Petrolul vs CFR Cluj prediction

Liga I
PetrolulPetrolulDWLDW
Sat, 31 Oct 202631/1017:00UK
CFR ClujCFR ClujWLWLD
38.9%Home winFair odds 2.57
28.7%DrawFair odds 3.48
32.4%Away winFair odds 3.09
Most likely published score1-113.6%Fair odds 7.35

MODELS TOP 3

Based on the Road2Sushi model. Not guaranteed outcomes.

Under 3.5 goalsBoth teams combined77.2%
Over 1.5 goalsBoth teams combined70.5%
Petrolul or draw67.6%

Early prediction · Model generated · Bookmaker odds pending.

Our verdict

Road2Sushi's own call on this match: the likeliest result, how confident the model is, its strongest signals and the reasons behind them.

Every percentage is a model estimate and every fair price is 1 divided by that estimate. Neither is a bookmaker offer, and a model call is not a proven edge over the market.

Model pick

Petrolul
Match winner (1X2)38.9%
Fair odds2.57
Save model pickSaved to my bets

Top signals

Goals marketUnder 3.5 goals
Model estimateModel77.2%
Fair oddsFair1.30
Double chance marketPetrolul or draw
Model estimateModel67.6%
Fair oddsFair1.48
Both teams to scoreBoth teams to score
Model estimateModel50.0%
Fair oddsFair2.00

Model read

An open result market: Petrolul lead at 38.9%, with draw 28.7% and CFR Cluj at 32.4%. No result has a majority of the model probability. Under 2.5 goaRead full analysisShow less

An open result market: Petrolul lead at 38.9%, with draw 28.7% and CFR Cluj at 32.4%. No result has a majority of the model probability. Under 2.5 goals stands out at 56.1%. The estimate leans this way, with substantial uncertainty remaining. Without a complete matching price comparison, this is an event read rather than a verified price opportunity.

Under 2.5 goals

Model estimate
56.1%
Fair odds
1.78

Not both teams to score

Model estimate
50.0%
Fair odds
2.00

Context & limits

  • Petrolul: 2 wins, 2 draws and 1 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • CFR Cluj: 2 wins, 1 draws and 2 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • The last 5 recorded meetings averaged 1.8 goals. This is a historical sample, not a forecast for this fixture.
  • Recorded season averages: Petrolul 1.4 and CFR Cluj 1.5 goals scored per game. These are team averages, not a forecast of this match total.
  • A complete matching price comparison is unavailable for this selection, so a price edge cannot be established.
Additional match context

The probabilities barely separate Petrolul and CFR Cluj on 31 October 2026: Petrolul nose ahead at 39%. Three angles decide this preview: 1) The model expects a tight, grinding game, just 44% on Over 2.5 with both teams to score at 50%. 2) Head to head, the last 5 meetings gave 1 wins for Petrolul, 1 draws and 3 for CFR Cluj, averaging 1.8 goals a game. 3) Form guide over the last six: Petrolul W3 D2 L1, CFR Cluj W2 D1 L3. Verdict: no bet. No bookmaker price published for this match yet.

Form & head-to-head

Recent form uses each club’s available results in their stored order. Select a W/D/L result for details.

Head-to-head figures use their own recorded sample. Where individual results are available, the figures and journal cover the same meetings. Missing results are never counted as draws.

PetrolulPetrolulLast 5
D
Draw · 2-2
W
Win · 2-0
L
Loss · 1-3
D
Draw · 1-1
W
Win · 3-1

2 wins · 2 draws · 1 loss

CFR ClujCFR ClujLast 5
W
Win · 3-1
L
Loss · 1-3
W
Win · 1-0
L
Loss · 0-1
D
Draw · 2-2

2 wins · 1 draw · 2 losses

W Win
D Draw
L Loss

Head-to-head

Last 5 meetings

1PetrolulPetrolul wins
1Draws
3CFR ClujCFR Cluj wins
1.8Average goals
Date
Home team
Score
Away team
CFR ClujCFR Cluj
2 – 1
PetrolulPetrolul
PetrolulPetrolul
1 – 0
CFR ClujCFR Cluj
CFR ClujCFR Cluj
2 – 0
PetrolulPetrolul
PetrolulPetrolul
0 – 0
CFR ClujCFR Cluj
PetrolulPetrolul
1 – 2
CFR ClujCFR Cluj

Odds: model vs bookmaker

Every price for this match in one place: the model's probabilities next to the bookmaker's, the bookmaker's prices with our gap, and the model's own fair odds for each market.

Bookmaker probabilities are de-vigged (the margin is removed) and come from one bookmaker. A gap between the model and that bookmaker is a disagreement, not a proven edge. Fair odds are 1 divided by the model probability, not a bookmaker quote.

Model probabilities

Model estimates and recorded bookmaker probabilities.

