Statistics / Football / Romania. Liga I / Farul Constanta vs FC Botosani

Farul Constanta vs FC Botosani Statistics & Analysis

Farul Constanta Farul Constanta
May 02, 2026 - 14:30
1 1.20
1 1.48
xG Accuracy: 83%
FC Botosani FC Botosani
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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 FC Botosani Draw ✖ Incorrect
  • Correct Score Insights 1-1 1-1 ✔ Correct

AI match briefing

AI Match Summary

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

  • League: Liga I
  • Fixture: Farul Constanta vs FC Botosani
  • Kickoff: 2026-05-02 14:00:00
  • 1X2 (model): Home 29.2% · Draw 28.8% · Away 42.0%
  • xG (showing): Farul Constanta 1.2 — FC Botosani 1.48 (total xG ≈ 2.68)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 49.9% · Implied: 45.9% · Probability edge: +4.0 pts · Est. EV: +8.8%
  • BTTS (model): Yes 55.6% · No 44.4%
  • Correct score (top bin): 1-1 (12.2%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

1X2 can look balanced even when side markets show clearer structure.

Best Bet + Reason

Primary angle highlighted on the page: Under 2.5 goals.

Model probability is compared to implied probability from odds to highlight a probability edge; EV uses the same model probability with the best decimal price tracked.

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

FAQ

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.

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.

Why might 1X2 look unattractive while totals do not?

Tight 1X2 prices often embed a fair three-way split, so EV on match-winner can sit negative even when Over/Under or BTTS still diverges from the model — compare the 1X2 row on the market cards to O/U and BTTS.

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

May 17, 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 8 5 1 2 46
2 Universitatea Cluj 8 6 0 2 45
3 CFR 1907 Cluj 9 4 3 2 42
4 Dinamo Bucuresti 9 3 3 3 38
5 Rapid 9 1 2 6 33
6 Arges Pitesti 9 1 3 5 31
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 8 12 5 +7 45
12 Dinamo Bucuresti 9 12 11 +1 38
13 Rapid 9 8 14 -6 33
14 Universitatea Craiova 8 7 6 +1 46
15 CFR 1907 Cluj 9 7 6 +1 42
16 Arges Pitesti 9 5 9 -4 31
# TEAM MP xG xGC +/- PTS
1 FCSB 30 50.6 28.2 +22.4 46
2 Dinamo Bucuresti 9 43.7 24.3 +19.4 38
3 Universitatea Craiova 8 37.5 24.4 +13.1 46
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 9 34.8 32.4 +2.4 42
7 Rapid 9 35.3 33.2 +2.1 33
8 FC Botosani 30 33.9 32.2 +1.7 42
9 Universitatea Cluj 8 32.0 30.8 +1.2 45
10 Arges Pitesti 9 26.0 25.8 +0.2 31
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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