Statistics / Football / Romania. Liga I / CFR 1907 Cluj vs Arges Pitesti

CFR 1907 Cluj vs Arges Pitesti Statistics & Analysis

CFR 1907 Cluj CFR 1907 Cluj
May 22, 2026 - 17:30
1 1.13
1 0.89
xG Accuracy: 94%
Arges Pitesti Arges Pitesti
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Tracked markets vs full-time result

Each row compares the model’s highlighted side (or lean) to what happened at full time.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Under 2.5 (2 goals) ✔ Correct
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 CFR 1907 Cluj Draw ✖ Incorrect
  • Correct Score Insights 1-0, 1-1, 0-0, 0-1, 2-0 1-1 ✔ Correct

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: Liga I
  • Fixture: CFR 1907 Cluj vs Arges Pitesti
  • Kickoff: 2026-05-23 15:00:00
  • 1X2 (model): Home 39.4% · Draw 33.8% · Away 26.8%
  • xG (showing): CFR 1907 Cluj 1.13 — Arges Pitesti 0.89 (total xG ≈ 2.02)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 67.1% · Implied: 56.2% · Probability edge: +10.9 pts · Est. EV: +14.1%
  • BTTS (model): Yes 41.6% · No 58.4%
  • Correct score (top bin): 1-0 (15.0%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

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

Best Bet + Reason

Primary angle highlighted on the page: Under 2.5 goals.

We separate probability edge (model minus implied, in points of probability) from estimated EV (economic edge at the best price shown on the page).

Edges shrink quickly if prices move; always re-check the number on your book.

FAQ

What changes first if odds move?

Implied probabilities and EV move immediately with price; model probabilities in this snapshot do not update until the pipeline is re-run. Refresh after material line moves.

What is the best-supported line in this snapshot?

Match the hero card above: if it says “Betting Primary Pick”, that leg cleared primary rules; if it says “Best +EV (tracked markets)”, it is the strongest +EV line that did not meet stricter Primary thresholds. The bullets below repeat the same model %, implied %, edge (pts), and EV % as that card.

Safer market than correct score?

Markets with more liquidity and smoother prices (often 1X2 or O/U 2.5 from many books) are usually easier to reason about than long-tail correct-score prices; still read EV on each leg.

How should I read EV versus a probability gap?

Probability edge = model probability minus implied probability (reported here in percentage points). EV ≈ model probability × best tracked decimal odds − 1, shown as return per unit stake. They are related but not interchangeable labels.

Risk Factors

  • 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%).

Methodology

  • Inputs: Same structured facts bundle as the public prediction page (xG / Poisson snapshot, market EV where available, decision engine v2).
  • Compliance: Educational framing only; not personalised advice.

Last Updated

June 08, 2026 (UTC)

How to use this
  • Focus on the Primary line when you want one actionable idea.
  • Do not parlay many thin-edge picks together; edges do not add reliably.
  • Treat longshots as optional, high-stake-sizing plays only.

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Back to Statistics
Liga I Liga I — Standings
# TEAM MP W D L PTS
1 Universitatea Craiova 10 6 2 2 50
2 Universitatea Cluj 10 6 1 3 46
3 CFR 1907 Cluj 10 4 4 2 43
4 Dinamo Bucuresti 10 3 4 3 39
5 Rapid 10 1 3 6 34
6 Arges Pitesti 10 1 4 5 32
7 FCSB 30 13 7 10 46
8 Uta Arad 30 11 10 9 43
9 FC Botosani 30 11 9 10 42
10 Oţelul 30 11 8 11 41
11 Farul Constanta 30 10 7 13 37
12 Petrolul Ploiesti 30 7 11 12 32
13 Csikszereda 30 8 8 14 32
14 Unirea Slobozia 30 7 4 19 25
15 AFC Hermannstadt 30 5 8 17 23
16 Metaloglobus 30 2 6 22 12
# TEAM MP GS GC +/- PTS
1 FCSB 30 48 40 +8 46
2 Oţelul 30 39 32 +7 41
3 Farul Constanta 30 39 37 +2 37
4 Uta Arad 30 39 44 -5 43
5 FC Botosani 30 37 29 +8 42
6 Csikszereda 30 30 58 -28 32
7 AFC Hermannstadt 30 29 50 -21 23
8 Unirea Slobozia 30 27 46 -19 25
9 Metaloglobus 30 25 66 -41 12
10 Petrolul Ploiesti 30 24 31 -7 32
11 Universitatea Cluj 10 13 11 +2 46
12 Dinamo Bucuresti 10 13 12 +1 39
13 Universitatea Craiova 10 12 6 +6 50
14 CFR 1907 Cluj 10 8 7 +1 43
15 Rapid 10 8 14 -6 34
16 Arges Pitesti 10 6 10 -4 32
# TEAM MP xG xGC +/- PTS
1 FCSB 30 50.6 28.2 +22.4 46
2 Dinamo Bucuresti 10 43.7 24.3 +19.4 39
3 Universitatea Craiova 10 37.5 24.4 +13.1 50
4 Oţelul 30 41.3 33.1 +8.2 41
5 Farul Constanta 30 37.8 33.2 +4.6 37
6 CFR 1907 Cluj 10 34.8 32.4 +2.4 43
7 Rapid 10 35.3 33.2 +2.1 34
8 FC Botosani 30 33.9 32.2 +1.7 42
9 Universitatea Cluj 10 32.0 30.8 +1.2 46
10 Arges Pitesti 10 26.0 25.8 +0.2 32
11 AFC Hermannstadt 30 29.8 31.9 -2.1 23
12 Petrolul Ploiesti 30 28.9 34.5 -5.6 32
13 Uta Arad 30 33.5 42.0 -8.5 43
14 Unirea Slobozia 30 26.9 39.8 -12.9 25
15 Metaloglobus 30 23.1 42.4 -19.3 12
16 Csikszereda 30 22.9 49.8 -26.9 32
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