Statistics / Football / France. National 1 / Bourg-en-bresse 01 vs Valenciennes

Bourg-en-bresse 01 vs Valenciennes Statistics & Analysis

May 09, 2026 - 17:30
1 1.45
0 1.25
xG Accuracy: 63%
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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 (1 goals) ✔ Correct
  • Both Teams To Score BTTS No No ✔ Correct
  • 1X2 Bourg-en-bresse 01 Bourg-en-bresse 01 ✔ Correct
  • Correct Score Insights 1-1 1-0 ✖ Incorrect

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: National 1
  • Fixture: Bourg-en-bresse 01 vs Valenciennes
  • Kickoff: 2026-05-08 17:30:00
  • 1X2 (model): Home 45.0% · Draw 45.0% · Away 10.0%
  • xG (showing): Bourg-en-bresse 01 1.45 — Valenciennes 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 58.0% · Implied: 48.8% · Probability edge: +9.2 pts · Est. EV: +11.9%
  • BTTS (model): Yes 42.0% · No 58.0%
  • Correct score (top bin): 1-1 (13.2%)

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

The engine’s headline primary is: 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).

When several markets sit near +EV, keep stakes small — correlation means edges do not add cleanly.

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.

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.

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 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