Otelul vs Sepsi Sf. Gheorghe prediction

Liga I
OtelulOtelulLLLDL
Sun, 1 Nov 20261/1113:00UK
Sepsi Sf. GheorgheGheorgheWLLDL
58.5%Home winFair odds 1.71
23.7%DrawFair odds 4.22
17.9%Away winFair odds 5.59
Most likely published score1-111.3%Fair odds 8.87

MODELS TOP 3

Based on the Road2Sushi model. Not guaranteed outcomes.

Otelul or draw82.2%
Over 1.5 goalsBoth teams combined76.5%
Under 3.5 goalsBoth teams combined70.4%

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

Otelul
Match winner (1X2)58.5%
Fair odds1.71
Save model pickSaved to my bets

Top signals

Double chance marketOtelul or draw
Model estimateModel82.2%
Fair oddsFair1.22
Goals marketOver 1.5 goals
Model estimateModel76.5%
Fair oddsFair1.31
Both teams to scoreBoth teams to score
Model estimateModel50.8%
Fair oddsFair1.97

Model read

Otelul lead the result estimates at 58.5%. The match still has meaningful room for a draw or an opponent win. Otelul win stands out at 58.5%. The estiRead full analysisShow less

Otelul lead the result estimates at 58.5%. The match still has meaningful room for a draw or an opponent win. Otelul win stands out at 58.5%. 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.

Otelul win

Model estimate
58.5%
Fair odds
1.71

Over 2.5 goals

Model estimate
51.8%
Fair odds
1.93

Both teams to score

Model estimate
50.8%
Fair odds
1.97

Context & limits

  • Otelul: 0 wins, 1 draws and 4 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • Sepsi Sf. Gheorghe: 1 wins, 1 draws and 3 losses in the last 5 recorded matches. Recent form is context, not an extra win probability.
  • The last 5 recorded meetings averaged 2.8 goals. This is a historical sample, not a forecast for this fixture.
  • A complete matching price comparison is unavailable for this selection, so a price edge cannot be established.
Additional match context

"When model and market disagree on Otelul, that gap is the story." Otelul go into this Liga I meeting with Sepsi Sf. Gheorghe on 1 November 2026 as clear favourites; our model has them at 58%. No strong lean on goals (52% Over 2.5). The interest, if any, lives elsewhere. The run in: Otelul arrive W0 D1 L5, Sepsi Sf. Gheorghe W1 D1 L4. Sepsi Sf. Gheorghe are newly promoted, a profile the model deliberately prices with caution. The recent series reads 2 wins for Otelul, 1 draws and 2 for Sepsi Sf. Gheorghe over 5 games, 2.8 goals on average. The engine passes on this one (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.

OtelulOtelulLast 5
L
Loss · 0-3
L
Loss · 2-3
L
Loss · 0-1
D
Draw · 1-1
L
Loss · 3-4

0 wins · 1 draw · 4 losses

Sepsi Sf. GheorgheGheorgheLast 5
W
Win · 3-1
L
Loss · 0-1
L
Loss · 0-2
D
Draw · 1-1
L
Loss · 0-5

1 win · 1 draw · 3 losses

W Win
D Draw
L Loss

Head-to-head

Last 5 meetings

2OtelulOtelul wins
1Draws
2Sepsi Sf. GheorgheGheorghe wins
2.8Average goals
Date
Home team
Score
Away team
Sepsi Sf. GheorgheGheorghe
0 – 3
OtelulOtelul
Sepsi Sf. GheorgheGheorghe
2 – 0
OtelulOtelul
OtelulOtelul
2 – 0
Sepsi Sf. GheorgheGheorghe
OtelulOtelul
2 – 3
Sepsi Sf. GheorgheGheorghe
Sepsi Sf. GheorgheGheorghe
1 – 1
OtelulOtelul

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: 58.5%
Otelul

Model minus market: —
Market probability: —
Model probability: 23.7%
Draw

Model minus market: —
Market probability: —
Model probability: 17.9%
Sepsi Sf. Gheorghe

Model minus market: —
Market probability: —

Goals

No recorded bookmaker price for this market.