1X2

No recorded bookmaker price for this market.

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 38.9%
Petrolul

Model minus market: —
Market probability: —
Model probability: 28.7%
Draw

Model minus market: —
Market probability: —
Model probability: 32.4%
CFR Cluj

Model minus market: —
Market probability: —

Goals

No recorded bookmaker price for this market.

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 90.6%
Over 0.5 goals

Model minus market: —
Market probability: —
Model probability: 9.4%
Under 0.5 goals

Model minus market: —
Market probability: —
Model probability: 70.5%
Over 1.5 goals

Model minus market: —
Market probability: —
Model probability: 29.5%
Under 1.5 goals

Model minus market: —
Market probability: —
Model probability: 43.9%
Over 2.5 goals

Model minus market: —
Market probability: —
Model probability: 56.1%
Under 2.5 goals

Model minus market: —
Market probability: —
Model probability: 22.8%
Over 3.5 goals

Model minus market: —
Market probability: —
Model probability: 77.2%
Under 3.5 goals

Model minus market: —
Market probability: —
Model probability: 10.0%
Over 4.5 goals

Model minus market: —
Market probability: —
Model probability: 90.0%
Under 4.5 goals

Model minus market: —
Market probability: —
Model probability: 3.8%
Over 5.5 goals

Model minus market: —
Market probability: —
Model probability: 96.2%
Under 5.5 goals

Model minus market: —
Market probability: —
Model probability: 50.0%
Both teams to score · Yes

Model minus market: —
Market probability: —
Model probability: 50.0%
Both teams to score · No

Model minus market: —
Market probability: —

Cards

No estimates available for this market.

Corners

No estimates available for this market.

Shots

No estimates available for this market.

Market comparison awaits bookmaker odds

Comparable bookmaker odds are not available for these outcomes yet.

Model fair odds

Our published model probability as a decimal price (1 divided by probability). A fair model price, not a bookmaker quote. Only the supported 1X2 calibration pool is calibrated; other markets retain their model estimates.

Match result

Petrolul win2.57
Draw3.48
CFR Cluj win3.09
Both teams to score2.00

Goals

Over 0.5 goals1.10
Over 1.5 goals1.42
Over 2.5 goals2.28
Over 3.5 goals4.39
Petrolul most2.57
CFR Cluj most3.09

Totals line guide

Both teams combined.

Over 0.590.6%Over 1.570.5%Over 2.543.9%Over 3.522.8%Over 4.510.0%Over 5.53.8%
Recommended focusOver 1.570.5%

Discipline: Our price. No bookmaker price published for this match yet.

Read context

Both teams combined. Each bar uses the stored model estimate for that exact total-goals line. Missing estimates are unavailable; they are not zero.

Fair odds are the model’s own probability price, not a published bookmaker offer.

Market explorer

Model probabilities and fair odds.

Each bar is a specific Over selection for both teams combined. Its height is the model probability, on the same 0–100% scale.

Risk describes estimated likelihood, not profitability: low risk at least 62%, medium 48% to under 62%, high below 48%. Colors follow the actual estimate, even when a risk band is missing.

Up to four markets are selected from available model data, prioritising a spread of risk profiles. Fair odds are calculated from the model, not bookmaker prices: 1 divided by probability.

Scores are exact home-away outcomes from zero to five goals per team. Unavailable estimates stay blank; partial inputs are not expanded, inferred or normalised. Scores outside the matrix remain eligible for the top three.

Low riskMedium riskHigh risk

Goals

Over 0.50.5 goals, Low risk
Model probability 90.6%
Fair odds Fair 1.10
Over 1.51.5 goals, Low risk
Model probability 70.5%
Fair odds Fair 1.42
Over 2.52.5 goals, High risk
Model probability 43.9%
Fair odds Fair 2.28
Correct score probabilitiesModel probability / Fair odds
Goal axes Home goals
Away goals 0 1 2 3 4 5
Away goals 0 0-09.4%Fair odds 10.59 1-010.6%Fair odds 9.41 2-07.2%Fair odds 13.81 3-03.1%Fair odds 32.26 4-01.0%Fair odds 101.01 5-00.3%Fair odds 384.62
Away goals 1 0-19.4%Fair odds 10.59 1-113.6%Fair odds 7.35 2-18.3%Fair odds 12.03 3-13.6%Fair odds 28.09 4-11.1%Fair odds 87.72 5-10.3%Fair odds 344.83
Away goals 2 0-25.8%Fair odds 17.27 1-27.4%Fair odds 13.44 2-24.8%Fair odds 20.96 3-22.0%Fair odds 49.02 4-20.7%Fair odds 151.52 5-20.2%Fair odds 588.24
Away goals 3 0-32.2%Fair odds 45.05 1-32.9%Fair odds 35.09 2-31.8%Fair odds 54.64 3-30.8%Fair odds 128.21 4-30.3%Fair odds 400.00 5-30.1%Fair odds 1,666.67
Away goals 4 0-40.6%Fair odds 156.25 1-40.8%Fair odds 121.95 2-40.5%Fair odds 192.31 3-40.2%Fair odds 454.55 4-40.1%Fair odds 1,428.57 5-40.0%Fair odds 5,000.00
Away goals 5 0-50.2%Fair odds 666.67 1-50.2%Fair odds 526.32 2-50.1%Fair odds 833.33 3-50.1%Fair odds 2,000.00 4-50.0%Fair odds 5,000.00 5-50.0%Fair odds ·

