Lorient II vs Poitiers Prediction, Odds & AI Betting Tips

May 16, 2026 - 16:00
1 1.45
1 1.25
xG Accuracy: 82%
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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 Under 2.5 (2 goals) ✔ Correct
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Lorient II Draw ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 0-0 1-1 ✔ Correct

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: National 2 - Group A
  • Fixture: Lorient II vs Poitiers
  • Kickoff: 2026-05-16 16:00:00
  • 1X2 (model): Home 41.8% · Draw 25.7% · Away 32.6%
  • xG (showing): Lorient II 1.45 — Poitiers 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 59.6% · Implied: 45.9% · Probability edge: +13.7 pts · Est. EV: +23.4%
  • BTTS (model): Yes 40.4% · No 59.6%
  • Correct score (top bin): 1-1 (12.8%)

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 pick from the decision engine: BTTS No.

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.

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.

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.

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.

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 23, 2026 (UTC)

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Back to Predictions
National 2 - Group A National 2 - Group AStandings
# TEAM MP W D L PTS
1 La Roche VF 30 19 8 3 65
2 Bordeaux 30 19 5 6 62
3 Bayonne 30 17 4 9 55
4 Saint-Malo 30 13 11 6 50
5 Les Herbiers 30 14 7 9 49
6 Angoulême 30 11 10 9 43
7 Dinan Léhon 30 12 5 13 41
8 Avranches 30 10 10 10 40
9 Chauray 30 11 5 14 38
10 Saint-Colomban Locminé 30 9 10 11 37
11 Montlouis 30 7 10 13 31
12 Lorient II 30 9 5 16 31
13 Châteaubriant 30 8 6 16 30
14 Granville 30 6 11 13 29
15 Saumur 30 6 10 14 28
16 Poitiers 30 5 11 14 25
# TEAM MP GS GC +/- PTS
1 La Roche VF 30 61 27 +34 65
2 Bordeaux 30 51 28 +23 62
3 Avranches 30 46 41 +5 40
4 Les Herbiers 30 45 33 +12 49
5 Dinan Léhon 30 44 45 -1 41
6 Saint-Malo 30 43 29 +14 50
7 Bayonne 30 42 27 +15 55
8 Montlouis 30 42 50 -8 31
9 Lorient II 30 38 51 -13 31
10 Saumur 30 37 56 -19 28
11 Chauray 30 35 38 -3 38
12 Angoulême 30 33 36 -3 43
13 Granville 30 32 41 -9 29
14 Saint-Colomban Locminé 30 31 34 -3 37
15 Châteaubriant 30 25 47 -22 30
16 Poitiers 30 21 43 -22 25