Predictions / Football / Germany. Frauen Bundesliga / SC Freiburg W vs VfL Wolfsburg W

SC Freiburg W vs VfL Wolfsburg W Prediction, Odds & AI Betting Tips

May 09, 2026 - 12:00
2 1.45
4 1.25
xG Accuracy: 40%
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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 (6 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 SC Freiburg W VfL Wolfsburg W ✖ Incorrect
  • Correct Score Insights 1-2, 1-1, 2-2, 1-3, 2-1 2-4 ✖ Incorrect

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Frauen Bundesliga
  • Fixture: SC Freiburg W vs VfL Wolfsburg W
  • Kickoff: 2026-05-10 12:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): SC Freiburg W 1.45 — VfL Wolfsburg W 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS Yes
  • Model: 75.9% · Implied: 62.9% · Probability edge: +13.0 pts · Est. EV: +16.9%
  • BTTS (model): Yes 75.9% · No 24.1%
  • Correct score (top bin): 1-2 (8.7%)

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.

Correct score remains high-variance even when a line is most likely on paper.

Best Bet + Reason

The engine’s headline primary is: BTTS Yes.

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.

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.

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.

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

May 22, 2026 (UTC)

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Frauen Bundesliga Frauen BundesligaStandings
# TEAM MP W D L PTS
1 Bayern Munich W 26 24 2 0 74
2 VfL Wolfsburg W 26 18 4 4 58
3 Eintracht Frankfurt W 26 16 3 7 51
4 1899 Hoffenheim W 26 14 4 8 46
5 Bayer Leverkusen W 26 15 1 10 46
6 Werder Bremen W 26 12 7 7 43
7 FC Koln W 26 11 4 11 37
8 SC Freiburg W 26 10 4 12 34
9 Union Berlin W 26 8 6 12 30
10 RB Leipzig W 26 7 7 12 28
11 Nürnberg W 26 6 4 16 22
12 Hamburger SV W 26 4 6 16 18
13 SGS Essen W 26 3 7 16 16
14 Carl Zeiss Jena W 26 2 5 19 11
# TEAM MP GS GC +/- PTS
1 Bayern Munich W 26 90 9 +81 74
2 VfL Wolfsburg W 26 72 38 +34 58
3 Eintracht Frankfurt W 26 65 43 +22 51
4 1899 Hoffenheim W 26 48 30 +18 46
5 Bayer Leverkusen W 26 46 36 +10 46
6 SC Freiburg W 26 44 46 -2 34
7 Werder Bremen W 26 42 36 +6 43
8 Union Berlin W 26 42 51 -9 30
9 RB Leipzig W 26 39 48 -9 28
10 FC Koln W 26 36 37 -1 37
11 Nürnberg W 26 33 61 -28 22
12 Hamburger SV W 26 26 57 -31 18
13 SGS Essen W 26 22 63 -41 16
14 Carl Zeiss Jena W 26 22 72 -50 11