Prediction Audit: North Star vs Capalaba Prediction, Odds & AI Betting Tips

Jul 31, 2026 - 10:30
1 1.41
0 1.19
xG Accuracy: 64%

AI correctly predicted the North Star win.

The match finished 1–0, validating the model's directional assessment.

Tracked markets vs full-time result

Prediction grade B-

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

Model vs Closing Market

Strong Disagreement

The closing market prices North Star higher than the statistical model.

Largest probability gap: North Star -21.9 pp

Outcome Model Closing Market Difference Signal
North Star 40.4% 62.3% -21.9 pp Market Higher
Draw 29.4% 18.9% +10.5 pp Model Edge
Capalaba 30.1% 18.7% +11.4 pp Model Edge

The closing market estimates North Star's win probability at 62.3%, compared with the model's estimate of 40.4%, a difference of 21.9 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 (North Star win 1–0).

Post Match Insights

What worked

  • Under 2.5 goals aligned with the xG profile
  • Exact score 1–0 fell within the model's highlighted bins

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced North Star higher (62.3% vs model 40.4%, 21.9 pp), but the model's lean was validated (North Star win 1–0).

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Prediction Timeline

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

  1. Jul 31, 2026 · 10:29 UTC Forecast generated
    • Model 1X2 · North Star 40.5% · Draw 29.4% · Capalaba 30.1%
    • xG · North Star 1.41 — Capalaba 1.19
  2. Jul 31, 2026 · 10:01 UTC Opening odds snapshot PRE30
    • 1X2 odds · North Star 1.47 · Draw 4.84 · Capalaba 4.89
    • Implied 1X2 · North Star 62.3% · Draw 18.9% · Capalaba 18.7%
    • Bookmaker · Pinnacle
  3. Jul 31, 2026 · 10:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · North Star 1.47 · Draw 4.84 · Capalaba 4.89
    • Implied 1X2 · North Star 62.3% · Draw 18.9% · Capalaba 18.7%
    • Bookmaker · Pinnacle
  4. Jul 31, 2026 · 10:30 UTC Kickoff
  5. FT Full-time result North Star win · 1–0
  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 52/100 · Moderate
  • Validation: Warning
  • Large market gap (22 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: Jul 25, 2026 · 02:34 UTC Snapshot ID: dp-1669793

Closing Odds 1.47
AI Fair Odds —
CLV Pending
Final Result North Star win · North Star 1–0 Capalaba
Prediction ✔ Correct
Decision Grade B-

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: Queensland Premier League
  • Fixture: North Star vs Capalaba
  • Kickoff: 2026-07-31 10:30:00
  • 1X2 (model): Home 40.5% · Draw 29.4% · Away 30.1%
  • xG (showing): North Star 1.41 — Capalaba 1.19 (total xG ≈ 2.6)
  • Value headline: None (actionable) — best tracked EV is about +0.9%, still below the +2.0% minimum for a headline / default stake (no default bet).
  • 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 54.2% · No 45.8%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.2% · No 45.8%
  • Correct score (top bin): 1-1 (12.5%)

Saying “no value” on a snapshot is a feature, not a bug: it protects readers from forcing a play when the edge is not there.

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 28, 2026 (UTC)

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Queensland Premier League Queensland Premier League — Standings
# TEAM MP W D L PTS
1 Brisbane Strikers 22 17 3 2 54
2 Broadbeach United 22 16 4 2 52
3 SC Wanderers 22 10 7 5 37
4 Ipswich 22 10 5 7 35
5 Robina City 22 9 5 8 32
6 Caboolture 22 9 4 9 31
7 Redlands United 22 8 6 8 30
8 Holland Park Hawks 22 9 3 10 30
9 Logan Lightning 22 8 3 11 27
10 North Star 22 6 3 13 21
11 St George Willawong 22 4 1 17 13
12 Capalaba 22 3 2 17 11
# TEAM MP GS GC +/- PTS
1 Brisbane Strikers 22 52 18 +34 54
2 Broadbeach United 22 51 20 +31 52
3 SC Wanderers 22 46 28 +18 37
4 Caboolture 22 45 38 +7 31
5 Redlands United 22 40 38 +2 30
6 Holland Park Hawks 22 40 48 -8 30
7 Logan Lightning 22 39 41 -2 27
8 Robina City 22 36 29 +7 32
9 Ipswich 22 35 30 +5 35
10 North Star 22 22 41 -19 21
11 Capalaba 22 21 57 -36 11
12 St George Willawong 22 13 52 -39 13