Model’s 3 most likely score outcomes

Model probability · Fair odds

1-1
Model probability13.6%
Fair odds7.35
1-0
Model probability10.6%
Fair odds9.41
0-0
Model probability9.4%
Fair odds10.59

Referee

One match referee is shown from an explicitly saved result or a fresh, identity-matched provider fixture. Previous referees are never used to guess an appointment. An API listing can change.

The referee’s totals count every completed match with this referee in our data: football-data.co.uk names the referee in English leagues, and API-Football names the referee of the same match (same teams, date and score) in every league from 2025/26. A rate needs at least 5 matches with that figure.

The team table shows each team’s published history with that same referee only. Matches, team cards per game and match cards per game are separate fields; their available samples can differ. Missing values are not zero. Cards include yellow and red cards in the current historical source.

Referee not confirmed

No referee assignment is confirmed in our data yet. We never guess one from past matches.

Season stats

2026/27 season. Recorded results, not model estimates.

PetrolulPetrolul
CFR ClujCFR Cluj

Overview

Statistic
Petrolul
CFR Cluj
League position
#4 of 16
#9 of 16
Matches played
13
13
Record W-D-L
7-2-4
5-2-6
Recent form
DWLDW
Last 5 matches
WLWLD
Last 5 matches
Current streak
W1
D1
Points per game
1.77
1.31
Record, home vs away
4-1-1
2-0-5
PPG, home vs away
2.17
0.86

PPG scale: 0–3 points per game. Each team uses the same scale independently.

Show all season statsHide season stats

Goals

Statistic
Petrolul
CFR Cluj
Goals scored per game
1.38
1.46
Goals conceded per game
1.31
1.54
Scored, home vs away
1.17
1.00
Conceded, home vs away
0.50
2.00
1st half goals per game
0.85
0.77
2nd half goals per game
0.54
0.69

Scale: 0–3 goals or expected goals (xG) per game. Each team uses the same scale independently.

Shooting

Statistic
Petrolul
CFR Cluj
Shots per game
12.9
13.5
Shots faced per game
16.5
16.0
Shots on target per game
4.4
4.7
1st half shots per game
5.6
5.5
2nd half shots per game
7.3
8.1

Scale: 0–20 shots per game. Each team uses the same scale independently.

Corners & discipline

Statistic
Petrolul
CFR Cluj
Corners won per game
3.7
4.5
Fouls per game
11.1
11.0
Red cards this season
—
0

0–10 corners per game; 0–20 fouls per game Each team uses the same scale independently.

Goal rates

Statistic
Petrolul
CFR Cluj
Over 2.5 rate
46.2%
69.2%
BTTS rate
46.2%
53.8%
Clean sheets
30.8%
30.8%

Scale: 0–100% of recorded matches, not model estimates. Each team uses the same scale independently.

League averages this season: 2.74 goals per match · Over 2.5 in 50.0% · BTTS in 48.1%. Full league tables & stats →

First half / second half

Averages per game in this season’s league matches, split at half-time. Games is the number of each team’s matches with verified half data for that row; below five matches the row stays blank, and a missing value is never a zero.

Corners, shots on target and yellow cards per half come from the data provider’s half-by-half match statistics and are only used when the two halves add up to the full-time count. Cards are split by the minute they were shown, and first-half stoppage time counts as the first half. These are recorded results, not predictions.

In the Premier League, La Liga, Bundesliga, Serie A and Ligue 1 the shots per half come from a different source than the match shot totals, so the two can differ slightly.

