Prediction Audit: Brann vs Universitatea Cluj Prediction, Odds & AI Betting Tips

Jul 30, 2026 - 17:00
3 1.36
1 1.24
xG Accuracy: 60%

AI correctly predicted the Brann win.

The match finished 3–1, 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 (4 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Brann Brann ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 3-1 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Brann higher than the statistical model.

Largest probability gap: Brann -31.2 pp

Outcome Model Closing Market Difference Signal
Brann 38.0% 69.2% -31.2 pp Market Higher
Draw 29.6% 18.4% +11.1 pp Model Edge
Universitatea Cluj 32.4% 12.3% +20.1 pp Model Edge

The closing market estimates Brann's win probability at 69.2%, compared with the model's estimate of 38.0%, a difference of 31.2 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 (Brann win 3–1).

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 4 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 (4 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 Brann higher (69.2% vs model 38.0%, 31.2 pp), but the model's lean was validated (Brann win 3–1).

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Prediction Timeline

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

  1. Jul 30, 2026 · 16:59 UTC Forecast generated
    • Model 1X2 · Brann 38.0% · Draw 29.6% · Universitatea Cluj 32.4%
    • xG · Brann 1.36 — Universitatea Cluj 1.24
  2. Jul 30, 2026 · 16:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Brann 1.34 · Draw 5.03 · Universitatea Cluj 7.54
    • Implied 1X2 · Brann 69.2% · Draw 18.4% · Universitatea Cluj 12.3%
    • Bookmaker · Pinnacle
  3. Jul 30, 2026 · 16:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Brann 1.34 · Draw 5.03 · Universitatea Cluj 7.54
    • Implied 1X2 · Brann 69.2% · Draw 18.4% · Universitatea Cluj 12.3%
    • Bookmaker · Pinnacle
  4. Jul 30, 2026 · 17:00 UTC Kickoff
  5. FT Full-time result Brann win · 3–1
  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 33/100 · Low
  • Validation: Fail
  • Large market gap (31 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market strongly disagrees on price
  • Validation failed
Pricing proximity (inverse gap) 0/100
Monitoring Confidence 9/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 24, 2026 · 01:26 UTC Snapshot ID: dp-1525707

Closing Odds 1.34
AI Fair Odds —
CLV Pending
Final Result Brann win · Brann 3–1 Universitatea Cluj
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

Model favours Brann; market prices Brann instead — inputs may be missing or stale.

  • Model: Brann 1.36 xG vs Universitatea Cluj 1.24 → Brann 38.0%
  • Market: Brann ~69.2% implied
  • Validation failed — do not treat 1X2 EV as actionable.

Do not act on 1X2 value until validation passes. Structural leans (O/U, BTTS) need separate odds review.

Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 54.4% · No 45.6%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes

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 30, 2026 (UTC)

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UEFA Europa Conference League UEFA Europa Conference League — Standings
# TEAM MP W D L PTS
1 Aarhus 0 0 0 0 0
2 Ajax 0 0 0 0 0
3 Atalanta 0 0 0 0 0
4 Borac Banja Luka 0 0 0 0 0
5 SC Braga 0 0 0 0 0
6 Brann 0 0 0 0 0
7 Brighton 0 0 0 0 0
8 FC Copenhagen 0 0 0 0 0
9 FK Crvena Zvezda 0 0 0 0 0
10 CSKA Sofia 0 0 0 0 0
11 Egnatia Rrogozhinë 0 0 0 0 0
12 SC Freiburg 0 0 0 0 0
13 Gent 0 0 0 0 0
14 Getafe 0 0 0 0 0
15 HNK Hajduk Split 0 0 0 0 0
16 Heart Of Midlothian 0 0 0 0 0
17 Saburtalo 0 0 0 0 0
18 Inter Club d'Escaldes 0 0 0 0 0
19 FK Jablonec 0 0 0 0 0
20 Kairat Almaty 0 0 0 0 0
21 Kauno Žalgiris 0 0 0 0 0
22 KuPS 0 0 0 0 0
23 Lincoln Red Imps FC 0 0 0 0 0
24 FC Lugano 0 0 0 0 0
25 FC Midtjylland 0 0 0 0 0
26 Mjallby AIF 0 0 0 0 0
27 Monaco 0 0 0 0 0
28 FC Nordsjaelland 0 0 0 0 0
29 Pafos 0 0 0 0 0
30 Panathinaikos 0 0 0 0 0
31 Riga 0 0 0 0 0
32 St. Truiden 0 0 0 0 0
33 FC Thun 0 0 0 0 0
34 Trabzonspor 0 0 0 0 0
35 Twente 0 0 0 0 0
36 Universitatea Craiova 0 0 0 0 0
# TEAM MP GS GC +/- PTS
1 Aarhus 0 0 0 0 0
2 Ajax 0 0 0 0 0
3 Atalanta 0 0 0 0 0
4 Borac Banja Luka 0 0 0 0 0
5 SC Braga 0 0 0 0 0
6 Brann 0 0 0 0 0
7 Brighton 0 0 0 0 0
8 FC Copenhagen 0 0 0 0 0
9 FK Crvena Zvezda 0 0 0 0 0
10 CSKA Sofia 0 0 0 0 0
11 Egnatia Rrogozhinë 0 0 0 0 0
12 SC Freiburg 0 0 0 0 0
13 Gent 0 0 0 0 0
14 Getafe 0 0 0 0 0
15 HNK Hajduk Split 0 0 0 0 0
16 Heart Of Midlothian 0 0 0 0 0
17 Saburtalo 0 0 0 0 0
18 Inter Club d'Escaldes 0 0 0 0 0
19 FK Jablonec 0 0 0 0 0
20 Kairat Almaty 0 0 0 0 0
21 Kauno Žalgiris 0 0 0 0 0
22 KuPS 0 0 0 0 0
23 Lincoln Red Imps FC 0 0 0 0 0
24 FC Lugano 0 0 0 0 0
25 FC Midtjylland 0 0 0 0 0
26 Mjallby AIF 0 0 0 0 0
27 Monaco 0 0 0 0 0
28 FC Nordsjaelland 0 0 0 0 0
29 Pafos 0 0 0 0 0
30 Panathinaikos 0 0 0 0 0
31 Riga 0 0 0 0 0
32 St. Truiden 0 0 0 0 0
33 FC Thun 0 0 0 0 0
34 Trabzonspor 0 0 0 0 0
35 Twente 0 0 0 0 0
36 Universitatea Craiova 0 0 0 0 0