ModelProbability (%)
Outcome
MarketProbability (%)
Model probability: 93.0%
Over 0.5 goals

Model minus market: —
Market probability: —
Model probability: 7.0%
Under 0.5 goals

Model minus market: —
Market probability: —
Model probability: 76.5%
Over 1.5 goals

Model minus market: —
Market probability: —
Model probability: 23.5%
Under 1.5 goals

Model minus market: —
Market probability: —
Model probability: 51.8%
Over 2.5 goals

Model minus market: —
Market probability: —
Model probability: 48.2%
Under 2.5 goals

Model minus market: —
Market probability: —
Model probability: 29.6%
Over 3.5 goals

Model minus market: —
Market probability: —
Model probability: 70.4%
Under 3.5 goals

Model minus market: —
Market probability: —
Model probability: 14.4%
Over 4.5 goals

Model minus market: —
Market probability: —
Model probability: 85.6%
Under 4.5 goals

Model minus market: —
Market probability: —
Model probability: 6.1%
Over 5.5 goals

Model minus market: —
Market probability: —
Model probability: 94.0%
Under 5.5 goals

Model minus market: —
Market probability: —
Model probability: 50.8%
Both teams to score · Yes

Model minus market: —
Market probability: —
Model probability: 49.2%
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

Otelul win1.71
Draw4.22
Sepsi Sf. Gheorghe win5.59
Both teams to score1.97

Goals

Over 0.5 goals1.07
Over 1.5 goals1.31
Over 2.5 goals1.93
Over 3.5 goals3.38
Otelul most1.71
Sepsi Sf. Gheorghe most5.60

Totals line guide

Both teams combined.

Over 0.593.0%Over 1.576.5%Over 2.551.8%Over 3.529.6%Over 4.514.4%Over 5.56.1%
Recommended focusOver 1.576.5%

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 1.51.5 goals, Low risk
Model probability 76.5%
Fair odds Fair 1.31
Over 2.52.5 goals, Medium risk
Model probability 51.8%
Fair odds Fair 1.93
Over 3.53.5 goals, High risk
Model probability 29.6%
Fair odds Fair 3.38
Correct score probabilitiesModel probability / Fair odds
Goal axes Home goals
Away goals 0 1 2 3 4 5
Away goals 0 0-07.0%Fair odds 14.37 1-011.2%Fair odds 8.90 2-010.8%Fair odds 9.28 3-06.6%Fair odds 15.17 4-03.0%Fair odds 33.11 5-01.1%Fair odds 90.09
Away goals 1 0-15.3%Fair odds 18.80 1-111.3%Fair odds 8.87 2-19.8%Fair odds 10.16 3-16.0%Fair odds 16.64 4-12.8%Fair odds 36.23 5-11.0%Fair odds 99.01
Away goals 2 0-22.7%Fair odds 37.31 1-24.9%Fair odds 20.41 2-24.5%Fair odds 22.27 3-22.8%Fair odds 36.36 4-21.3%Fair odds 79.37 5-20.5%Fair odds 217.39
Away goals 3 0-30.8%Fair odds 123.46 1-31.5%Fair odds 67.11 2-31.4%Fair odds 72.99 3-30.8%Fair odds 119.05 4-30.4%Fair odds 263.16 5-30.1%Fair odds 714.29
Away goals 4 0-40.2%Fair odds 526.32 1-40.3%Fair odds 294.12 2-40.3%Fair odds 322.58 3-40.2%Fair odds 526.32 4-40.1%Fair odds 1,111.11 5-40.0%Fair odds 3,333.33
Away goals 5 0-50.0%Fair odds 3,333.33 1-50.1%Fair odds 1,666.67 2-50.1%Fair odds 1,666.67 3-50.0%Fair odds 3,333.33 4-50.0%Fair odds 5,000.00 5-50.0%Fair odds 10,000.00

Model’s 3 most likely score outcomes

Model probability · Fair odds

1-1
Model probability11.3%
Fair odds8.87
1-0
Model probability11.2%
Fair odds8.90
2-0
Model probability10.8%
Fair odds9.28

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.

OtelulOtelul
Sepsi Sf. GheorgheGheorghe

Overview

Statistic
Otelul
Sepsi Sf. Gheorghe
League position
#14 of 16
#12 of 16
Matches played
13
13
Record W-D-L
2-5-6
3-5-5
Recent form
LLLDL
Last 5 matches
WLLDL
Last 5 matches
Current streak
L1
L1
Points per game
0.85
1.08
Record, home vs away
2-3-2
1-3-3
PPG, home vs away
1.29
0.86

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

Show all season statsHide season stats

Goals

Statistic
Otelul
Sepsi Sf. Gheorghe
Goals scored per game
1.15
0.62
Goals conceded per game
1.62
1.38
Scored, home vs away
1.14
0.43
Conceded, home vs away
1.14
1.29
1st half goals per game
0.38
0.25
2nd half goals per game
0.77
0.42

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

Shooting

Statistic
Otelul
Sepsi Sf. Gheorghe
Shots per game
14.0
11.5
Shots faced per game
15.2
16.5
Shots on target per game
4.4
3.6
1st half shots per game
5.4
4.8
2nd half shots per game
8.6
6.7

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

Corners & discipline

Statistic
Otelul
Sepsi Sf. Gheorghe
Corners won per game
5.1
3.3
Cards per game
1.9
—
Fouls per game
11.9
12.0
Red cards this season
4
—

0–10 corners per game; 0–5 cards per game; 0–20 fouls per game Each team uses the same scale independently.

