Statistics / Football / Australia. New South Wales NPL / UNSW vs Sydney Olympic

UNSW vs Sydney Olympic Statistics & Analysis

UNSW UNSW
Aug 08, 2026 - 05:30
1 1.28
3 1.32
xG Accuracy: 58%
Sydney Olympic Sydney Olympic
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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 Over 2.5 (4 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Sydney Olympic Sydney Olympic ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-3 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Aug 02, 2026 · 00:53 UTC Snapshot ID: dp-2807228

Closing Odds 1.8
AI Fair Odds —
CLV +0.0%
Final Result Sydney Olympic win · UNSW 1–3 Sydney Olympic
Prediction ✔ Correct
Decision Grade B-

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

Market intelligence

Supporting read on how the prioritized closing feed moved versus the model — use after the Primary pick above.

Market briefing

Market remained largely stable before kickoff. No meaningful late implied-price shift was detected between PRE30 and PRE1 on the prioritized bookmaker snapshot.

Despite limited late movement, the model still prices Draw (1X2), Sydney Olympic (1X2), Under 2.5 goals, BTTS No meaningfully above what those closing snapshots implied — that gap is a static “model vs. price” read, not a late steam or chase story.

The model still exceeds closing implied on Under 2.5 goals by about 11.8 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market Model % Closing impl. % Gap (pp)
UNSW (1X2) 34.2 49.6 -15.4
Draw (1X2) 29.7 24.8 +4.8
Sydney Olympic (1X2) 36.1 25.5 +10.6
Over 2.5 goals 48.2 60.0 -11.8
Under 2.5 goals 51.8 40.0 +11.8
BTTS Yes 54.5 60.9 -6.4
BTTS No 45.5 39.1 +6.4
What this means

In plain terms: the model lands near 51.8% on Under 2.5 goals, while the closing snapshot implied about 40.0%. The difference — about 11.8 percentage points — is the largest model-vs.-market gap highlighted on this page.

Quick definitions: “closing implied” is the probability for that outcome implied by the final captured odds (after a simple de-vig). “Gap (pp)” is the model percentage minus that implied value, in percentage points (pp).

Closing-window line move

Single prioritized bookmaker per snapshot (not all books). Capture path: PRE30 → PRE1 · Book: Bet365

Column tags in parentheses: Closing uses the first available snapshot in PRE1→PRE5→PRE10→PRE30; Early uses the first available in PRE30→PRE10→PRE5 that is not the same capture as Closing.

Detailed capture odds are folded below — movement was negligible on de-vig implied prices.

View full line-by-line capture table
Market Early (PRE30) Closing (PRE1) Implied Δ (pp)
UNSW (1X2) 1.8 1.8 0.0
Draw (1X2) 3.6 3.6 0.0
Sydney Olympic (1X2) 3.5 3.5 0.0
Over 2.5 goals 1.57 1.57 0.0
Under 2.5 goals 2.35 2.35 0.0
BTTS Yes 1.53 1.53 0.0
BTTS No 2.38 2.38 0.0

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: New South Wales NPL
  • Fixture: UNSW vs Sydney Olympic
  • Kickoff: 2026-08-08 05:30:00
  • 1X2 (model): Home 34.2% · Draw 29.7% · Away 36.1%
  • xG (showing): UNSW 1.28 — Sydney Olympic 1.32 (total xG ≈ 2.6)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Under 2.5 goals
  • Model: 51.8% · Implied: 41.8% · Probability edge: +10.0 pts · Est. EV: +21.7%
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

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

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

Historical Recommendation

Historical Decision: No Primary Bet

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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Back to Statistics
New South Wales NPL New South Wales NPL — Standings
# TEAM MP W D L PTS
1 APIA Leichhardt Tigers 30 21 5 4 68
2 Sydney United 30 20 4 6 64
3 Marconi Stallions 30 19 5 6 62
4 Sutherland Sharks 30 14 4 12 46
5 Manly United 30 12 8 10 44
6 Rockdale City Suns 30 13 4 13 43
7 NWS Spirit 30 12 5 13 41
8 SD Raiders 30 12 5 13 41
9 Sydney II 30 11 8 11 41
10 Western Sydney W. II 30 11 5 14 38
11 Wollongong Wolves 30 11 5 14 38
12 St George City FA 30 10 7 13 37
13 Blacktown City 30 8 8 14 32
14 UNSW 30 9 5 16 32
15 St. George Saints 30 8 3 19 27
16 Sydney Olympic 30 6 5 19 23
# TEAM MP GS GC +/- PTS
1 APIA Leichhardt Tigers 30 66 35 +31 68
2 Western Sydney W. II 30 55 49 +6 38
3 Marconi Stallions 30 50 22 +28 62
4 Rockdale City Suns 30 48 42 +6 43
5 Sydney United 30 47 20 +27 64
6 Sutherland Sharks 30 46 38 +8 46
7 SD Raiders 30 44 49 -5 41
8 Blacktown City 30 41 48 -7 32
9 Manly United 30 39 35 +4 44
10 Sydney II 30 38 43 -5 41
11 UNSW 30 38 49 -11 32
12 NWS Spirit 30 37 38 -1 41
13 Wollongong Wolves 30 35 43 -8 38
14 Sydney Olympic 30 32 62 -30 23
15 St George City FA 30 30 46 -16 37
16 St. George Saints 30 28 55 -27 27