Predictions / Football / France. National 1 / Le Puy Foot vs Dijon

Prediction Audit: Le Puy Foot vs Dijon Prediction, Odds & AI Betting Tips

May 09, 2026 - 17:30
1 1.45
2 1.25
xG Accuracy: 72%

The model missed the final outcome (Dijon win 1–2).

The model had projected Le Puy Foot at 41.8%, but the full-time result went the other way.

Tracked markets vs full-time result

Prediction grade F

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

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Over 2.5 (3 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 draw Dijon ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 0-0, 1-2 1-2 ✔ Correct

Model vs Closing Market

Strong Disagreement

The model rates Le Puy Foot considerably stronger than the closing betting market.

Largest probability gap: Le Puy Foot +17.8 pp

Outcome Model Closing Market Difference Signal
Le Puy Foot 41.8% 24.0% +17.8 pp Model Edge
Draw 25.7% 28.1% -2.4 pp Aligned
Dijon 32.6% 48.0% -15.4 pp Market Higher

The statistical model estimates Le Puy Foot's win probability at 41.8%, compared with the closing market's implied probability of 24.0%, a difference of 17.8 percentage points. This highlights a substantial disagreement between the model's assessment and the market consensus, rather than indicating which view is ultimately correct.

Model probabilities are generated from the statistical xG model using a Poisson distribution. Closing market probabilities are derived from consensus closing 1X2 odds after margin removal. Values represent implied probabilities rather than betting recommendations. Closing snapshot: PRE1.

After full time, the result was Dijon win 1–2.

Market Assessment

The statistical fair estimate is materially higher than the market on Le Puy Foot.

  • The model may see a slower-scoring or closer matchup than the market.
  • Monitor line movement before kickoff — not a betting recommendation.

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.70) — 3 goals materialised
  • Both Teams To Score (Yes) matched the full-time result
  • Exact score 1–2 fell within the model's highlighted bins

What failed

  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (3 goals)
  • 1X2: model leaned draw; match finished Dijon

Market lesson

The closing market differed from the model on Le Puy Foot by 17.8 percentage points (24.0% vs model 41.8%) — in this case the market view proved closer.

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Prediction Timeline

How this prediction moved from forecast to full-time review.

  1. May 08, 2026 · 17:29 UTC Forecast generated
    • Model 1X2 · Le Puy Foot 41.8% · Draw 25.7% · Dijon 32.6%
    • xG · Le Puy Foot 1.45 — Dijon 1.25
  2. May 08, 2026 · 16:59 UTC Opening odds snapshot PRE30
    • 1X2 odds · Le Puy Foot 3.90 · Draw 3.33 · Dijon 1.95
    • Implied 1X2 · Le Puy Foot 24.0% · Draw 28.1% · Dijon 48.0%
    • Bookmaker · Pinnacle
  3. May 08, 2026 · 17:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Le Puy Foot 3.90 · Draw 3.33 · Dijon 1.95
    • Implied 1X2 · Le Puy Foot 24.0% · Draw 28.1% · Dijon 48.0%
    • Bookmaker · Pinnacle
  4. May 09, 2026 · 17:30 UTC Kickoff
  5. FT Full-time result Dijon win · 1–2
  6. FT Prediction missed 1X2 lean did not match full-time result
  7. Archived Prediction review

Historical Snapshot

Frozen at kickoff — the model output as it stood before the match started.

Historical verdict: Monitor
Historical Decision Monitor
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 54/100 · Moderate
  • Validation: Warning
  • Large market gap (18 pp)
Evidence ★★★★★
  • Statistical edge detected
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 3/100
Monitoring Confidence 19/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 24, 2026 · 14:13 UTC Snapshot ID: dp-1604587

Closing Odds 3.9
AI Fair Odds 2.39
CLV Pending
Final Result Dijon win · Le Puy Foot 1–2 Dijon
Prediction ✖ Missed
Decision Grade F

Probability Calibration

  • Expected: 41.8%
  • Historical Bucket: 40–45% — Actual 0.0% (n=2)

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

Review FAQ

How accurate was the prediction?
This page grades directional markets (1X2, Over/Under 2.5, BTTS) against the full-time result. The prediction grade reflects how many of those tracked markets matched reality.
What does xG Accuracy measure?
xG Accuracy compares the model's pre-match expected-goals profile to the actual scoreline — not whether every market hit. A strong directional review can coexist with a moderate xG accuracy score.
Why wasn't the exact score predicted?
Correct-score outcomes are low-probability tails even when the model reads the match profile well. We highlight top score bins for context; missing the exact line does not invalidate a directional review.
Does this improve the AI record?
Each finished match is logged in our validation pipeline. Aggregated hit rates and CLV studies are published separately — this page is the per-match audit trail.

Predictions are for informational purposes only. Always gamble responsibly and within your limits. Past performance does not guarantee future results.

AI match briefing

AI Match Summary

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

  • League: National 1
  • Fixture: Le Puy Foot vs Dijon
  • Kickoff: 2026-05-08 17:30:00
  • 1X2 (model): Home 10.0% · Draw 45.0% · Away 45.0%
  • xG (showing): Le Puy Foot 1.45 — Dijon 1.25 (total xG ≈ 2.7)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 57.0% · Implied: 50.8% · Probability edge: +6.1 pts · Est. EV: +8.3%
  • BTTS (model): Yes 56.2% · No 43.8%
  • Correct score (top bin): 1-1 (12.9%)

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

Early match state can move realised goals away from pre-kick projections.

Historical Recommendation

Historical Decision: Monitor

Outcome: Missed — Pre-match 1X2 lean did not match 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

October 04, 2026 (UTC)

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Back to Predictions
National 1 National 1 — Standings
# 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