Prediction Audit: Valentine vs Kahibah Prediction, Odds & AI Betting Tips

Jul 12, 2026 - 03:00
3 1.26
2 1.34
xG Accuracy: 52%

AI correctly predicted the Valentine win.

The match finished 3–2, 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 Over 2.5 (5 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Valentine Valentine ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 3-2 ✖ Incorrect

Model vs Closing Market

Moderate Disagreement

The closing market prices Valentine higher than the statistical model.

Largest probability gap: Valentine -8.3 pp

Outcome Model Closing Market Difference Signal
Valentine 36.5% 44.9% -8.3 pp Market Higher
Draw 27.9% 23.4% +4.6 pp Aligned
Kahibah 35.5% 31.8% +3.7 pp Aligned

The closing market estimates Valentine's win probability at 44.9%, compared with the model's estimate of 36.5%, a difference of 8.3 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 (Valentine win 3–2).

Market Assessment

The market and model broadly agree on Valentine. 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)
  • Exact score: outside the model's top score bins

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Valentine higher (44.8% vs model 36.5%, 8.3 pp), but the model's lean was validated (Valentine win 3–2).

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Prediction Timeline

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

  1. Jul 12, 2026 · 19:21 UTC Forecast generated
    • Model 1X2 · Valentine 36.5% · Draw 28.0% · Kahibah 35.5%
    • xG · Valentine 1.26 — Kahibah 1.34
  2. Jul 12, 2026 · 02:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Valentine 2.02 · Draw 3.88 · Kahibah 2.85
    • Implied 1X2 · Valentine 44.9% · Draw 23.4% · Kahibah 31.8%
    • Bookmaker · Pinnacle
  3. Jul 12, 2026 · 02:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Valentine 2.02 · Draw 3.88 · Kahibah 2.85
    • Implied 1X2 · Valentine 44.9% · Draw 23.4% · Kahibah 31.8%
    • Bookmaker · Pinnacle
  4. Jul 12, 2026 · 03:00 UTC Kickoff
  5. FT Full-time result Valentine win · 3–2
  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: Observe
Historical Decision No Primary Bet
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 75/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Pricing proximity (inverse gap) 58/100
Betting Confidence 78/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 25, 2026 · 21:13 UTC Snapshot ID: dp-1765944

Closing Odds 2.02
AI Fair Odds —
CLV Pending
Final Result Valentine win · Valentine 3–2 Kahibah
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

Quick read on how the model reads this matchup.

  • League: Northern NSW NPL
  • Fixture: Valentine vs Kahibah
  • Kickoff: 2026-07-12 03:00:00
  • 1X2 (model): Home 10.0% · Draw 45.0% · Away 45.0%
  • xG (showing): Valentine 1.26 — Kahibah 1.34 (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

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: 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 30, 2026 (UTC)

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Back to Predictions
Northern NSW NPL Northern NSW NPL — Standings
# TEAM MP W D L PTS
1 Broadmeadow Magic 22 15 4 3 49
2 Maitland 22 13 3 6 42
3 Weston Bears 22 12 5 5 41
4 Edgeworth Eagles 22 11 6 5 39
5 Belmont Swansea 22 10 5 7 35
6 Cooks Hill United 22 9 6 7 33
7 Valentine 22 7 5 10 26
8 Lambton Jaffas 22 7 4 11 25
9 Adamstown Rosebuds 22 6 6 10 24
10 Hamilton Olympic 22 5 6 11 21
11 Kahibah 22 6 2 14 20
12 Charlestown City Blues 22 4 2 16 14
# TEAM MP GS GC +/- PTS
1 Broadmeadow Magic 22 59 23 +36 49
2 Weston Bears 22 48 33 +15 41
3 Belmont Swansea 22 47 44 +3 35
4 Cooks Hill United 22 43 36 +7 33
5 Edgeworth Eagles 22 41 31 +10 39
6 Maitland 22 40 32 +8 42
7 Hamilton Olympic 22 39 40 -1 21
8 Lambton Jaffas 22 38 33 +5 25
9 Kahibah 22 35 53 -18 20
10 Adamstown Rosebuds 22 34 45 -11 24
11 Charlestown City Blues 22 25 62 -37 14
12 Valentine 22 22 39 -17 26