Statistics / Football / France. National 1 / Stade Briochin vs Quevilly

Stade Briochin vs Quevilly Statistics & Analysis

May 09, 2026 - 17:30
3 1.45
0 1.25
xG Accuracy: 46%
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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 No No ✔ Correct
  • 1X2 Stade Briochin Stade Briochin ✔ Correct
  • Correct Score Insights 1-1 3-0 ✖ Incorrect

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: National 1
  • Fixture: Stade Briochin vs Quevilly
  • Kickoff: 2026-05-08 17:30:00
  • 1X2 (model): Home 10.0% · Draw 45.0% · Away 45.0%
  • xG (showing): Stade Briochin 1.45 — Quevilly 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 55.7% · Implied: 46.7% · Probability edge: +9.0 pts · Est. EV: +17.0%
  • BTTS (model): Yes 44.3% · No 55.7%
  • Correct score (top bin): 1-1 (12.6%)

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

Primary pick from the decision engine: BTTS No.

We separate probability edge (model minus implied, in points of probability) from estimated EV (economic edge at the best price shown on the page).

Edges shrink quickly if prices move; always re-check the number on your book.

FAQ

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.

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.

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 17, 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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Back to Statistics
National 1 National 1Standings
# TEAM MP W D L PTS
1 Dijon 32 18 11 3 65
2 Sochaux 32 16 10 6 58
3 Rouen 32 14 13 5 55
4 Fleury 91 32 15 9 8 54
5 Versailles 32 15 8 9 53
6 Orleans 32 14 9 9 51
7 Le Puy Foot 32 12 11 9 47
8 Caen 32 8 16 8 40
9 Concarneau 32 8 14 10 38
10 Valenciennes 32 10 8 14 37
11 Aubagne 32 9 10 13 37
12 Villefranche 32 10 7 15 37
13 Quevilly 32 8 9 15 33
14 Gobelins 32 7 11 14 32
15 Bourg-en-bresse 01 32 8 7 17 31
16 Chateauroux 32 6 13 13 30
17 Stade Briochin 32 5 12 15 27
# TEAM MP GS GC +/- PTS
1 Dijon 32 52 25 +27 65
2 Sochaux 32 51 26 +25 58
3 Fleury 91 32 47 30 +17 54
4 Versailles 32 46 34 +12 53
5 Le Puy Foot 32 45 38 +7 47
6 Rouen 32 43 29 +14 55
7 Orleans 32 42 42 0 51
8 Caen 32 39 34 +5 40
9 Aubagne 32 38 46 -8 37
10 Valenciennes 32 35 44 -9 37
11 Chateauroux 32 35 49 -14 30
12 Stade Briochin 32 35 50 -15 27
13 Villefranche 32 34 45 -11 37
14 Quevilly 32 34 45 -11 33
15 Concarneau 32 32 37 -5 38
16 Gobelins 32 26 41 -15 32
17 Bourg-en-bresse 01 32 25 44 -19 31