Predictions / Football / France. Ligue 1 / Nice vs Le Mans

Prediction Audit: Nice vs Le Mans Prediction, Odds & AI Betting Tips

Sep 05, 2026 - 18:45
1 1.38
1 1.50
xG Accuracy: 78%

The model missed the final outcome (Draw 1–1).

The model had projected Nice at 39.4%, 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 Over 2.5 Under 2.5 (2 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Nice Draw ✖ Incorrect
  • Correct Score Insights 1-1, 1-2, 0-1, 2-1, 1-0 1-1 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Nice higher than the statistical model.

Largest probability gap: Nice -15.3 pp

Outcome Model Closing Market Difference Signal
Nice 39.4% 54.6% -15.3 pp Market Higher
Draw 27.7% 24.7% +3.0 pp Aligned
Le Mans 33.0% 20.7% +12.3 pp Model Edge

The closing market estimates Nice's win probability at 54.6%, compared with the model's estimate of 39.4%, a difference of 15.3 percentage points. This highlights a disagreement between the model and market consensus, without 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 Draw 1–1.

Market Assessment

The market is materially more optimistic about Nice than the current fair estimate.

  • Investors may be incorporating information not fully reflected in the baseline model.
  • Tournament-specific context can shift market pricing.

Post Match Insights

What worked

  • Both Teams To Score (Yes) matched the full-time result
  • Exact score 1–1 fell within the model's highlighted bins

What failed

  • Over / Under 2.5: model leaned Over 2.5; match finished Under 2.5 (2 goals)
  • 1X2: model leaned Nice; match finished Draw

Market lesson

The closing market differed from the model on Nice by 15.3 percentage points (54.7% vs model 39.4%) — 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. Sep 05, 2026 · 19:56 UTC Forecast generated
    • Model 1X2 · Nice 39.3% · Draw 27.7% · Le Mans 33.0%
    • xG · Nice 1.38 — Le Mans 1.50
  2. Sep 05, 2026 · 18:14 UTC Opening odds snapshot PRE30
    • 1X2 odds · Nice 1.78 · Draw 3.94 · Le Mans 4.70
    • Implied 1X2 · Nice 54.6% · Draw 24.7% · Le Mans 20.7%
    • Bookmaker · Pinnacle
  3. Sep 05, 2026 · 18:44 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Nice 1.78 · Draw 3.94 · Le Mans 4.70
    • Implied 1X2 · Nice 54.6% · Draw 24.7% · Le Mans 20.7%
    • Bookmaker · Pinnacle
  4. Sep 05, 2026 · 18:45 UTC Kickoff
  5. FT Full-time result Draw · 1–1
  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 55/100 · Moderate
  • Validation: Warning
  • Large market gap (15 pp)
Evidence
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 23/100
Betting Confidence 44/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 30, 2026 · 04:14 UTC Snapshot ID: dp-6167968

Closing Odds 1.78
AI Fair Odds
CLV Pending
Final Result Draw · Nice 1–1 Le Mans
Prediction ✖ Missed
Decision Grade F

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

Pre-match snapshot for this fixture.

  • League: Ligue 1
  • Fixture: Nice vs Le Mans
  • Kickoff: 2026-09-05 18:45:00
  • 1X2 (model): Home 39.3% · Draw 27.7% · Away 33.0%
  • xG (showing): Nice 1.38 — Le Mans 1.5 (total xG ≈ 2.88)
  • Value headline: At least one tracked line reaches the headline EV threshold — align with the hero / Primary card if shown.
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Over 2.5 (Under 2.5 45.1% · Over 2.5 54.9%); BTTS Yes (Yes 59.7% · No 40.4%) Value lean (pricing): O/U 2.5 Over 2.5; BTTS Yes
  • BTTS (model): Yes 59.7% · No 40.4%
  • Correct score (top bin): 1-1 (11.6%)

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.

Prefer skipping to over-staking when the engine is honest about missing edge.

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

September 16, 2026 (UTC)

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Ligue 1 Ligue 1Standings
# TEAM MP W D L PTS
1 Monaco 4 3 1 0 10
2 Rennes 4 3 1 0 10
3 Lyon 4 2 2 0 8
4 Paris FC 4 2 2 0 8
5 Lille 3 2 1 0 7
6 Strasbourg 4 2 1 1 7
7 Stade Brestois 29 3 1 2 0 5
8 Lorient 4 1 2 1 5
9 Angers 4 1 1 2 4
10 Estac Troyes 3 1 1 1 4
11 Lens 3 1 0 2 3
12 Marseille 4 1 0 3 3
13 Auxerre 4 1 0 3 3
14 Paris Saint Germain 3 0 2 1 2
15 Le Mans 3 0 2 1 2
16 Le Havre 4 0 2 2 2
17 Toulouse 4 0 2 2 2
18 Nice 4 0 2 2 2
# TEAM MP GS GC +/- PTS
1 Strasbourg 4 9 8 +1 7
2 Rennes 4 8 5 +3 10
3 Monaco 4 6 2 +4 10
4 Lyon 4 6 2 +4 8
5 Paris FC 4 6 2 +4 8
6 Stade Brestois 29 3 6 5 +1 5
7 Lens 3 6 5 +1 3
8 Marseille 4 6 6 0 3
9 Lille 3 5 2 +3 7
10 Paris Saint Germain 3 5 6 -1 2
11 Le Mans 3 5 6 -1 2
12 Auxerre 4 5 11 -6 3
13 Lorient 4 4 4 0 5
14 Angers 4 4 5 -1 4
15 Estac Troyes 3 4 7 -3 4
16 Toulouse 4 4 7 -3 2
17 Le Havre 4 2 4 -2 2
18 Nice 4 1 5 -4 2
# TEAM MP xG xGC +/- PTS
1 Lens 3 7.3 3.5 +3.8 3
2 Stade Brestois 29 3 4.4 1.8 +2.6 5
3 Paris FC 4 3.5 0.9 +2.6 8
4 Marseille 4 3.1 1.7 +1.4 3
5 Angers 4 3.6 2.5 +1.1 4
6 Monaco 4 2.9 1.8 +1.1 10
7 Paris Saint Germain 3 3.2 2.2 +1.0 2
8 Toulouse 4 3.8 2.9 +0.9 2
9 Estac Troyes 3 4.9 4.8 +0.1 4
10 Lorient 4 2.0 2.5 -0.5 5
11 Le Mans 3 3.7 4.3 -0.6 2
12 Lille 3 2.3 3.3 -1.0 7
13 Rennes 4 3.7 4.9 -1.2 10
14 Lyon 4 1.9 3.3 -1.4 8
15 Le Havre 4 1.3 3.1 -1.8 2
16 Nice 4 1.5 3.6 -2.1 2
17 Strasbourg 4 4.8 7.7 -2.9 7
18 Auxerre 4 3.1 6.1 -3.0 3