Statistics / Football / France. National 2 - Group A / Colmar vs Biesheim

Colmar vs Biesheim Statistics & Analysis

Colmar Colmar
Aug 29, 2026 - 16:00
1 1.32
0 1.28
xG Accuracy: 64%
Biesheim Biesheim
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Tracked markets vs full-time result

Each row compares the pre-match model lean to the full-time result.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Under 2.5 (1 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Colmar Colmar ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 1-0 ✔ Correct

Validation Report

Immutable Snapshot

Prediction Time: Aug 23, 2026 · 04:22 UTC Snapshot ID: dp-5155493

Closing Odds Pending
AI Fair Odds —
CLV Pending
Final Result Colmar win · Colmar 1–0 Biesheim
Prediction ✔ Correct
Decision Grade B-

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

AI match briefing

AI Match Summary

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

  • League: National 2 - Group A
  • Fixture: Colmar vs Biesheim
  • Kickoff: 2026-08-29 16:00:00
  • 1X2 (model): Home 36.1% · Draw 29.7% · Away 34.2%
  • xG (showing): Colmar 1.32 — Biesheim 1.28 (total xG ≈ 2.6)
  • Value headline: None — no positive EV could be estimated on tracked lines at current best prices (missing odds or thin book depth).
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 54.5% · No 45.5%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

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.

Historical Recommendation

Historical Decision: No Primary Bet

Outcome: Validated — Pre-match lean validated against the full-time result.

Risk Factors Considered Before Kickoff

  • 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%).

Last Updated

September 25, 2026 (UTC)

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Back to Statistics
National 2 - Group A National 2 - Group A — Standings
# TEAM MP W D L PTS
1 Chambly Thelle FC 5 4 0 1 12
2 Furiani-Agliani 5 3 2 0 11
3 St Maur Lusitanos 5 3 2 0 11
4 Racing Colombes 92 5 3 1 1 10
5 Dieppe 5 2 3 0 9
6 Feignies-Aulnoye 5 2 3 0 9
7 Creteil 5 2 2 1 8
8 Haguenau 5 2 0 3 6
9 Colmar 5 1 2 2 5
10 Epinal 5 1 2 2 5
11 Bastia-Borgo 5 1 2 2 5
12 Biesheim 5 1 2 2 5
13 St-Pryvé St-Hilaire 5 0 3 2 3
14 Montlouis 5 0 3 2 3
15 Le Pays du Valois 5 0 2 3 2
16 Chantilly 5 0 1 4 1
# TEAM MP GS GC +/- PTS
1 Chambly Thelle FC 5 10 4 +6 12
2 Furiani-Agliani 5 9 3 +6 11
3 Racing Colombes 92 5 9 5 +4 10
4 St Maur Lusitanos 5 7 4 +3 11
5 Biesheim 5 7 7 0 5
6 Dieppe 5 6 3 +3 9
7 Le Pays du Valois 5 6 10 -4 2
8 Feignies-Aulnoye 5 5 3 +2 9
9 Creteil 5 5 3 +2 8
10 Haguenau 5 5 4 +1 6
11 Epinal 5 5 5 0 5
12 Bastia-Borgo 5 5 7 -2 5
13 St-Pryvé St-Hilaire 5 5 7 -2 3
14 Montlouis 5 5 9 -4 3
15 Colmar 5 4 8 -4 5
16 Chantilly 5 4 15 -11 1