Statistics / Football / Sweden. Damallsvenskan / Piteå W vs Brommapojkarna W

Piteå W vs Brommapojkarna W Statistics & Analysis

Jun 13, 2026 - 10:30
1 2.67
2 1.47
xG Accuracy: 55%
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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 Over 2.5 (3 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Piteå W Brommapojkarna W ✖ Incorrect
  • Correct Score Insights 2-1, 3-1, 1-1, 2-2, 2-0 1-2 ✖ Incorrect

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Damallsvenskan
  • Fixture: Piteå W vs Brommapojkarna W
  • Kickoff: 2026-06-13 10:30:00
  • 1X2 (model): Home 60.9% · Draw 19.9% · Away 19.2%
  • xG (showing): Piteå W 2.67 — Brommapojkarna W 1.47 (total xG ≈ 4.14)
  • Primary / headline line (Betting Primary Pick when shown): Over 2.5 goals
  • Model: 78.2% · Implied: 57.7% · Probability edge: +20.5 pts · Est. EV: +29.0%
  • BTTS (model): Yes 72.5% · No 27.5%
  • Correct score (top bin): 2-1 (8.3%)

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

Primary angle highlighted on the page: Over 2.5 goals.

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 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.

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.

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.

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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