Prediction Audit: Rana vs Skeid Prediction, Odds & AI Betting Tips

Aug 09, 2026 - 10:30
2 1.20
0 1.40
xG Accuracy: 55%

The model missed the final outcome (Rana win 2–0).

The model had projected Skeid at 39.9%, 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 Under 2.5 (2 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Skeid Rana ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 2-0 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Rana higher than the statistical model.

Largest probability gap: Rana -14.9 pp

Outcome Model Closing Market Difference Signal
Rana 30.6% 45.5% -14.9 pp Market Higher
Draw 29.5% 24.3% +5.1 pp Model Higher
Skeid 39.9% 30.2% +9.7 pp Model Higher

The closing market estimates Rana's win probability at 45.5%, compared with the model's estimate of 30.6%, a difference of 14.9 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 result was Rana win 2–0.

Market Assessment

The market is materially more optimistic about Rana than the current fair estimate.

  • Investors may be incorporating information not fully reflected in the baseline model.
  • Tournament-specific context can shift market pricing.

Post Match Insights

What worked

  • Under 2.5 goals aligned with the xG profile

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • 1X2: model leaned Skeid; match finished Rana

Market lesson

The closing market differed from the model on Skeid by 14.9 percentage points (54.8% vs model 39.9%) — 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. Aug 09, 2026 · 10:29 UTC Forecast generated
    • Model 1X2 · Rana 30.6% · Draw 29.5% · Skeid 40.0%
    • xG · Rana 1.20 — Skeid 1.40
  2. Aug 09, 2026 · 10:00 UTC Opening odds snapshot PRE30
    • 1X2 odds · Rana 2.04 · Draw 3.81 · Skeid 3.07
    • Implied 1X2 · Rana 45.5% · Draw 24.3% · Skeid 30.2%
    • Bookmaker · Pinnacle
  3. Aug 09, 2026 · 10:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Rana 2.04 · Draw 3.81 · Skeid 3.07
    • Implied 1X2 · Rana 45.5% · Draw 24.3% · Skeid 30.2%
    • Bookmaker · Pinnacle
  4. Aug 09, 2026 · 10:30 UTC Kickoff
  5. FT Full-time result Rana win · 2–0
  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 56/100 · Moderate
  • Validation: Warning
  • Large market gap (15 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market has already priced much of the edge
  • Validation warning
Pricing proximity (inverse gap) 8/100
Monitoring Confidence 19/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 04, 2026 · 00:54 UTC Snapshot ID: dp-2960848

Closing Odds 2.04
AI Fair Odds —
CLV Pending
Final Result Rana win · Rana 2–0 Skeid
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: 2. Division - Group 2
  • Fixture: Rana vs Skeid
  • Kickoff: 2026-08-09 10:30:00
  • 1X2 (model): Home 30.6% · Draw 29.5% · Away 40.0%
  • xG (showing): Rana 1.2 — Skeid 1.4 (total xG ≈ 2.6)
  • Value headline: None (actionable) — best tracked EV is about +0.4%, 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 54.3% · No 45.7%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.3% · No 45.7%
  • Correct score (top bin): 1-1 (12.5%)

The decision block shows no default Primary: Primary needs consensus EV ≥ +5.0% plus strength/reliability/calibration gates. A separate Lean/tracked gate is +2.0% (selective only). Lean labels are directional only — not bankroll-sized recommendations.

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 29, 2026 (UTC)

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Back to Predictions
2. Division - Group 2 2. Division - Group 2 — Standings
# TEAM MP W D L PTS
1 Eidsvold 20 15 3 2 48
2 Levanger 20 15 0 5 45
3 Kjelsås 21 14 2 5 44
4 Hønefoss 20 13 3 4 42
5 Grorud 20 11 4 5 37
6 Stjørdals-Blink 21 9 3 9 30
7 Lørenskog 20 9 3 8 30
8 Tromsdalen Uil 20 9 2 9 29
9 Junkeren 20 8 4 8 28
10 Rana 20 7 3 10 24
11 Skeid 20 5 2 13 17
12 Follo 21 3 5 13 14
13 Ull/Kisa 21 3 1 17 10
14 Trygg/Lade 20 2 3 15 9
# TEAM MP GS GC +/- PTS
1 Levanger 20 51 21 +30 45
2 Hønefoss 20 51 28 +23 42
3 Kjelsås 21 49 31 +18 44
4 Eidsvold 20 48 16 +32 48
5 Stjørdals-Blink 21 37 38 -1 30
6 Grorud 20 34 20 +14 37
7 Tromsdalen Uil 20 34 34 0 29
8 Rana 20 34 38 -4 24
9 Lørenskog 20 29 32 -3 30
10 Junkeren 20 29 33 -4 28
11 Skeid 20 27 43 -16 17
12 Follo 21 25 45 -20 14
13 Ull/Kisa 21 25 70 -45 10
14 Trygg/Lade 20 23 47 -24 9