln W Statistics & Analysis

Pre-match snapshot for this fixture.

• League: Frauen Bundesliga
• Fixture: Carl Zeiss Jena W vs FC Koln W
• Kickoff: 2026-05-17 12:00:00
• 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
• xG (showing): Carl Zeiss Jena W 1.45 — FC Koln W 1.25 (total xG ≈ 2.7)
• Primary / headline line (Betting Primary Pick when shown): Carl Zeiss Jena W
• Model: 41.8% · Implied: 12.5% · Probability edge: +29.3 pts · Est. EV: +15.5%
• BTTS (model): Yes 54.4% · No 45.6%
• Correct score (top bin): 1-2 (9.8%)

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.

The engine’s headline primary is: Carl Zeiss Jena W.

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.

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 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.

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.

• 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 19, 2026 (UTC)