Predictions / Football / Egypt. Second League / Tersana vs El Mansura

Prediction Audit: Tersana vs El Mansura Prediction, Odds & AI Betting Tips

Tersana Tersana
Sep 11, 2026 - 13:30
1 1.34
1 1.26
xG Accuracy: 85%
El Mansura El Mansura

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

The model had projected Tersana at 37.1%, 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 Tersana Draw ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 1-1 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Draw higher than the statistical model.

Largest probability gap: Draw -11.4 pp

Outcome Model Closing Market Difference Signal
Tersana 37.1% 34.0% +3.0 pp Aligned
Draw 29.6% 41.0% -11.4 pp Market Higher
El Mansura 33.3% 24.9% +8.4 pp Model Higher

The closing market estimates Draw's win probability at 41.0%, compared with the model's estimate of 29.6%, a difference of 11.4 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 Draw 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 Tersana; match finished Draw

Market lesson

The closing market differed from the model on Tersana by 11.4 percentage points (48.5% vs model 37.1%) — 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 11, 2026 · 13:29 UTC Forecast generated
    • Model 1X2 · Tersana 37.0% · Draw 29.6% · El Mansura 33.4%
    • xG · Tersana 1.34 — El Mansura 1.26
  2. Sep 11, 2026 · 13:00 UTC Opening odds snapshot PRE30
    • 1X2 odds · Tersana 2.69 · Draw 2.23 · El Mansura 3.67
    • Implied 1X2 · Tersana 34.0% · Draw 41.0% · El Mansura 24.9%
    • Bookmaker · Pinnacle
  3. Sep 11, 2026 · 13:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Tersana 2.69 · Draw 2.23 · El Mansura 3.67
    • Implied 1X2 · Tersana 34.0% · Draw 41.0% · El Mansura 24.9%
    • Bookmaker · Pinnacle
  4. Sep 11, 2026 · 13:30 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 57/100 · Moderate
  • Validation: Warning
  • Large market gap (11 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market has already priced much of the edge
  • Validation warning
Pricing proximity (inverse gap) 14/100
Monitoring Confidence 20/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 05, 2026 · 01:16 UTC Snapshot ID: dp-7024738

Closing Odds 2.23
AI Fair Odds —
CLV Pending
Final Result Draw · Tersana 1–1 El Mansura
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

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

  • League: Second League
  • Fixture: Tersana vs El Mansura
  • Kickoff: 2026-09-11 13:30:00
  • 1X2 (model): Home 37.0% · Draw 29.6% · Away 33.4%
  • xG (showing): Tersana 1.34 — El Mansura 1.26 (total xG ≈ 2.6)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Over 2.5 goals
  • Model: 48.2% · Implied: 30.3% · Probability edge: +17.9 pts · Est. EV: +57.1%
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

Totals and BTTS are evaluated against current market prices where available.

1X2 can look balanced even when side markets show clearer structure.

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 30, 2026 (UTC)

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Second League Second League — Standings
# TEAM MP W D L PTS
1 Masar 6 5 1 0 16
2 Maleyet Kafr El Zayiat 6 4 2 0 14
3 Kahraba Ismailia 6 4 1 1 13
4 Haras El Hodood 5 4 1 0 13
5 Pharco 6 4 1 1 13
6 AL Nasr SC 6 2 3 1 9
7 Itesalat 5 3 0 2 9
8 Tersana 5 2 2 1 8
9 El Mansura 6 2 2 2 8
10 Team 6 2 1 3 7
11 Tanta SC 5 2 1 2 7
12 El Seka El Hadid 6 2 1 3 7
13 El Entag EL Harby 5 1 3 1 6
14 El Dakhleya 6 1 3 2 6
15 Baladiyyat Al Mehalla 5 1 1 3 4
16 La Viena FC 5 0 3 2 3
17 Proxy 6 1 0 5 3
18 Mega Sport 5 0 2 3 2
19 Ismaily SC 5 0 2 3 2
20 Dayrout 5 0 0 5 0
# TEAM MP GS GC +/- PTS
1 Masar 6 13 3 +10 16
2 Kahraba Ismailia 6 11 4 +7 13
3 Maleyet Kafr El Zayiat 6 8 2 +6 14
4 Haras El Hodood 5 8 2 +6 13
5 Pharco 6 8 5 +3 13
6 AL Nasr SC 6 7 4 +3 9
7 Itesalat 5 7 5 +2 9
8 El Entag EL Harby 5 7 5 +2 6
9 El Mansura 6 6 7 -1 8
10 Team 6 6 7 -1 7
11 El Seka El Hadid 6 6 9 -3 7
12 Tersana 5 4 4 0 8
13 Tanta SC 5 4 5 -1 7
14 Ismaily SC 5 4 9 -5 2
15 Baladiyyat Al Mehalla 5 3 5 -2 4
16 La Viena FC 5 3 5 -2 3
17 El Dakhleya 6 3 6 -3 6
18 Mega Sport 5 3 6 -3 2
19 Proxy 6 2 7 -5 3
20 Dayrout 5 0 13 -13 0
Second League Egypt. Second League Predictions