Predictions / Football / Australia. New South Wales NPL / UNSW vs St. George Saints

Prediction Audit: UNSW vs St. George Saints Prediction, Odds & AI Betting Tips

UNSW UNSW
Jun 13, 2026 - 05:00
1 1.40
4 1.20
xG Accuracy: 42%
St. George Saints St. George Saints

The model missed the final outcome (St. George Saints win 1–4).

The model had projected UNSW at 41.7%, 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 Under 2.5 Over 2.5 (5 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 UNSW St. George Saints ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 1-4 ✖ Incorrect

Model vs Closing Market

Moderate Disagreement

The closing market prices UNSW higher than the statistical model.

Largest probability gap: UNSW -5.7 pp

Outcome Model Closing Market Difference Signal
UNSW 41.7% 47.4% -5.7 pp Market Higher
Draw 28.9% 26.7% +2.1 pp Aligned
St. George Saints 29.5% 25.9% +3.6 pp Aligned

The closing market estimates UNSW's win probability at 47.4%, compared with the model's estimate of 41.7%, a difference of 5.7 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 St. George Saints win 1–4.

Market Assessment

The market and model broadly agree on UNSW. The remaining divergence may reflect differences in team-strength assumptions rather than a directional disagreement.

  • Monitor line movement before kickoff — not a betting recommendation.

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 5 goals materialised
  • Both Teams To Score (Yes) matched the full-time result

What failed

  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (5 goals)
  • 1X2: model leaned UNSW; match finished St. George Saints

Market lesson

The closing market differed from the model on UNSW by 5.7 percentage points (47.4% vs model 41.7%) — 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. Jun 13, 2026 · 18:28 UTC Forecast generated
    • Model 1X2 · UNSW 41.6% · Draw 28.9% · St. George Saints 29.5%
    • xG · UNSW 1.40 — St. George Saints 1.20
  2. Jun 13, 2026 · 04:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · UNSW 1.93 · Draw 3.42 · St. George Saints 3.53
    • Implied 1X2 · UNSW 47.4% · Draw 26.7% · St. George Saints 25.9%
    • Bookmaker · Pinnacle
  3. Jun 13, 2026 · 04:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · UNSW 1.93 · Draw 3.42 · St. George Saints 3.53
    • Implied 1X2 · UNSW 47.4% · Draw 26.7% · St. George Saints 25.9%
    • Bookmaker · Pinnacle
  4. Jun 13, 2026 · 05:00 UTC Kickoff
  5. FT Full-time result St. George Saints win · 1–4
  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: Observe
Historical Decision No Primary Bet
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 76/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Market Compatibility 71/100
Betting Confidence 79/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 26, 2026 · 17:41 UTC Snapshot ID: dp-1905433

Closing Odds 1.93
AI Fair Odds —
CLV Pending
Final Result St. George Saints win · UNSW 1–4 St. George Saints
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: New South Wales NPL
  • Fixture: UNSW vs St. George Saints
  • Kickoff: 2026-06-13 05:00:00
  • 1X2 (model): Home 45.0% · Draw 45.0% · Away 10.0%
  • xG (showing): UNSW 1.4 — St. George Saints 1.2 (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): See the Over/Under and BTTS cards for any directional lean text.
  • BTTS (model): Yes N/A · No N/A
  • Correct score (top bin): N/A

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

October 03, 2026 (UTC)

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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