Prediction Audit: Masar vs Dayrout Prediction, Odds & AI Betting Tips

Aug 28, 2026 - 13:30
4 1.32
0 1.28
xG Accuracy: 34%

AI correctly predicted the Masar win.

The match finished 4–0, validating the model's directional assessment.

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 (4 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Masar Masar ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 4-0 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Masar higher than the statistical model.

Largest probability gap: Masar -23.4 pp

Outcome Model Closing Market Difference Signal
Masar 36.1% 59.5% -23.4 pp Market Higher
Draw 29.6% 25.4% +4.2 pp Aligned
Dayrout 34.2% 15.1% +19.1 pp Model Edge

The closing market estimates Masar's win probability at 59.5%, compared with the model's estimate of 36.1%, a difference of 23.4 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 model's directional lean matched the result (Masar win 4–0).

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 4 goals materialised

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (4 goals)

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Masar higher (59.5% vs model 36.1%, 23.4 pp), but the model's lean was validated (Masar win 4–0).

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Prediction Timeline

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

  1. Aug 28, 2026 · 13:29 UTC Forecast generated
    • Model 1X2 · Masar 36.1% · Draw 29.7% · Dayrout 34.2%
    • xG · Masar 1.32 — Dayrout 1.28
  2. Aug 28, 2026 · 13:00 UTC Opening odds snapshot PRE30
    • 1X2 odds · Masar 1.54 · Draw 3.60 · Dayrout 6.06
    • Implied 1X2 · Masar 59.5% · Draw 25.4% · Dayrout 15.1%
    • Bookmaker · Pinnacle
  3. Aug 28, 2026 · 13:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Masar 1.54 · Draw 3.60 · Dayrout 6.06
    • Implied 1X2 · Masar 59.5% · Draw 25.4% · Dayrout 15.1%
    • Bookmaker · Pinnacle
  4. Aug 28, 2026 · 13:30 UTC Kickoff
  5. FT Full-time result Masar win · 4–0
  6. FT Prediction validated Directional lean matched full-time result
  7. Archived Prediction review

Historical Snapshot

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

Historical verdict: Cautious / Wait

Historical label: Originally displayed as "Wait for validation".

Historical Decision Wait
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 51/100 · Moderate
  • Validation: Warning
  • Large market gap (23 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 0/100
Betting Confidence 33/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 22, 2026 · 01:47 UTC Snapshot ID: dp-4919427

Closing Odds 1.54
AI Fair Odds —
CLV Pending
Final Result Masar win · Masar 4–0 Dayrout
Prediction ✔ Correct
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

Quick read on how the model reads this matchup.

  • League: Second League
  • Fixture: Masar vs Dayrout
  • Kickoff: 2026-08-28 13:30:00
  • 1X2 (model): Home 36.1% · Draw 29.7% · Away 34.2%
  • xG (showing): Masar 1.32 — Dayrout 1.28 (total xG ≈ 2.6)
  • 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 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%)

When book depth is thin or odds are missing, EV may be unavailable even though the model still prefers one side on totals or BTTS — wait for cleaner prices or skip.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

Historical Recommendation

Historical Decision: Wait

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 29, 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