Goal rates

Statistic
Otelul
Sepsi Sf. Gheorghe
Over 2.5 rate
46.2%
23.1%
BTTS rate
61.5%
30.8%
Clean sheets
7.7%
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.

OtelulOtelul
Otelul: season average per game by half
Per game 1H 2H Games
Goals scoredScored 0.38 0.77 13
Goals concededConceded 0.69 0.92 13
Shots 5.4 8.6 13
Shots facedOpp. shots 6.5 8.6 13
Shots on targetOn target 1.8 2.6 13
Shots on target facedOpp. on target 2.0 2.6 13
Corners wonCorners 2.1 3.0 12
Corners concededOpp. corners 2.6 1.8 12
Yellow cardsYellows 0.6 1.1 9
Opponent yellow cardsOpp. yellows 0.9 1.6 9
Sepsi Sf. GheorgheGheorghe
Sepsi Sf. Gheorghe: season average per game by half
Per game 1H 2H Games
Goals scoredScored 0.25 0.42 12
Goals concededConceded 0.75 0.33 12
Shots 4.8 6.7 12
Shots facedOpp. shots 7.8 8.7 12
Shots on targetOn target 1.8 1.8 12
Shots on target facedOpp. on target 2.7 2.3 12
Corners wonCorners 1.6 1.8 12
Corners concededOpp. corners 3.1 4.0 12
Yellow cardsYellows 0.7 1.2 9
Opponent yellow cardsOpp. yellows 0.6 1.2 9
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.

Otelul clean sheet 39.7%
Sepsi Sf. Gheorghe clean sheet 16.0%
Otelul win to nil 32.7%
Sepsi Sf. Gheorghe win to nil 9.0%

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 58.5% draw 23.7% away 17.8%
double_chance
1X 82.2% 12 76.3% X2 41.5%
dnb
home 76.6% away 23.4%
btts
yes 50.8% no 49.2%
clean_sheet
home 40.1% away 16.0%
win_to_nil
home 33.2% away 9.0%
winning_margin
home_by_1 24.2% home_by_2 18.2% home_by_3plus 16.1%
away_by_1 11.8% away_by_2 4.5% away_by_3plus 1.5%
correct_score
0-0 7.0% 0-1 5.3% 0-2 2.7%
0-3 0.8% 0-4 0.2% 0-5 0.0%
1-0 11.2% 1-1 11.3% 1-2 4.9%
1-3 1.5% 1-4 0.3% 1-5 0.1%
2-0 10.8% 2-1 9.8% 2-2 4.5%
2-3 1.4% 2-4 0.3% 2-5 0.1%
3-0 6.6% 3-1 6.0% 3-2 2.8%
3-3 0.8% 3-4 0.2% 3-5 0.0%
4-0 3.0% 4-1 2.8% 4-2 1.3%
4-3 0.4% 4-4 0.1% 4-5 0.0%
5-0 1.1% 5-1 1.0% 5-2 0.5%
5-3 0.1% 5-4 0.0% 5-5 0.0%
other 1.2%
likeliest_score
h 100.0% a 100.0% p 11.3%
Goals: totals / handicap / exact calibrated
total
over_0.5 93.0% under_0.5 7.0% over_1.5 76.5%
under_1.5 23.5% over_2.5 51.8% under_2.5 48.2%
over_3.5 29.6% under_3.5 70.4% over_4.5 14.4%
under_4.5 85.6% over_5.5 6.1% under_5.5 94.0%
odd_even
odd 48.7% even 51.3%
team_home
over_0.5 84.0% under_0.5 16.0% over_1.5 54.7%
under_1.5 45.3% over_2.5 27.8% under_2.5 72.2%
team_away
over_0.5 59.9% under_0.5 40.1% over_1.5 23.2%
under_1.5 76.8% over_2.5 6.5% under_2.5 93.5%
most
home 58.5% draw 23.7% away 17.8%
handicap
home_-2.5 16.1% away_+2.5 84.0% home_-1.5 34.3%
away_+1.5 65.7% home_-0.5 58.5% away_+0.5 41.5%
home_+0.5 82.2% away_-0.5 17.8% home_+1.5 94.0%
away_-1.5 6.1% home_+2.5 98.5% away_-2.5 1.5%
total_exact
exact_0 7.0% exact_1 16.6% exact_2 24.7%
exact_3 22.2% exact_4 15.2% exact_5 8.4%
exact_6 3.8% exact_7plus 2.2%
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