Ferrymead Bays vs Eastern Suburbs Statistics & Analysis

Ferrymead Bays

Sep 26, 2026 - 03:30

0 1.34

0 1.26

xG Accuracy: 49%

Eastern Suburbs

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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 (0 goals) ✔ Correct
Both Teams To Score BTTS Yes No ✖ Incorrect
1X2 Ferrymead Bays Draw ✖ Incorrect
Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 0-0 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Sep 21, 2026 · 00:36 UTC Snapshot ID: dp-10076349

Closing Odds Pending

AI Fair Odds —

CLV Pending

Final Result Draw · Ferrymead Bays 0–0 Eastern Suburbs

Prediction ✖ Missed

Decision Grade F

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 League - National
Fixture: Ferrymead Bays vs Eastern Suburbs
Kickoff: 2026-09-26 03:30:00
1X2 (model): Home 37.0% · Draw 29.6% · Away 33.4%
xG (showing): Ferrymead Bays 1.34 — Eastern Suburbs 1.26 (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%)

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.

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

Historical Recommendation

Historical Decision: No Primary Bet

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 29, 2026 (UTC)

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