Statistics / Football / France. Feminine Division 1 / Lyon W vs Montpellier W

Lyon W vs Montpellier W Statistics & Analysis

May 06, 2026 - 15:00
3 1.45
1 1.25
xG Accuracy: 61%
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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 Under 2.5 Over 2.5 (4 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Lyon W Lyon W ✔ Correct
  • Correct Score Insights 2-0 3-1 ✖ Incorrect

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: Feminine Division 1
  • Fixture: Lyon W vs Montpellier W
  • Kickoff: 2026-05-06 15:00:00
  • 1X2 (model): Home 50.0% · Draw 50.0% · Away 0.0%
  • xG (showing): Lyon W 1.45 — Montpellier W 1.25 (total xG ≈ 2.7)
  • Value headline: At least one tracked line reaches the headline EV threshold — align with the hero / Primary card if shown.
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 29.4% · Over 2.5 70.6%); BTTS Yes (Yes 81.6% · No 18.4%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 81.6% · No 18.4%
  • Correct score (top bin): 2-0 (9.8%)

Saying “no value” on a snapshot is a feature, not a bug: it protects readers from forcing a play when the edge is not there.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

Best Bet + Reason

No bankroll-sized bet is implied here.

Treat this page as a read-only diagnostic: totals/BTTS structure can be informative even when the honest answer is to wait.

Re-check after material price moves; edges appear and disappear with liquidity.

FAQ

What do the grey “lean” labels mean then?

They summarise where the model tilts (e.g. Under 2.5 or BTTS No) without claiming a positive economic edge. Use them as context; size to zero unless you deliberately accept discretionary risk.

Why is there no “best bet” on this page?

The headline engine uses a minimum +EV threshold (e.g. 2%) for a default pick. A line can still show tiny +EV that fails that bar — we still call it no default bet so readers do not over-size thin edges.

Should I still read the 1X2 card?

Yes — it shows whether any winner price clears value. Here it often explains why there is no headline: probabilities can be clustered while prices already embed that uncertainty.

When would a headline +EV return?

When odds move enough that implied probabilities drop relative to the same model snapshot, or when more book prices arrive so EV can be computed reliably — then re-run the pipeline.

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 17, 2026 (UTC)

How to use this
  • When there is no Primary line, compare the +EV rows in the market cards below (not only 1X2).
  • 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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Back to Statistics
Feminine Division 1 Feminine Division 1Standings
# TEAM MP W D L PTS
1 Lyon W 22 19 3 0 60
2 Paris FC W 22 15 3 4 48
3 Paris Saint Germain W 22 15 2 5 47
4 Nantes W 22 12 5 5 41
5 FC Fleury 91 W 22 9 6 7 33
6 Dijon W 22 9 6 7 33
7 Strasbourg W 22 7 5 10 26
8 Le Havre W 22 5 6 11 21
9 Marseille W 22 5 4 13 19
10 Montpellier W 22 4 3 15 15
11 Lens W 22 4 3 15 15
12 Saint-Étienne W 22 3 4 15 13
# TEAM MP GS GC +/- PTS
1 Lyon W 22 76 11 +65 60
2 Paris Saint Germain W 22 48 26 +22 47
3 Paris FC W 22 46 16 +30 48
4 Nantes W 22 42 34 +8 41
5 Montpellier W 22 28 45 -17 15
6 FC Fleury 91 W 22 27 21 +6 33
7 Strasbourg W 22 26 38 -12 26
8 Marseille W 22 26 44 -18 19
9 Le Havre W 22 25 45 -20 21
10 Dijon W 22 21 28 -7 33
11 Lens W 22 20 50 -30 15
12 Saint-Étienne W 22 11 38 -27 13