Predictions / Football / Kosovo. Superliga / Dukagjini vs Malisheva

Prediction Audit: Dukagjini vs Malisheva Prediction, Odds & AI Betting Tips

Sep 10, 2026 - 17:00
2 1.34
0 1.26
xG Accuracy: 59%

AI correctly predicted the Dukagjini win.

The match finished 2–0, validating the model's directional assessment.

Tracked markets vs full-time result

Prediction grade A

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

Model vs Closing Market

Moderate Disagreement

The model rates Dukagjini considerably stronger than the closing betting market.

Largest probability gap: Dukagjini +5.7 pp

Outcome Model Closing Market Difference Signal
Dukagjini 37.1% 31.4% +5.7 pp Model Higher
Draw 29.6% 29.8% -0.2 pp Aligned
Malisheva 33.3% 38.8% -5.5 pp Market Higher

The statistical model estimates Dukagjini's win probability at 37.1%, compared with the closing market's implied probability of 31.4%, a difference of 5.7 percentage points. This highlights a substantial disagreement between the model's assessment and the market consensus, rather than 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 (Dukagjini win 2–0).

Market Assessment

The fair estimate shows a modest edge over current market pricing on Dukagjini.

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

Post Match Insights

What worked

  • Both Teams To Score (No) matched the full-time result
  • Under 2.5 goals aligned with the xG profile

What failed

  • 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 Dukagjini more conservatively (31.4% vs model 37.1%, 5.7 pp), but the model's lean was validated (Dukagjini win 2–0).

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Prediction Timeline

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

  1. Sep 10, 2026 · 16:59 UTC Forecast generated
    • Model 1X2 · Dukagjini 37.0% · Draw 29.6% · Malisheva 33.4%
    • xG · Dukagjini 1.34 — Malisheva 1.26
  2. Sep 10, 2026 · 16:30 UTC Opening odds snapshot PRE30
    • 1X2 odds · Dukagjini 2.83 · Draw 2.98 · Malisheva 2.29
    • Implied 1X2 · Dukagjini 31.4% · Draw 29.8% · Malisheva 38.8%
    • Bookmaker · Pinnacle
  3. Sep 10, 2026 · 16:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Dukagjini 2.83 · Draw 2.98 · Malisheva 2.29
    • Implied 1X2 · Dukagjini 31.4% · Draw 29.8% · Malisheva 38.8%
    • Bookmaker · Pinnacle
  4. Sep 10, 2026 · 17:00 UTC Kickoff
  5. FT Full-time result Dukagjini win · 2–0
  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: Monitor
Historical Decision Monitor
Outcome Validated
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 24/100
Monitoring Confidence 34/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 04, 2026 · 01:41 UTC Snapshot ID: dp-6850472

Closing Odds 2.83
AI Fair Odds —
CLV Pending
Final Result Dukagjini win · Dukagjini 2–0 Malisheva
Prediction ✔ Correct
Decision Grade A

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: Superliga
  • Fixture: Dukagjini vs Malisheva
  • Kickoff: 2026-09-10 17:00:00
  • 1X2 (model): Home 37.0% · Draw 29.6% · Away 33.4%
  • xG (showing): Dukagjini 1.34 — Malisheva 1.26 (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: 49.1% · Probability edge: +2.7 pts · Est. EV: +11.4%
  • 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.

Early match state can move realised goals away from pre-kick projections.

Historical Recommendation

Historical Decision: Monitor

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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Superliga Superliga — Standings
# TEAM MP W D L PTS
1 Prishtina 6 6 0 0 18
2 Malisheva 7 5 1 1 16
3 Dukagjini 7 3 3 1 12
4 Drita 6 3 2 1 11
5 Gjilani 7 3 2 2 11
6 Ballkani 7 3 1 3 10
7 Drenica Skënderaj 7 2 3 2 9
8 Feronikeli 7 2 0 5 6
9 Llapi 7 1 0 6 3
10 Vushtrria 7 0 0 7 0
# TEAM MP GS GC +/- PTS
1 Malisheva 7 19 6 +13 16
2 Prishtina 6 18 4 +14 18
3 Gjilani 7 10 8 +2 11
4 Drenica Skënderaj 7 9 7 +2 9
5 Ballkani 7 9 8 +1 10
6 Dukagjini 7 8 5 +3 12
7 Drita 6 8 5 +3 11
8 Llapi 7 8 21 -13 3
9 Feronikeli 7 5 13 -8 6
10 Vushtrria 7 3 20 -17 0