Statistics / Football / Sweden. Damallsvenskan / Rosengård W vs Norrköping W

Rosengård W vs Norrköping W Statistics & Analysis

Jun 13, 2026 - 11:00
1 2.42
1 1.54
xG Accuracy: 58%
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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 Over 2.5 Under 2.5 (2 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Rosengård W Draw ✖ Incorrect
  • Correct Score Insights 2-1, 1-1, 3-1, 2-2, 2-0 1-1 ✔ Correct

AI match briefing

AI Match Summary

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

  • League: Damallsvenskan
  • Fixture: Rosengård W vs Norrköping W
  • Kickoff: 2026-06-13 11:00:00
  • 1X2 (model): Home 54.6% · Draw 21.8% · Away 23.6%
  • xG (showing): Rosengård W 2.42 — Norrköping W 1.54 (total xG ≈ 3.96)
  • Primary / headline line (Betting Primary Pick when shown): Over 2.5 goals
  • Model: 75.6% · Implied: 58.0% · Probability edge: +17.6 pts · Est. EV: +22.5%
  • BTTS (model): Yes 72.5% · No 27.5%
  • Correct score (top bin): 2-1 (8.6%)

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.

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

Best Bet + Reason

Primary pick from the decision engine: Over 2.5 goals.

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.

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.

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.

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.

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.

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 13, 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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