Predictions / Football / France. Ligue 1 / Le Havre vs Marseille

Le Havre vs Marseille Prediction, Odds & AI Betting Tips

May 10, 2026 - 19:00
0 1.23
1 1.83
xG Accuracy: 57%
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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 (1 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Marseille Marseille ✔ Correct
  • Correct Score Insights 1-1, 1-2, 0-1, 0-2, 2-1 0-1 ✔ Correct

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Ligue 1
  • Fixture: Le Havre vs Marseille
  • Kickoff: 2026-05-09 19:00:00
  • 1X2 (model): Home 24.3% · Draw 25.7% · Away 50.0%
  • xG (showing): Le Havre 1.23 — Marseille 1.83 (total xG ≈ 3.06)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Over 2.5 goals
  • Model: 59.0% · Implied: 57.3% · Probability edge: +1.7 pts · Est. EV: +2.1%
  • BTTS (model): Yes 60.8% · No 39.2%
  • Correct score (top bin): 1-1 (10.6%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

1X2 can look balanced even when side markets show clearer structure.

Best Bet + Reason

Top tracked +EV leg right now (hero card, non-primary grading): 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.

No pick is a guarantee; variance is especially large in scoreline markets.

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.

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.

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.

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 21, 2026 (UTC)

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Ligue 1 Ligue 1Standings
# TEAM MP W D L PTS
1 Paris Saint Germain 34 24 4 6 76
2 Lens 34 22 4 8 70
3 Lille 34 18 7 9 61
4 Lyon 34 18 6 10 60
5 Marseille 34 18 5 11 59
6 Rennes 34 17 8 9 59
7 Monaco 34 16 6 12 54
8 Strasbourg 34 15 8 11 53
9 Lorient 34 11 12 11 45
10 Toulouse 33 12 8 13 44
11 Paris FC 34 11 11 12 44
12 Stade Brestois 29 34 10 9 15 39
13 Angers 34 9 9 16 36
14 Le Havre 34 7 14 13 35
15 Auxerre 34 8 10 16 34
16 Nice 34 7 11 16 32
17 Nantes 33 5 8 20 23
18 Metz 34 3 8 23 17
# TEAM MP GS GC +/- PTS
1 Paris Saint Germain 34 74 29 +45 76
2 Lens 34 66 35 +31 70
3 Marseille 34 63 45 +18 59
4 Monaco 34 60 54 +6 54
5 Rennes 34 59 50 +9 59
6 Strasbourg 34 58 47 +11 53
7 Lyon 34 53 40 +13 60
8 Lille 34 52 37 +15 61
9 Lorient 34 48 51 -3 45
10 Toulouse 33 47 46 +1 44
11 Paris FC 34 47 50 -3 44
12 Stade Brestois 29 34 43 55 -12 39
13 Nice 34 37 60 -23 32
14 Auxerre 34 34 44 -10 34
15 Le Havre 34 32 44 -12 35
16 Metz 34 32 76 -44 17
17 Angers 34 29 48 -19 36
18 Nantes 33 29 52 -23 23
# TEAM MP xG xGC +/- PTS
1 Paris Saint Germain 34 63.7 27.4 +36.3 76
2 Lens 34 66.7 42.7 +24.0 70
3 Marseille 34 60.2 42.1 +18.1 59
4 Lille 34 54.6 36.8 +17.8 61
5 Strasbourg 34 51.4 43.9 +7.5 53
6 Lyon 34 51.1 43.7 +7.4 60
7 Monaco 34 56.9 50.0 +6.9 54
8 Rennes 34 54.0 52.8 +1.2 59
9 Lorient 34 45.4 45.0 +0.4 45
10 Toulouse 33 42.9 42.6 +0.3 44
11 Stade Brestois 29 34 44.3 50.0 -5.7 39
12 Nantes 33 33.4 43.5 -10.1 23
13 Paris FC 34 44.4 56.1 -11.7 44
14 Le Havre 34 38.3 50.9 -12.6 35
15 Auxerre 34 35.5 48.1 -12.6 34
16 Nice 34 43.1 59.2 -16.1 32
17 Angers 34 32.4 55.4 -23.0 36
18 Metz 34 34.4 62.7 -28.3 17