PetrolulPetrolul
Petrolul: season average per game by half
Per game 1H 2H Games
Goals scoredScored 0.85 0.54 13
Goals concededConceded 0.77 0.54 13
Shots 5.6 7.3 13
Shots facedOpp. shots 8.7 7.8 13
Shots on targetOn target 2.2 2.2 13
Shots on target facedOpp. on target 2.7 3.0 13
Corners wonCorners 1.9 1.9 13
Corners concededOpp. corners 2.5 2.5 13
Yellow cardsYellows 0.4 1.9 10
Opponent yellow cardsOpp. yellows 1.0 1.5 10
CFR ClujCFR Cluj
CFR Cluj: season average per game by half
Per game 1H 2H Games
Goals scoredScored 0.77 0.69 13
Goals concededConceded 0.46 1.08 13
Shots 5.5 8.1 13
Shots facedOpp. shots 8.3 7.7 13
Shots on targetOn target 2.0 2.7 13
Shots on target facedOpp. on target 2.5 2.8 13
Corners wonCorners 2.0 2.5 13
Corners concededOpp. corners 2.3 2.7 13
Yellow cardsYellows 0.8 0.8 12
Opponent yellow cardsOpp. yellows 0.6 0.9 12
All model outcomes · full market spectrum & player markets

Shots

Shots on target

Cards

Clean sheet & win to nil

Worked out from the scoreline grid above: a clean sheet is every scoreline where the other side fails to score. It is the model’s own percentage, scored against the result afterwards, and it is not a tip.

Petrolul clean sheet 31.7%
CFR Cluj clean sheet 27.7%
Petrolul win to nil 22.2%
CFR Cluj win to nil 18.2%

Full market spectrum · model probabilities

The model’s own percentages, with no odds attached. The smaller markets are here so you can see everything we hold a number on, not because we claim an advantage in them. The colour says how close our percentages have landed to reality on matches the model had never seen. This is the raw model spectrum. Its match-result marginal can differ from the published 1X2 above; it does not replace the saved prediction.

Match result & goals calibrated
1×2
home 38.9% draw 28.7% away 32.4%
double_chance
1X 67.6% 12 71.3% X2 61.1%
dnb
home 54.6% away 45.4%
btts
yes 50.0% no 50.0%
clean_sheet
home 31.7% away 27.7%
win_to_nil
home 22.3% away 18.3%
winning_margin
home_by_1 21.3% home_by_2 11.5% home_by_3plus 6.2%
away_by_1 19.0% away_by_2 9.2% away_by_3plus 4.2%
correct_score
0-0 9.4% 0-1 9.4% 0-2 5.8%
0-3 2.2% 0-4 0.6% 0-5 0.2%
1-0 10.6% 1-1 13.6% 1-2 7.4%
1-3 2.9% 1-4 0.8% 1-5 0.2%
2-0 7.2% 2-1 8.3% 2-2 4.8%
2-3 1.8% 2-4 0.5% 2-5 0.1%
3-0 3.1% 3-1 3.6% 3-2 2.0%
3-3 0.8% 3-4 0.2% 3-5 0.1%
4-0 1.0% 4-1 1.1% 4-2 0.7%
4-3 0.3% 4-4 0.1% 4-5 0.0%
5-0 0.3% 5-1 0.3% 5-2 0.2%
5-3 0.1% 5-4 0.0% 5-5 0.0%
other 0.3%
likeliest_score
h 100.0% a 100.0% p 13.6%
Goals: totals / handicap / exact calibrated
total
over_0.5 90.6% under_0.5 9.4% over_1.5 70.5%
under_1.5 29.5% over_2.5 43.9% under_2.5 56.1%
over_3.5 22.8% under_3.5 77.2% over_4.5 10.0%
under_4.5 90.0% over_5.5 3.8% under_5.5 96.2%
odd_even
odd 48.3% even 51.7%
team_home
over_0.5 72.3% under_0.5 27.7% over_1.5 36.7%
under_1.5 63.3% over_2.5 13.9% under_2.5 86.1%
team_away
over_0.5 68.3% under_0.5 31.7% over_1.5 31.9%
under_1.5 68.2% over_2.5 11.0% under_2.5 89.1%
most
home 38.9% draw 28.7% away 32.4%
handicap
home_-2.5 6.2% away_+2.5 93.9% home_-1.5 17.7%
away_+1.5 82.3% home_-0.5 38.9% away_+0.5 61.1%
home_+0.5 67.6% away_-0.5 32.4% home_+1.5 86.5%
away_-1.5 13.5% home_+2.5 95.8% away_-2.5 4.2%
total_exact
exact_0 9.4% exact_1 20.1% exact_2 26.6%
exact_3 21.1% exact_4 12.8% exact_5 6.2%
exact_6 2.5% exact_7plus 1.2%
Method, limits & performance

How this works (honestly)

We are transparent about our method, our limits and how we measure performance.

What we use

Results, odds & closing prices, xG, shots, lineups, referee and schedule load.

Our method

Dixon-Coles + an xG strength model + champion/challenger selection + probability calibration + a trust gate.

What we don’t do

We do not beat the sharp market. The value is honest probabilities, No-bet calls and CLV.

Performance snapshot

Top-pick hit rate 47.7% (reliability, not edge). Calibration error 0.0106 (56038 matches).

Not financial advice. No model beats the sharp closing market on public data. The value here is honest probabilities, No-bet calls, and CLV history.

Explore this match