Predictions / Football / Indonesia. Liga 1 / PSS Sleman vs Persepam Madura Utd

Prediction Audit: PSS Sleman vs Persepam Madura Utd Prediction, Odds & AI Betting Tips

PSS Sleman PSS Sleman
Sep 12, 2026 - 08:30
1 1.33
3 1.27
xG Accuracy: 57%
Persepam Madura Utd Persepam Madura Utd

The model missed the final outcome (Persepam Madura Utd win 1–3).

The model had projected PSS Sleman at 36.6%, 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 (4 goals) ✖ Incorrect
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 PSS Sleman Persepam Madura Utd ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 1-3 ✖ Incorrect

Model vs Closing Market

Broadly Aligned

The model and closing market are broadly aligned.

Largest probability gap: Persepam Madura Utd -3.4 pp

Outcome Model Closing Market Difference Signal
PSS Sleman 36.6% 35.8% +0.8 pp Aligned
Draw 29.6% 27.0% +2.6 pp Aligned
Persepam Madura Utd 33.8% 37.2% -3.4 pp Aligned

The model and closing market are broadly aligned, with probability differences below 5 percentage points.

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 Persepam Madura Utd win 1–3.

Market Assessment

The market and model are broadly aligned. Any small pricing gap likely reflects rounding or bookmaker margin, not a structural disagreement.

  • Current pricing remains close to the model baseline.

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 4 goals materialised

What failed

  • Both Teams To Score: model leaned BTTS No; match finished BTTS Yes
  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (4 goals)

Market lesson

The full-time result was Persepam Madura Utd win 1–3, which did not match the model's pre-match lean on 1X2.

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Prediction Timeline

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

  1. Sep 12, 2026 · 08:29 UTC Forecast generated
    • Model 1X2 · PSS Sleman 36.6% · Draw 29.6% · Persepam Madura Utd 33.8%
    • xG · PSS Sleman 1.33 — Persepam Madura Utd 1.27
  2. Sep 12, 2026 · 08:01 UTC Opening odds snapshot PRE30
    • 1X2 odds · PSS Sleman 2.65 · Draw 3.51 · Persepam Madura Utd 2.55
    • Implied 1X2 · PSS Sleman 35.8% · Draw 27.0% · Persepam Madura Utd 37.2%
    • Bookmaker · Pinnacle
  3. Sep 12, 2026 · 08:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · PSS Sleman 2.65 · Draw 3.51 · Persepam Madura Utd 2.55
    • Implied 1X2 · PSS Sleman 35.8% · Draw 27.0% · Persepam Madura Utd 37.2%
    • Bookmaker · Pinnacle
  4. Sep 12, 2026 · 08:30 UTC Kickoff
  5. FT Full-time result Persepam Madura Utd win · 1–3
  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: Monitor
Historical Decision Monitor
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 77/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Market Compatibility 28/100
Monitoring Confidence 34/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 07, 2026 · 00:46 UTC Snapshot ID: dp-7418218

Closing Odds 2.55
AI Fair Odds —
CLV Pending
Final Result Persepam Madura Utd win · PSS Sleman 1–3 Persepam Madura Utd
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

Quick read on how the model reads this matchup.

  • League: Liga 1
  • Fixture: PSS Sleman vs Persepam Madura Utd
  • Kickoff: 2026-09-12 08:30:00
  • 1X2 (model): Home 36.6% · Draw 29.6% · Away 33.8%
  • xG (showing): PSS Sleman 1.33 — Persepam Madura Utd 1.27 (total xG ≈ 2.6)
  • Value headline: None (actionable) — best tracked EV is about +1.0%, 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 54.5% · No 45.5%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS No
  • 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: Monitor

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 30, 2026 (UTC)

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Liga 1 Liga 1 — Standings
# TEAM MP W D L PTS
1 Dewa United 4 3 1 0 10
2 Persepam Madura Utd 3 3 0 0 9
3 Persija 3 3 0 0 9
4 Bali United 3 2 0 1 6
5 Persib Bandung 3 2 0 1 6
6 Pusamania Borneo 4 2 0 2 6
7 Arema FC 3 1 2 0 5
8 Bhayangkara FC 3 1 2 0 5
9 Persita 3 1 2 0 5
10 Persebaya Surabaya 3 1 2 0 5
11 Persik Kediri 3 1 1 1 4
12 PSM Makassar 3 0 2 1 2
13 Garudayaksa 3 0 2 1 2
14 PSIM Yogyakarta 3 0 1 2 1
15 PSS Sleman 3 0 0 3 0
16 Persijap 3 0 0 3 0
17 Malut United 3 0 1 2 -1
18 Adhyaksa 3 0 0 3 -2
# TEAM MP GS GC +/- PTS
1 Dewa United 4 8 4 +4 10
2 Arema FC 3 8 4 +4 5
3 Persepam Madura Utd 3 7 2 +5 9
4 Bali United 3 6 3 +3 6
5 Persib Bandung 3 6 4 +2 6
6 Persita 3 6 5 +1 5
7 PSM Makassar 3 6 8 -2 2
8 Bhayangkara FC 3 5 3 +2 5
9 Persija 3 4 1 +3 9
10 Persebaya Surabaya 3 3 2 +1 5
11 Persik Kediri 3 3 2 +1 4
12 Pusamania Borneo 4 3 4 -1 6
13 Malut United 3 3 5 -2 -1
14 PSS Sleman 3 3 7 -4 0
15 Garudayaksa 3 2 4 -2 2
16 PSIM Yogyakarta 3 2 4 -2 1
17 Persijap 3 1 5 -4 0
18 Adhyaksa 3 1 10 -9 -2